Showing 1–50 of 2,126 results for author: Fan, X

LoRA-GA$^2$: Low Rank Adaptation with Multi-step Gradient Adaptive Alignment

Authors: Haonan He, Xinyue Fan

Abstract: Low-Rank Adaptation (LoRA) is a prominent fine-tuning method for large models, achieving competitive performance with reduced memory overhead. However, a persistent performance gap remains between LoRA and full fine-tuning. Recent studies have sought to narrow this gap by employing one-step gradient approximations of pretrained weights to align LoRA updates with the principal directions or intrins… ▽ More Low-Rank Adaptation (LoRA) is a prominent fine-tuning method for large models, achieving competitive performance with reduced memory overhead. However, a persistent performance gap remains between LoRA and full fine-tuning. Recent studies have sought to narrow this gap by employing one-step gradient approximations of pretrained weights to align LoRA updates with the principal directions or intrinsic dimensionalities of full fine-tuning updates. Nevertheless, these approaches fail to capture the full dynamics of the gradients. In this paper, we propose LoRA-GA$^2$, an effective fine-tuning algorithm that fully leverages multi-step gradient information. Specifically, we introduce a lightweight probe for multi-step gradients of pretrained weights that incurs no additional GPU memory cost and only marginal time overhead. We further employ a spectrum-aware, importance-based rank allocation and optimal initialization derived from multi-step gradients. Extensive experimental results demonstrate that LoRA-GA$^2$ consistently outperforms existing LoRA variants while preserving the efficiency advantages of vanilla LoRA. For instance, LoRA-GA$^2$ surpasses the leading baseline by an average of 0.66 points on the GLUE benchmark, and outperforms the strongest baseline by 1.03 points on GSM8K and 0.87 points on HumanEval, respectively. △ Less

Submitted 20 August, 2026; originally announced August 2026.

Can Agent Memory Systems Track Evolving State?

Authors: Xinyi Fan, Miri Liu, Ruozhen Yang, Siru Ouyang, Jiawei Han

Abstract: As LLM-based agents are deployed for longer and higher-stakes tasks, their memory systems continue to have crucial gaps. While existing memory benchmarks focus largely on recall-shaped tasks, we argue an effective memory system must track the evolving state of the world; as facts, constraints, and decisions are revised over a long interaction, answers must reflect the current state and not a super… ▽ More As LLM-based agents are deployed for longer and higher-stakes tasks, their memory systems continue to have crucial gaps. While existing memory benchmarks focus largely on recall-shaped tasks, we argue an effective memory system must track the evolving state of the world; as facts, constraints, and decisions are revised over a long interaction, answers must reflect the current state and not a superseded one. We define this capability as state tracking and instantiate it in StateMemBench, a benchmark of 234 multi-session scenarios spanning two conversation-length regimes. Its closed-pool grading scores whether an answer reflects the current state, the superseded state, or fails otherwise, separating state-tracking failures from other errors by construction. Our analysis shows that this task is challenging for existing memory systems, retrieval-augmented baselines, and long-context baselines. We then present StateMem, a state-first memory method that explicitly tracks supersession and relational dependencies, and show it improves current-state accuracy over the strongest same-backbone baseline by 1.8x (0.205 -> 0.363) on DeepSeek-V4-Flash and over the strongest memory system by 1.6x (0.149 -> 0.233) on Qwen-3.5-9B, while remaining competitive with the long-context baselines. Finally, we show the same state approach can be applied as a lightweight single-call wrapper over existing memory systems, lifting current-state accuracy by +32 to +67 points on StateMemBench across six memory and retrieval backends. A length- and cost-matched control attributes +15 to +32 of those points to state structure rather than added context. △ Less

Submitted 20 August, 2026; originally announced August 2026.

Low Ly$α$ Visibility in Galaxy Overdensities: Reionization Topology and Neutral-Fraction Ceilings from DIVER over $4.8<z<11$

Authors: Yongda Zhu, Xiaohui Fan, Laura C. Keating, George D. Becker, Eiichi Egami, Xiaojing Lin, Fengwu Sun, Christopher Cain, Marcia J. Rieke, Andrew J. Bunker, Sijia Cai, Francesco D'Eugenio, Jakob M. Helton, Xiangyu Jin, Mingyu Li, Zheng Ma, Roberto Maiolino, Pierluigi Rinaldi, Christopher N. A. Willmer, Yunjing Wu, Zihao Wu, Junyu Zhang

Abstract: Ly-alpha emission is widely used to trace cosmic reionization, but its interpretation depends on how Ly-alpha visibility varies with galaxy environment. We use deep JWST/NIRSpec observations from Deep Insights into UV Spectroscopy at the Epoch of Reionization (DIVER) in GOODS-N to measure Ly-alpha visibility for 250 galaxies at 4.8<z<11. The sample contains 84 Ly-alpha detections, including 44 str… ▽ More Ly-alpha emission is widely used to trace cosmic reionization, but its interpretation depends on how Ly-alpha visibility varies with galaxy environment. We use deep JWST/NIRSpec observations from Deep Insights into UV Spectroscopy at the Epoch of Reionization (DIVER) in GOODS-N to measure Ly-alpha visibility for 250 galaxies at 4.8<z<11. The sample contains 84 Ly-alpha detections, including 44 strong emitters with rest-frame Ly-alpha equivalent width W_Lyalpha>25 A. We combine these measurements with H-alpha and [O III] emitters from JWST/NIRCam wide-field slitless spectroscopy to map the density field around each DIVER galaxy. Galaxies with high Ly-alpha equivalent widths (W_Lyalpha>25 A) or high effective Ly-alpha escape fractions (f_esc,Lyalpha^eff>0.05) tend to lie farther from nearby H-alpha and [O III] emitters than galaxies with lower Ly-alpha visibility. The clearest signal occurs near the prominent GOODS-N overdensity at z~5.2, where fewer than 15% of galaxies show strong Ly-alpha emission. This trend is opposite to the simplest inside-out reionization expectation that overdensities produce larger ionized regions and enhance Ly-alpha visibility. Possible explanations include circumgalactic and local intergalactic opacity, dense absorbers, and gas kinematics. We also derive an empirical upper envelope for f_esc,Lyalpha^eff and calibrate it with reionization simulations. Interpreting this envelope as a limiting IGM-attenuation signal gives neutral-fraction ceilings of <x_HI>_max=0.36, 0.76, 0.74, 0.84, and 1.0 at z~5.2, 5.8, 6.7, 7.7, and 9.8, respectively. The z~8 ceiling disfavors an almost completely neutral IGM at this epoch. These results support patchy reionization already underway by z~8 and show that galaxy Ly-alpha visibility encodes both large-scale ionization topology and near-source gas structure. △ Less

Submitted 19 August, 2026; originally announced August 2026.

Comments: 30 pages, 17 figures, 3 tables; submitted to ApJ

Adaptive Memory and Reflection Multi-Agent System for Medical Question Answering

Authors: Pradeep Murugesan, Luoxiao Yang, Xueli Chen, Xinqi Fan

Abstract: Accurate and responsible medical question answering (QA) is important in healthcare, where complex cases require factual knowledge and nuanced reasoning. Existing medical QA systems, typically based on single-agent architectures and static retrieval, often lack adaptability, persistent memory, and structured decision-making. This work introduces an adaptive memory and reflection (AMR) agentic syst… ▽ More Accurate and responsible medical question answering (QA) is important in healthcare, where complex cases require factual knowledge and nuanced reasoning. Existing medical QA systems, typically based on single-agent architectures and static retrieval, often lack adaptability, persistent memory, and structured decision-making. This work introduces an adaptive memory and reflection (AMR) agentic system, a multi-agent framework in which specialized agents use dedicated memory and reflection-based feedback to retrieve relevant prior cases and improve subsequent reasoning. Complexity assessment routes questions through solo, collaborative, or escalated workflows, while consensus and ethical overseer modules support reasoning consolidation and output review. Evaluation on MedQA and MedMCQA demonstrates strong performance compared with several baselines. Ablation studies show that combining agent-specific memory, reflection, and external retrieval yields the strongest performance. These findings highlight the potential of structured memory and feedback for developing more trustworthy medical agents. The source code is publicly available at https://github.com/mm-air/AMR-Agent. △ Less

Submitted 19 August, 2026; originally announced August 2026.

Comments: Accepted by IEEE SMC 2026

Quasar Impostors: Two Extremely UV-Bright ($M_{\rm UV}\approx-23.5$) Reionisation-Epoch Galaxies Powered by Very Massive Stars

Authors: Daming Yang, Joseph F. Hennawi, Sarah E. I. Bosman, Frederick B. Davies, Rychard Bouwens, Timo Kist, Eduardo Bañados, Jiamu Huang, Alice E. Shapley, Marianne Vestergaard, Hiddo S. B. Algera, Silvia Belladitta, Anna-Christina Eilers, Xiaohui Fan, Francesco Guarneri, Xiangyu Jin, Romain A. Meyer, Elia Pizzati, Huub Röttgering, Jan-Torge Schindler, Mauro Stefanon, Feige Wang, Jinyi Yang

Abstract: The extreme bright end of the galaxy UV luminosity function during reionisation remains poorly constrained, particularly where the galaxy and quasar luminosity functions overlap and source classification becomes ambiguous. We present JWST/NIRSpec and ALMA Band-6 observations of J1450-0144 ($z=6.627$) and J1429-0104 ($z=6.796$), two $M_{\rm UV}\simeq-23.5$ sources originally classified as faint qua… ▽ More The extreme bright end of the galaxy UV luminosity function during reionisation remains poorly constrained, particularly where the galaxy and quasar luminosity functions overlap and source classification becomes ambiguous. We present JWST/NIRSpec and ALMA Band-6 observations of J1450-0144 ($z=6.627$) and J1429-0104 ($z=6.796$), two $M_{\rm UV}\simeq-23.5$ sources originally classified as faint quasars by SHELLQs. NIRSpec reveals blue UV continua, strong P Cygni profiles in N V, Si IV, and C IV, broad He II $\lambda1640$ emission with rest-frame equivalent widths of $8.8\pm1.2$ and $3.7\pm1.1$ Å, respectively, and narrow nebular lines, reclassifying both as extremely UV-luminous galaxies. Standard population-synthesis models cannot simultaneously reproduce the strong He II and wind features, whereas models incorporating very massive stars (VMS; $M\gtrsim100\,M_\odot$) with dedicated wind prescriptions can. These models favor a star-formation duration of 2-4 Myr for J1450-0144, with a broader allowed range for J1429-0104, stellar masses of $\log(M_\star/M_\odot)\approx9.2$-$9.9$, and star-formation rates of $\simeq300$-$540\,M_\odot\,{\rm yr}^{-1}$. Under the same VMS wind models, equivalent-width diagnostics imply $M_{\rm up}\gtrsim225\,M_\odot$ for J1429-0104, while J1450-0144 lies beyond even the $M_{\rm up}=475\,M_\odot$ grid. ALMA detects luminous [C II] 158 $μ$m emission in both systems, with $L_{\rm [CII]}\approx0.8$ and $4.1\times10^{9}\,L_\odot$, respectively. J1429-0104 additionally shows bright dust continuum, with both [C II] and dust offset by $\sim5.4$ kpc from its UV emission. These sources demonstrate that VMS can power some of the most UV-luminous galaxies at cosmic dawn and show that source classifications, and hence the inferred demographics of both galaxies and quasars in the crossover regime, need revisiting. △ Less

Submitted 18 August, 2026; originally announced August 2026.

Comments: 18 figures, 4 tables. Submitted

FedPref: Federated Preference Learning for Structured Radiology Report Extraction

Authors: Flint Xiaofeng Fan, Cheston Tan, Yew-Soon Ong, Roger Wattenhofer

Abstract: Radiology reports describe findings and locations in free text, but downstream search and analysis require these relations in a fixed schema. Learning this extraction requires labels that are unevenly distributed across institutions: smaller hospitals have less local evidence, and pooling data may be infeasible. We introduce FedPref: frozen public language models propose alternative JSON extractio… ▽ More Radiology reports describe findings and locations in free text, but downstream search and analysis require these relations in a fixed schema. Learning this extraction requires labels that are unevenly distributed across institutions: smaller hospitals have less local evidence, and pooling data may be infeasible. We introduce FedPref: frozen public language models propose alternative JSON extractions, local annotations rank them, and sites collaboratively train compact Qwen3-8B adapters while sharing only model updates. A heterogeneous teacher pool provides cross-model contrast when repeated single-model samples collapse. On development data from six simulated hospitals with unequal data volume and disease prevalence, FedPref improves client-mean F1 by 2.49 points and worst-site F1 by 9.10 points compared with training each site in isolation, with the largest gains at the sites holding the least data. Central training on the pooled preference-pair union is 2.66 points higher on client-mean F1. On a locked, 400-report manually validated gold test set, FedPref reaches 68.68 F1 and pooled training 71.67, preserving that same ordering. FedPref thus lets institutions with unequal, unpooled data benefit from collaboration without ever sharing reports or annotations. △ Less

Submitted 17 August, 2026; originally announced August 2026.

Comments: Accepted at ELAMI 2026, held in conjunction with MICCAI 2026. To appear in the Springer proceedings

FreeToken: Efficient Edge-Native MoE Serving with Bandwidth-Adaptive Execution

Authors: Shuo Yang, Xiaoze Fan, Melissa Pan, Haocheng Xi, Zhe Wang, Shanlin Sun, Kurt Keutzer, Song Han, Matei Zaharia, Chenfeng Xu, Ion Stoica

Abstract: Frontier open-weight models are increasingly available, but serving them still largely assumes datacenter infrastructure. We present FreeToken, an edge-native MoE serving system that treats a personal machine not as a small GPU, but as a unified, elastic inference platform. FreeToken co-designs the full serving stack, including model layout and loading, expert residency, CPU--GPU execution, agenti… ▽ More Frontier open-weight models are increasingly available, but serving them still largely assumes datacenter infrastructure. We present FreeToken, an edge-native MoE serving system that treats a personal machine not as a small GPU, but as a unified, elastic inference platform. FreeToken co-designs the full serving stack, including model layout and loading, expert residency, CPU--GPU execution, agentic state reuse, and runtime memory management, around two realities of local AI: agent workloads continuously change their execution pattern, and edge hardware exposes heterogeneous resources whose balance differs from machine to machine. Rather than committing to a fixed offloading strategy, FreeToken continuously maps computation and model state onto the resources actually available. FreeToken supports more than 20 MoE models and real coding and tool-using agents across hardware ranging from an 8GB laptop GPU to a single workstation GPU. More importantly, it changes what these machines can practically serve, from a 35B model on a laptop to a 284B model on a gaming desktop and the 753B GLM-5.2 on a single workstation GPU. FreeToken turns open weights into deployable local software, making the machines users already own a practical platform for frontier-scale intelligence. We release the system at flashml.ai. △ Less

Submitted 17 August, 2026; originally announced August 2026.

Jet Power, Bulk Lorentz Factor, Black Hole Spin, and Magnetic Field of Accretion Disk in Jetted Active Galactic Nuclei: A Large Gamma-Ray Emission Sample

Authors: Dingrong Xiong, Junhui Fan, Feng Yuan, Jun-Xian Wang, Minfeng Gu, Yongquan Xue, Jirong Mao, Liang Chen, Rui Xue, Xu-Liang Fan, Yongyun Chen, Nan Ding, Fei Guo, Jia-Wen Li, Dahai Yan, Y. G. Zheng, Jinming Bai

Abstract: We present a catalog of physical parameters for powerful jet-accretion disk-black hole systems in one of the largest samples of gamma-ray emitting jetted active galactic nuclei (AGNs), including jet kinetic and radiative powers, jet radiative efficiencies, bulk Lorentz factors, black hole spins, accretion-disk magnetic fields and Compton dominance. Comparing jet kinetic power estimators for blazar… ▽ More We present a catalog of physical parameters for powerful jet-accretion disk-black hole systems in one of the largest samples of gamma-ray emitting jetted active galactic nuclei (AGNs), including jet kinetic and radiative powers, jet radiative efficiencies, bulk Lorentz factors, black hole spins, accretion-disk magnetic fields and Compton dominance. Comparing jet kinetic power estimators for blazars, values derived from spectral energy distribution (SED) fitting tend to exceed those estimated via cavity power and other scaling relations. For radiatively efficient AGNs, most sources are inferred to possess high spins; for radiatively inefficient AGNs, many potentially have high spins, though some may differ. This indicates that black hole spin does not effectively distinguish radiatively efficient from inefficient jetted AGNs. Our results suggest accretion-disk magnetic field strength as a key discriminator, proposing a tentative dividing value of $\approx 10^{3.9}$ Gauss between radiatively efficient and inefficient populations. Jet power and bulk Lorentz factor exhibit significant correlations with black hole mass in radiatively efficient AGNs, while weak-to-moderate correlations are observed in radiatively inefficient AGNs within narrow accretion-rate bins. Our analysis reveals that jet power correlates with both disk luminosity and magnetic field strength. Furthermore, correlations linking Eddington ratio and Compton dominance with jet properties are consistent with the jet-accretion connection. Finally, jet radiative power and bulk Lorentz factor show a potential dependence on black hole spin. These results are consistent with the scenario in which jets are powered and accelerated by energy extraction from rapidly spinning black holes via accretion-disk magnetic fields. △ Less

Submitted 15 August, 2026; originally announced August 2026.

Comments: 25 pages, 11 figures, 3 tables, accepted for publication in ApJ

High-precision measurement of the space-like $η^\prime$ transition form factor

Authors: BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, X. C. Ai, C. S. Akondi, R. Aliberti, A. Amoroso, Q. An, Y. H. An, M. S. Anderson, Y. Bai, O. Bakina, H. R. Bao, X. L. Bao, M. Barbagiovanni, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. B. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone , et al. (758 additional authors not shown)

Abstract: Using a data sample corresponding to an integrated luminosity of $20.3\ \text{fb}^{-1}$, collected with the BESIII detector at a center-of-mass energy of $3.773\ \text{GeV}$ at the BEPCII collider, we report a precision measurement of the product $Q^2|F(Q^2)|$, where $F(Q^2)$ is the single-virtual space-like transition form factor of the $η'$ meson and $Q^2$ is the squared momentum transfer of the… ▽ More Using a data sample corresponding to an integrated luminosity of $20.3\ \text{fb}^{-1}$, collected with the BESIII detector at a center-of-mass energy of $3.773\ \text{GeV}$ at the BEPCII collider, we report a precision measurement of the product $Q^2|F(Q^2)|$, where $F(Q^2)$ is the single-virtual space-like transition form factor of the $η'$ meson and $Q^2$ is the squared momentum transfer of the tagged virtual photon. The transition form factor is extracted from the differential Born cross section of the two-photon fusion processes $e^+e^- \to e^+e^-γγ^* \to e^+e^-η^\prime$ using a single-tag technique, where only one scattered lepton is detected. The measurement covers $Q^2 \in [0.1, 6.0]$ GeV$^2$, achieving unprecedented precision, better than $3.0\%$ for $Q^2 < 1.5$ GeV$^2$, and providing the first direct determination at $Q^2 < 0.3$ GeV$^2$. △ Less

Submitted 12 August, 2026; originally announced August 2026.

LIGO A$^\sharp$: Detector Design and Science Prospects Beyond A+

Authors: L. Sun, K. Kuns, B. J. J. Slagmolen, P. Fritschel, P. Schmidt, B. T. Lantz, S. S. Y. Chua, Divyajyoti, S. W. Ballmer, M. A. Barton, A. V. Cumming, K. L. Dooley, J. C. Driggers, A. Effler, M. Evans, B. Farr, G. González, N. Lu, D. J. Ottaway, C. Palomba, O. J. Piccinni, G. Pratten, S. Raja, A. P. Subhash, P. J. Sutton , et al. (1131 additional authors not shown)

Abstract: We present the LIGO A$^\sharp$ detector concept, an upgrade for the LIGO observatories based on room-temperature interferometers beyond the fifth observing run (O5). Building on the A+ sensitivity, A$^\sharp$ targets broadband sensitivity improvements through heavier test masses, improved suspensions and seismic isolation, increased arm-cavity power, enhanced frequency-dependent squeezing, reduced… ▽ More We present the LIGO A$^\sharp$ detector concept, an upgrade for the LIGO observatories based on room-temperature interferometers beyond the fifth observing run (O5). Building on the A+ sensitivity, A$^\sharp$ targets broadband sensitivity improvements through heavier test masses, improved suspensions and seismic isolation, increased arm-cavity power, enhanced frequency-dependent squeezing, reduced coating thermal noise considering two scenarios, and improved control of mechanical motion and optical modes. We describe the principal design choices, projected noise performance, and corresponding astrophysical prospects. LIGO A$^\sharp$ substantially increases compact-binary detection rates, strengthens population inference, and improves both early-warning times and localization for binary neutron star mergers. The improved sensitivity enables more detailed studies of compact-binary coalescences, including higher-order multipoles, intermediate-mass black holes, remnant black hole ringdown, and the neutron star equation of state. It also broadens the discovery potential for new gravitational-wave sources such as continuous waves and bursts, should enable detection of the stochastic background from compact binary mergers if it remains undetected after O5, and strengthens the role of gravitational-wave detectors as probes of fundamental physics. We discuss key technical challenges and the role of A$^\sharp$ as both a major scientific upgrade for the 2030s and a technology pathfinder for next-generation gravitational-wave observatories, such as Cosmic Explorer. △ Less

Submitted 12 August, 2026; originally announced August 2026.

Comments: 78 pages, 22 figures

Report number: LIGO-P2600307

Constraints on ultralight bosons from merging binary and remnant black holes observed during the second and third parts of the fourth LIGO-Virgo-KAGRA observing run

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, A. Abe, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, S. Adhicary, D. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu , et al. (1786 additional authors not shown)

Abstract: We present constraints on ultralight bosons using binary black hole mergers observed in the second and third parts of the fourth LIGO-Virgo-KAGRA observing run. Directed searches are conducted for long-transient gravitational waves from ultralight vector boson clouds around merger remnants, using a hidden-Markov-model (HMM) tracking scheme. We target the remnant black holes formed in the binary co… ▽ More We present constraints on ultralight bosons using binary black hole mergers observed in the second and third parts of the fourth LIGO-Virgo-KAGRA observing run. Directed searches are conducted for long-transient gravitational waves from ultralight vector boson clouds around merger remnants, using a hidden-Markov-model (HMM) tracking scheme. We target the remnant black holes formed in the binary coalescences that produced GW250114 and GW250207. We find no evidence for such signals from either target. Estimating our search sensitivity at a threshold corresponding to a 1% false alarm probability, we thus disfavor vector boson masses in the range of $[2.80, 3.95]\times 10^{-13}$ eV with greater than 90% confidence. In addition, we derive constraints on ultralight scalar and vector bosons from the inferred high spins of the constituent black holes in three binaries, using events GW240515, GW241113, and GW241225_08. The excluded mass ranges in this approach depend on the assumed black-hole ages. At $10^5$ years, corresponding to typical dynamically formed binaries, we exclude scalar and vector bosons in the ranges $[1.39, 6.94]\times 10^{-13}$ eV and $[0.32, 14.4]\times 10^{-13}$ eV at 90% confidence, respectively. △ Less

Submitted 11 August, 2026; originally announced August 2026.

Comments: 27 pages (12 pages author list, 15 pages main paper), 5 figures

Report number: LIGO-P2600218

Robust Multi-Tier Infant-Centered Audio Understanding with Whisper via Structured Speaker Conditioning

Authors: Xulin Fan, Jialu Li, Mohammad Nur Hossain Khan, Kexin Hu, Bashima Islam, Mark Hasegawa-Johnson, Nancy L. McElwain

Abstract: Recent advances in model design and self-supervised audio representations have improved speech and audio understanding, yet infant-centered naturalistic recordings remain challenging due to limited labeled data, low signal-to-noise ratio, and cross-family domain shifts. We present a family-conditioned, multi-tier audio tagger that combines a LoRA-finetuned Whisper encoder with a lightweight, targe… ▽ More Recent advances in model design and self-supervised audio representations have improved speech and audio understanding, yet infant-centered naturalistic recordings remain challenging due to limited labeled data, low signal-to-noise ratio, and cross-family domain shifts. We present a family-conditioned, multi-tier audio tagger that combines a LoRA-finetuned Whisper encoder with a lightweight, target-speaker-aware Transformer for long-context inference and framewise prediction across tiers. To improve temporal coherence, we incorporate a simple sequence-level smoothing loss, and to enhance robustness across households, we introduce a factorized speaker-token design with a shared tier token and a learned family-specific offset, reducing family bias and promoting generalizable representations. Together, these choices enable efficient and effective infant-centered audio tagging of daylong audio recordings in home environments. △ Less

Submitted 11 August, 2026; originally announced August 2026.

Comments: Accepted to Interspeech 2026

Compact Actively-Shielded Magnetic Field Coil within Mu-Metal Shields for ACME Electric Dipole Moment Measurements

Authors: S. Liu, M. Watts, C. Diver, D. G. Ang, C. Meisenhelder, X. Fan, B. Hao, D. Lascar, A. Hiramoto, T. Masuda, P. Hu, Z. Han, X. Wu, D. DeMille, J. M. Doyle, G. Gabrielse

Abstract: A system of actively-shielded coils and mu-metal shields is devised, constructed and shown to provide the stable and spatially uniform magnetic field needed for the ACME III electron electric dipole moment (eEDM) measurement. Two layers of current-carrying coils, enclosed within three layers of ferromagnetic shields, produce a field that varies by less than 1 nT (10 $\uG$) within the 1 m $\times$… ▽ More A system of actively-shielded coils and mu-metal shields is devised, constructed and shown to provide the stable and spatially uniform magnetic field needed for the ACME III electron electric dipole moment (eEDM) measurement. Two layers of current-carrying coils, enclosed within three layers of ferromagnetic shields, produce a field that varies by less than 1 nT (10 $\uG$) within the 1 m $\times$ 4.2 cm $\times$ 4.2 cm interior volume in which a beam of ThO molecules are probed as they precess. The demountable shields are constructed from rectangular mu-metal plates. The largest, with a mass of 19 kg and an area of 2.18 m $\times$ 0.75 m, is easily carried by two people and just fits within a large available annealing oven. The assembly design facilitates low-stress mounting and handling to suppress changes in the magnetic properties of the mu metal, and also provides modular access to apparatus within the coils for maintenance and upgrades. The nearly static external ambient field is reduced within the shielded precession volume by up to a factor of $10^5$. During the magnetic field reversals that ACME uses to suppress systematic uncertainties, the ``actively-shielded'' coil largely cancels out its external fringing field to minimize the magnetization of the mu metal. Even though the shields are only 10 cm outside the coils, shield degaussing after every magnetic field reversal is not required. The non-reversing residual field stays below 1 nT for up to 17 hours when the field is reversed every 30 seconds, for example. The measured performance, compared to the previous generation ACME II apparatus, suggests that the magnetic-field-related systematic uncertainties for ACME III will be smaller by an estimated factor of 40 despite a five times longer precession volume and the use of three magnetic shielding layers rather than five. △ Less

Submitted 11 August, 2026; originally announced August 2026.

Comments: 24 pages, 28 figures

ConnectionMind: Leveraging Social Networks and Large Language Models for Personalized Recommendation at Meta

Authors: Haoyu Han, Yuming Liu, Lei Huang, Lizhu Zhang, Jiliang Tang, Xiangjun Fan

Abstract: Modern recommendation systems on social media platforms such as Meta must model complex social relationships, including friendships, group memberships, and creator interactions, alongside massive and heterogeneous content such as text and video. Traditional recommendation models, however, often omit these signals or treat them independently, lacking the reasoning capability to integrate multi-rela… ▽ More Modern recommendation systems on social media platforms such as Meta must model complex social relationships, including friendships, group memberships, and creator interactions, alongside massive and heterogeneous content such as text and video. Traditional recommendation models, however, often omit these signals or treat them independently, lacking the reasoning capability to integrate multi-relational context for fine-grained personalization. We present ConnectionMind, a production-ready recommendation framework that tightly integrates the social network structure with large language models (LLMs) to enable scalable, interpretable, and reasoning-aware personalization in Meta. ConnectionMind constructs a heterogeneous graph connecting users, items, friends, groups, and creator pages, and formulates recommendation as a graph reasoning problem: discovering personalized paths from users to candidate items. An LLM-based policy is employed to reason over these graph structures and guide recommendation decisions. To train the system at scale, ConnectionMind adopts a two-stage learning strategy. We first perform supervised fine-tuning (SFT) on large-scale user-item interaction trajectories to initialize the reasoning policy, followed by end-to-end reinforcement learning (RL) to refine the model's ability to reason over social graphs for personalized recommendation. Extensive experiments on multiple real-world datasets demonstrate the effectiveness of ConnectionMind compared to representative baselines. More importantly, ConnectionMind has been deployed in Meta's large-scale recommendation pipeline and has been evaluated through online A/B tests, achieving a 0.43% improvement in video watch time. These results demonstrate measurable real-world impact in a production recommendation system. △ Less

Submitted 10 August, 2026; originally announced August 2026.

Crossing tournaments are polynomially $\vecχ$-bounded

Authors: Lila Crew, Xinyue Fan, Hidde Koerts, Benjamin Moore, Sophie Spirkl

Abstract: Given a tournament $T$, Aboulker, Aubian, Charbit, and Lopes (2023) defined its clique number $\vecω(T)$ as the minimum clique number of a backedge graph of $T$, and raised the question: Which classes of tournaments are polynomially $\vecχ$-bounded? Aboulker, Duron, Jacob, Kimbrough, Thomassé, and this work's authors (2026) showed that this holds for classes of tournaments whose arc sets may be wr… ▽ More Given a tournament $T$, Aboulker, Aubian, Charbit, and Lopes (2023) defined its clique number $\vecω(T)$ as the minimum clique number of a backedge graph of $T$, and raised the question: Which classes of tournaments are polynomially $\vecχ$-bounded? Aboulker, Duron, Jacob, Kimbrough, Thomassé, and this work's authors (2026) showed that this holds for classes of tournaments whose arc sets may be written as the union of a bounded number of comparability digraphs. What about classes of tournaments that do not admit such a decomposition? The crossing tournaments of Nguyen, Scott, and Seymour (2025) are an example of such a class, as shown in the aforementioned 2026 work; we show that nonetheless crossing tournaments are polynomially $\vecχ$-bounded by adapting a method of Davies and McCarty (2021) and Davies (2022). We additionally show that we cannot extend this result for crossing tournaments to tournaments with chordal graphs as backedge graphs. △ Less

Submitted 10 August, 2026; originally announced August 2026.

Beyond the Capability Boundary: Zeroth-Order Optimization for Self-Evolving LLM Agents

Authors: Bingzhen Liu, Xiaomeng Fan, Yuwei Wu, Zhi Gao, Mingyang Gao, Chuanhao Li, Yunde Jia

Abstract: Self-evolving methods improve the capabilities of LLM agents by sampling trajectories from the underlying LLMs and learning from these trajectories. However, these methods struggle to learn beyond the inherent capability boundary of the agents, since the agents cannot sample correct trajectories on difficult examples for further improvements. In this paper, we propose a zeroth-order self-evolution… ▽ More Self-evolving methods improve the capabilities of LLM agents by sampling trajectories from the underlying LLMs and learning from these trajectories. However, these methods struggle to learn beyond the inherent capability boundary of the agents, since the agents cannot sample correct trajectories on difficult examples for further improvements. In this paper, we propose a zeroth-order self-evolution framework that enables agents to learn beyond their capability boundary by perturbing LLM parameters to adapt to difficult examples without any trajectory annotations. Specifically, we perturb LoRA parameters of LLMs, run the agent, compute the losses under the perturbed and original parameters, and use the loss difference to estimate gradients and further update the LoRA parameters. We sample trajectories using the updated LLMs for supervised fine-tuning to break through the capability boundary of the agents, forming a closed self-evolution loop. We introduce a parallel perturbation inference mechanism and an adaptive lookup mechanism to reduce time consumption in zeroth-order optimization, with an answer perplexity loss that provides smooth and stable zeroth-order loss values. Experiments on multiple deep research benchmarks show that our method obtains substantially more successful trajectories and consistently outperforms strong baselines, especially on difficult examples. The code and released artifacts are available at https://github.com/hidk1911/ZOForLLMAgents. △ Less

Submitted 10 August, 2026; originally announced August 2026.

Time-Reversal-Invariant Altermagnetic Acoustic Crystals

Authors: Tianzhi Xia, Han-Rong Xia, Jinglin Liu, Xiying Fan, Zebin Zhu, Zhen Gao

Abstract: Altermagnets have emerged as a new class of magnetic materials that combine spin-split electronic bands with zero net magnetization. Extending this paradigm to classical-wave systems has, however, been fundamentally challenging because conventional realizations require broken time-reversal symmetry (TRS). Here, we overcome this limitation by introducing two pseudospin degrees of freedom and constr… ▽ More Altermagnets have emerged as a new class of magnetic materials that combine spin-split electronic bands with zero net magnetization. Extending this paradigm to classical-wave systems has, however, been fundamentally challenging because conventional realizations require broken time-reversal symmetry (TRS). Here, we overcome this limitation by introducing two pseudospin degrees of freedom and constructing a pseudo-time-reversal operator that faithfully reproduces the action of its physical counterpart while preserving actual TRS. Building on this framework, we theoretically propose and experimentally realize the first time-reversal-invariant altermagnetic acoustic crystal. Acoustic measurements directly reveal pseudospin-dependent band splitting--a defining hallmark of altermagnetism--under strictly TRS-preserving conditions. Moreover, the altermagnetic acoustic crystal exhibits sublattice-pseudospin locking, enabling flexible control over acoustic pseudospin splitting and filtering. Our work establishes acoustic crystals as a versatile platform for exploring altermagnetic physics and opens new avenues for spin-inspired wave manipulation in nonmagnetic devices. △ Less

Submitted 9 August, 2026; originally announced August 2026.

Comments: 12pages, 4 figures

Beyond Reconstruction: Full-Context Generative DiT for Music Generation

Authors: Yunjia Li, Menglin Wu, Junyu Dai, Xinyue Fan, Xiangang Li, Haoxu Wang, Jianwei Yu, Huaicheng Zhang, Han Zhao, Weiqin Li, Yufei Shi, Cheng Wen, Sitong Zhao, Qixi Zheng, Haina Zhu, Wei Li

Abstract: Hybrid music generators combine the long-range planning of an autoregressive language model with the fidelity of a diffusion- or flow-based acoustic renderer. Yet renderers are trained with clean, target-derived codec tokens but deployed with imperfect language-model predictions, creating codecinterface exposure bias. Rather than treating rendering as a simple reconstruction task,we formulate it a… ▽ More Hybrid music generators combine the long-range planning of an autoregressive language model with the fidelity of a diffusion- or flow-based acoustic renderer. Yet renderers are trained with clean, target-derived codec tokens but deployed with imperfect language-model predictions, creating codecinterface exposure bias. Rather than treating rendering as a simple reconstruction task,we formulate it as full-context generation from an imperfect discrete plan. We introduce FullDiT, a conditional DiT that fuses eight frame-aligned RVQ streams with independently encoded captions and lyrics and uses non-causal self-attention over the complete acoustic latent sequence. During training, Error-Matched Distractor Conditioning (EMDC) matches per-codebook replacement rates to teacher-forced top-1 error rates and samples near-miss tokens from cosine-KNN neighborhoods without changing the acoustic target. At inference, four-way classifier-free guidance (4-CFG) independently scales codec, lyric, and caption guidance increments. Matched ablations show that EMDC improves ViSQOL by 0.77 under synthetic corruption and is clearly preferred in non-tied comparisons with fixed languagemodel tokens. Further ablations show gains from full-song context and renderer-side text conditioning. The complete system outperforms five commercial systems on 15 of 18 automatic metrics and ranks among the top three on the Artificial Analysis Music with Vocals Leaderboard. The demo page is available at https://selinacloudl.github.io/fulldit-demo/. △ Less

Submitted 10 August, 2026; v1 submitted 9 August, 2026; originally announced August 2026.

Learning from Consensus and Disagreement: Unsupervised On-Policy Self-Distillation with Minority-Trajectory Contrast

Authors: Jiaxin Guo, Yanwei Yue, Xuanbo Fan, Chunyu Yang, Yan Zhang

Abstract: On-policy self-distillation improves language-model reasoning by querying a teacher on states actually visited by the student. Recent methods create a powerful information asymmetry by exposing the teacher to privileged context, yet they fundamentally rely on external supervision---such as gold solutions or verifiers---to construct this advantage. We introduce CoDA (Consensus and Disagreement Alig… ▽ More On-policy self-distillation improves language-model reasoning by querying a teacher on states actually visited by the student. Recent methods create a powerful information asymmetry by exposing the teacher to privileged context, yet they fundamentally rely on external supervision---such as gold solutions or verifiers---to construct this advantage. We introduce CoDA (Consensus and Disagreement Alignment), a fully unsupervised framework that creates reliable privileged information entirely from the latent uncertainty structure of a model's own unlabeled rollouts. CoDA extracts two complementary signals. In the positive branch, answer-level consensus identifies a stable reasoning mode, which conditions a frozen self-teacher to provide dense distributional guidance on fresh student trajectories. However, because agreement does not guarantee correctness, positive-only distillation risks amplifying correlated errors into a false consensus. To break this harmful feedback loop, CoDA incorporates a negative branch that exploits disagreement: minority trajectories are treated as unstable alternatives and gently penalized via a reference-anchored, KTO-style calibration objective. This unpaired binary feedback provides robust regularization without requiring the strong assumption that the consensus is the absolute ground truth. Empirical evaluations on competition-level mathematical benchmarks demonstrate that CoDA significantly improves reasoning, outperforming self-generated baselines and effectively stabilizing training against erroneous consensus. △ Less

Submitted 9 August, 2026; originally announced August 2026.

EnergyBridge: Benchmarking Household Energy Management, User Participation, and Grid Flexibility

Authors: Xudong Wu, Zeqing Wu, Jiarui Zhang, Xuhao Fan, Ziang Ding, Yuming Zhuang, Mingqi Yuan, Yilun Du, Hongjie Jia, Yunfei Mu, Jiayu Chen

Abstract: Residential virtual power plants (VPPs) can provide grid flexibility by shifting household demand, but physical flexibility becomes dependable capacity only when residents authorize a plan and the promised response is delivered. Existing benchmarks evaluate control but omit event-specific authorization. We present EnergyBridge, a benchmark and agent framework connecting capacity reporting, househo… ▽ More Residential virtual power plants (VPPs) can provide grid flexibility by shifting household demand, but physical flexibility becomes dependable capacity only when residents authorize a plan and the promised response is delivered. Existing benchmarks evaluate control but omit event-specific authorization. We present EnergyBridge, a benchmark and agent framework connecting capacity reporting, household authorization, and physical execution. It combines region-specific EnergyPlus environments for Tianjin and Berlin with an LLM-based User Participation Simulator. Against 584 persona- and event-matched human role-play judgments, the LLM-based User Participation Simulator preserves method ordering with a 5.3-point mean absolute acceptance error. Across conventional controllers and agent baselines, EnergyBridge achieves the highest simulated authorization, lowest event-window energy, and the most reliable capacity commitment in both regions. We release human data and codes for reproducible human-centered grid-flexibility research: https://github.com/Agentic-Intelligence-Lab/EnergyBridge. △ Less

Submitted 9 August, 2026; originally announced August 2026.

Cloud-Boosted Low-Compute Multi-Channel Speech Enhancement

Authors: Xulin Fan, Juan Azcarreta, Ashutosh Pandey, Jesus Alvarez, Ke Tan, Jacob Donley, Ritwik Giri, Buye Xu

Abstract: Low-latency, low-compute speech enhancement is essential for wearable devices with real-time communication requirements, but strict computational constraints significantly limit on-device performance. Knowledge Boosting has been proposed as an effective approach to improve edge model performance by leveraging a more capable server-side model, but performance gains for speech enhancement have been… ▽ More Low-latency, low-compute speech enhancement is essential for wearable devices with real-time communication requirements, but strict computational constraints significantly limit on-device performance. Knowledge Boosting has been proposed as an effective approach to improve edge model performance by leveraging a more capable server-side model, but performance gains for speech enhancement have been limited. We propose a collaborative framework incorporating three techniques: (1) delayed server output as additional input, (2) layerwise feature boosting that transfers intermediate server representations to guide edge inference, and (3) collaborative multichannel Wiener filtering, which fuses weighted covariance matrices estimated from both server and edge models for improved beamforming. Experimental results demonstrate that the proposed collaborative framework significantly outperforms the edge-only baseline with minimal additional computational overhead. △ Less

Submitted 7 August, 2026; originally announced August 2026.

Comments: Accepted to Interspeech 2026

When History Lies: Evaluating and Improving Tool Use under Misleading Multi-Turn Histories

Authors: Xiaoqing Wu, Xingyu Fan, Feifei Li, Wenhui Que

Abstract: Tool-calling agents infer task state from accumulated dialogue and tool traces. In persistent interactions, however, historical traces may remain structurally valid and semantically plausible after they cease to be authoritative for the current request. We show that such history can hijack a policy the model already possesses: on Qwen3-1.7B, pollution flips 32.1% of decisions that are correct unde… ▽ More Tool-calling agents infer task state from accumulated dialogue and tool traces. In persistent interactions, however, historical traces may remain structurally valid and semantically plausible after they cease to be authoritative for the current request. We show that such history can hijack a policy the model already possesses: on Qwen3-1.7B, pollution flips 32.1% of decisions that are correct under the original trajectory and frequently induces reuse of corrupted entities or interface conventions. We introduce bench, a paired benchmark with synchronized Original, Polluted, and Oracle State views that preserve the system policy, current tools, latest request, and gold next action. Eleven gold-preserving interventions isolate failures in decision state, entity binding, and interface execution across complete calls and non-call decisions. We further propose ours, which transfers an Oracle-conditioned teacher policy to a student observing only polluted history through soft supervision on student-generated prefixes. On Qwen3-1.7B, ours achieves 87.0% Balanced Tool-Use Accuracy, outperforming Gold-SFT (66.3%), Oracle sequence distillation (82.3%), and off-policy token distillation (85.0%). The method scales consistently: an 8B teacher raises the same compact 1.7B student to 91.9%, while an 8B student reaches 93.0%. The resulting policies further transfer to clean histories, unseen functions, independently regenerated evaluation contexts, external tool-use benchmarks, and noisy multi-hop question answering. These results establish history reliability as a distinct tool-use bottleneck and demonstrate reliable-state policy transfer as an effective and scalable solution. △ Less

Submitted 6 August, 2026; originally announced August 2026.

A Session Interaction Framework for The Multiple-Unicast Conjecture

Authors: Sirui Liu, Zongpeng Li, Xiying Fan, Haifeng Chen

Abstract: The multiple-unicast conjecture asserts that network coding offers no throughput advantage over routing in undirected networks. Its validity is known to imply fundamental lower bounds in computational complexity. We propose a Session Interaction Framework that reduces the conjecture to a central equivalence: the conjecture holds universally if and only if every irreducible core is independent. Thi… ▽ More The multiple-unicast conjecture asserts that network coding offers no throughput advantage over routing in undirected networks. Its validity is known to imply fundamental lower bounds in computational complexity. We propose a Session Interaction Framework that reduces the conjecture to a central equivalence: the conjecture holds universally if and only if every irreducible core is independent. This result transforms the global feasibility problem into a two-stage process. First, to make the reduction phase tractable, we provide simplified sufficient conditions for session dominance, offering geometric criteria to iteratively simplify complex session sets. Second, for the remaining "irreducible core," we propose a Session Decoupling Theorem, reducing the conjecture's validity for a session set to its independent subsets. Topologically, we prove that sessions separated by high-cost cuts or cut-vertices are guaranteed to be independent. By integrating these reduction and decomposition mechanisms, our framework offers a systematic methodology to verify the conjecture across general network topologies. △ Less

Submitted 6 August, 2026; originally announced August 2026.

Comments: Presented at the 2026 IEEE International Symposium on Information Theory (ISIT 2026)

EvoHarness-RL: Learning Self-Evolving Runtime Harness for Long-Horizon LLM Agents

Authors: Xuying Ning, Dongqi Fu, Tianxin Wei, Hanqing Zeng, Yuanchen Bei, Bingxuan Li, Zihao Li, Qifan Wang, Xiang Shen, Yifan Wu, Jiayi Liu, Hong Li, Yinglong Xia, Xiangjun Fan, Hanghang Tong, Jingrui He

Abstract: Long-horizon LLM agents increasingly rely on external execution support to maintain state, track progress, invoke tools, verify outcomes, and reuse experience across interactions. However, effective harness use raises two coupled challenges: state formation from noisy interaction traces and runtime control over external-state access. Existing agents usually handle both through prompts, heuristics,… ▽ More Long-horizon LLM agents increasingly rely on external execution support to maintain state, track progress, invoke tools, verify outcomes, and reuse experience across interactions. However, effective harness use raises two coupled challenges: state formation from noisy interaction traces and runtime control over external-state access. Existing agents usually handle both through prompts, heuristics, or domain-specific conventions, leaving the external workspace and its usage policy manually engineered. To address this, we study the problem of harness policy learning, where agents learn harness policies offline and deploy them to construct and update external harness state online during runtime task execution. We introduce EvoHarness-RL, which exposes Belief, Progress, and Experience (BPE) as policy-facing harness state. Supervised harness fine-tuning teaches the base agent the harness action space and how to construct useful external state, while cost-aware GRPO explores coordination policies to selectively read, update, and consolidate that state during long-horizon interaction. Instantiated on ALFWorld with a Qwen3-8B LLM, EvoHarness-RL reaches 96.9% success and reveals two key dynamics: harness annealing, where training internalizes recurring harness-use patterns into the model policy and shifts the agent from frequent harness calls toward selective external-state access, and harness evolution, where progress updates and experience consolidation refine the harness into a compact, task-adaptive state substrate. These results suggest that long-horizon agents benefit from trainable policies for constructing and coordinating with external harness workspaces, beyond simply adding stronger tools or larger memories. △ Less

Submitted 5 August, 2026; originally announced August 2026.

Comments: Accepted to LLA@COLM 2026

Frequency-Decorrelated Temporal Ensembles for EEG--fNIRS Imagined-Handwriting Decoding

Authors: Xiao Fan, Hongbin Guo, Yubo Han, Yi Zhang

Abstract: Imagined handwriting offers a temporally rich paradigm for non-invasive neural decoding, yet reliable recognition across unseen participants remains difficult because scalp EEG is noisy and internally generated stroke sequences vary across individuals. The Multimodal Brain-Computer Interface Grand Challenge provides synchronized EEG and fNIRS for four-class subject-independent handwriting-trajecto… ▽ More Imagined handwriting offers a temporally rich paradigm for non-invasive neural decoding, yet reliable recognition across unseen participants remains difficult because scalp EEG is noisy and internally generated stroke sequences vary across individuals. The Multimodal Brain-Computer Interface Grand Challenge provides synchronized EEG and fNIRS for four-class subject-independent handwriting-trajectory classification. We propose FRED, a task-adapted system that models imagined handwriting as a multi-second motor sequence and trains a compact multi-scale temporal network on three complementary EEG frequency views. With three seeds per view, cross-band members produce substantially less-correlated errors than same-band replicas, yielding a clean nine-member ensemble accuracy of 0.8076/0.7242/0.7492 on the public/private/overall test partitions without test-set adaptation or output constraints. The submitted pipeline further incorporates transductive pseudo-label training, three EEG-Conformer members, posterior aggregation, and a paradigm-aware decoder. Because every 12-trial randomization block contains three instances of each class, the final predictions are obtained by Hungarian assignment under the known block quota. On one fixed posterior pool, independent, session-constrained, and block-constrained decoding achieve 0.7600, 0.7758, and 0.7952 overall accuracy, respectively. The complete system reaches 0.8498/0.7718/0.7952, ranking fourth on the private split. A modality audit finds fNIRS-only decoding at chance (0.2511 overall), while adding fNIRS to EEG changes accuracy by only +0.0025. These results identify frequency-diverse temporal EEG modeling and protocol-matched structured inference as the principal sources of performance in this sparse-montage EEG--fNIRS setting. The source code is available at https://github.com/XiuFan719/EEG-fNIRS-fuse-method-for-MM-challenge. △ Less

Submitted 4 August, 2026; originally announced August 2026.

CLEAR: Conflict-aware Learning via Evidence-guided Adaptive Routing for Unified Sparse-View 3D Gaussian Super-Resolution

Authors: Hantang Li, Qiang Zhu, Xiandong Meng, Debin Zhao, Xiaopeng Fan

Abstract: Sparse-view 3D Gaussian Splatting Super-resolution is highly challenging since the sparse and low-resolution (LR) inputs lack sufficient geometric and high-frequency information for accurate reconstruction. To achieve high-quality reconstruction, existing sparse-view super-resolution methods adhere to two-stage pipeline that performs LR Gaussian reconstruction and then high-resolution (HR) Gaussia… ▽ More Sparse-view 3D Gaussian Splatting Super-resolution is highly challenging since the sparse and low-resolution (LR) inputs lack sufficient geometric and high-frequency information for accurate reconstruction. To achieve high-quality reconstruction, existing sparse-view super-resolution methods adhere to two-stage pipeline that performs LR Gaussian reconstruction and then high-resolution (HR) Gaussian refinement, which directly results in stage-wise Gaussian transfer and reconstruction error accumulation. To this end, we propose CLEAR, a Conflict-aware Learning via Evidence-guided Adaptive Routing, as the first unified single-stage framework for Sparse-view 3D Gaussian Splatting Super-resolution. Specifically, CLEAR performs joint the optimization of authentic LR observations and external HR priors within a unified Gaussian representation. To mitigate the gradient conflicts introduced by sparse supervision during training, we propose a Gaussian-wise conflict-aware optimization strategy that regards the LR gradient as a reliable anchor and applies evidence-conditioned soft correction only to severe HR conflicts. Moreover, to recover high-frequency details, we introduce an evidence-guided Patch-to-Gaussian routing mechanism which estimates patch reliability and detail demand, lifts them into Gaussian space, and selectively routes high-frequency gradients and densification. Finally, we employ shared Gaussian dropout and a detached mid-training anchoring to enhance the robustness of training framework. Extensive experiments on both synthetic and real-world $4\times$ super-resolution benchmarks demonstrate that CLEAR consistently achieves state-of-the-art rendering quality and superior geometric fidelity. △ Less

Submitted 3 August, 2026; originally announced August 2026.

Comments: 9 pages, 5 figures

GIFT: Geometry-Invariant Fine-Tuning for Non-Lambertian Monocular Depth Estimation

Authors: Xianghui Fan, Zhaoyu Chen, Bingqian Wu, Dayu Li, Xin Zeng, Huanran Cui, Guangzhen Xu, Xiangru Huang, Hang Yang

Abstract: Monocular depth foundation models, benefiting from large-scale synthetic training data, have demonstrated strong generalization. However, they often hallucinate depth on non-Lambertian surfaces, estimating reflected content in mirrors or transmitted content behind glass rather than the physical surface itself. Adapting these models with real-world data is challenging because conventional depth sen… ▽ More Monocular depth foundation models, benefiting from large-scale synthetic training data, have demonstrated strong generalization. However, they often hallucinate depth on non-Lambertian surfaces, estimating reflected content in mirrors or transmitted content behind glass rather than the physical surface itself. Adapting these models with real-world data is challenging because conventional depth sensors are also unreliable in such regions. We observe that while the appearance of a non-Lambertian surface varies with its reflected or transmitted environment, its underlying geometry remains unchanged. Based on this observation, we propose GIFT (Geometry-Invariant Fine-Tuning), a parameter-efficient post-training framework that requires no measured depth labels. We collect groups of RGB images under controlled appearance changes while keeping the camera and target geometry fixed. GIFT exploits geometric invariance across these observations to suppress non-Lambertian depth hallucinations while retaining general depth estimation capability. We further construct a controlled benchmark that evaluates non-Lambertian depth recovery, robustness to appearance changes, and performance retention in other regions. Experiments on our benchmark and an independent real-world dataset demonstrate that GIFT improves depth prediction for mirrors and transparent objects while largely preserving the base model's performance, providing a practical and low-cost approach for adapting monocular depth foundation models to non-Lambertian scenes. △ Less

Submitted 3 August, 2026; originally announced August 2026.

Teleopit: A Full-Embodiment Humanoid Teleoperation System

Authors: Bingqian Wu, Zicheng Xu, Xianghui Fan, Dayu Li, Xiangru Huang

Abstract: Humanoid teleoperation for demonstration collection requires coordinated whole-body motion, continuous dexterous hand control, and viewpoint control. Existing systems either simplify hand commands or depend on dedicated wearable sensors for fine-grained hand motion. We introduce Teleopit, a full-embodiment teleoperation system that maps body, hand, and head signals from VR to a humanoid body, conf… ▽ More Humanoid teleoperation for demonstration collection requires coordinated whole-body motion, continuous dexterous hand control, and viewpoint control. Existing systems either simplify hand commands or depend on dedicated wearable sensors for fine-grained hand motion. We introduce Teleopit, a full-embodiment teleoperation system that maps body, hand, and head signals from VR to a humanoid body, configurable dexterous hands, and a 2-DoF active vision module. A history encoder and failure-aware rewind sampling improve the motion tracker on both motion-capture and live VR references. An optimization-based hand retargeter combines normalized finger directions, fingertip closure, and thumb-frame alignment to map human hand motion to different dexterous hands without tuning hand-specific objective or solver hyperparameters. Component experiments evaluate tracking success rate and retargeting behavior, while real-robot teleoperation demonstrates coordinated locomotion, manipulation, and viewpoint control. ACT and GR00T N1.7 policies trained on 96 successful demonstrations collected with Teleopit achieve task success rates of 90.0% and 95.0%, respectively, when deployed on the humanoid. The project page is available at https://botrunner64.github.io/teleopit-page. △ Less

Submitted 3 August, 2026; originally announced August 2026.

Comments: 17 pages, 16 figures. Project page: https://botrunner64.github.io/teleopit-page

DynamicManip: Enabling Dynamic Manipulation from a Single Static Demonstration

Authors: Haoran Liao, Pengyue Wang, Shuoyu Chen, Kehan Cheng, Xuhang Chen, Yuhao Lin, Mu Lin, Zhizhao Liang, Xiaoyi Fan, Chengyi Xing, Dan Niu, Yi-Lin Wei, Wei-Shi Zheng

Abstract: Dynamic manipulation is a critical capability for robots operating in complex and dynamic environments, where robots must interact with objects that are moving or require rapid adjustments. However, learning models for dynamic manipulation tasks face two major challenges: (1) the combinatorial complexity of dynamic scenarios leads to substantial data requirements, and (2) rapid variations in dynam… ▽ More Dynamic manipulation is a critical capability for robots operating in complex and dynamic environments, where robots must interact with objects that are moving or require rapid adjustments. However, learning models for dynamic manipulation tasks face two major challenges: (1) the combinatorial complexity of dynamic scenarios leads to substantial data requirements, and (2) rapid variations in dynamics require real-time and accurate policy execution. In this paper, we propose DynamicManip to address these challenges through an efficient data augmentation pipeline and a low-latency imitation policy. We first propose a static-to-dynamic augmentation pipeline that synthesizes diverse dynamic manipulation demonstrations from a single static demonstration. Second, we introduce a dynamic-aware adaptive policy that adjusts its inference frequency according to task dynamics, enabling responsive and effective dynamic manipulation. Third, we build a dynamic manipulation benchmark, which includes diverse dynamic tasks with an automatic evaluation system for scalable and consistent assessment. Extensive experiments in both simulation and the real world demonstrate that DynamicManip not only provides significant improvements in data efficiency but also achieves better performance in dynamic manipulation tasks, with a mean success rate 18.4 percentage points higher and policy-query latency 32.9% lower. △ Less

Submitted 2 August, 2026; originally announced August 2026.

Comments: Project page: https://liaohr9.github.io/DynamicManip/ Code: https://github.com/liaohr9/DynamicManip

CT-PrepAgent: Bounded Policy and Controlled Execution for Adaptive CT Data Preparation

Authors: Xiaolin Fan, Yue Pei, Yingying Zhang, Haogang Zhu

Abstract: Heterogeneous computed tomography (CT) acquisitions and diverse downstream task requirements limit the transferability of fixed data preparation workflows across data sources and tasks. Existing approaches typically rely on manually designed or dataset-specific rules, making it difficult to accommodate changes in acquisition conditions and analytical objectives without manual intervention. Large l… ▽ More Heterogeneous computed tomography (CT) acquisitions and diverse downstream task requirements limit the transferability of fixed data preparation workflows across data sources and tasks. Existing approaches typically rely on manually designed or dataset-specific rules, making it difficult to accommodate changes in acquisition conditions and analytical objectives without manual intervention. Large language model (LLM)-based agents have shown promise for automating medical workflows, yet their potential for adaptive CT data preparation remains largely unexplored. To bridge this gap, we propose CT-PrepAgent, which enables adaptive CT data preparation through a bounded policy and controlled deterministic execution. Deterministic inspection constructs structured data--task profiles, from which a policy decides an eligible DICOM series or predefined preprocessing profile, while the controlled execution flow guards, resolves, executes, and verifies the decision with bounded recovery when enabled and safe quarantine otherwise. Across three public CT segmentation tasks, CT-PrepAgent derived data-task adaptive preprocessing decisions and achieved the highest macro-average Dice. On two private raw-DICOM cohorts, CT-PrepAgent increased verified output yield from 61.7\% to 70.0\% and yielded similar registration metrics on common verified outputs. Controlled fault and replay tests validate bounded recovery, safe quarantine, and policy-free replay under tested fault and drift settings. △ Less

Submitted 2 August, 2026; originally announced August 2026.

Misaligned or chaotic? A strong break of axial symmetry in the local LRD J1025 revealed with VLT/FORS2 spectropolarimetry

Authors: Francesco D'Eugenio, Gabriele Pezzulli, Roberto Maiolino, Alessandro Marconi, Xihan Ji, Cristina Ramos Almeida, Andrea Ferrara, Piero Madau, Xiaojing Lin, José A. Acosta-Pulido, Fuyan Bian, Matilde Brazzini, Zheng Cai, Stefano Carniani, Xiaohui Fan, Ignas Juodžbalis, Robert G. Pascalau, Jan Scholtz, Charlotte Simmonds, Fengwu Sun, Sandro Tacchella

Abstract: Little Red Dots (LRDs) are compact active galactic nuclei (AGN) with unusual spectral energy distributions and broad Balmer emission, candidate signposts of rapid black-hole growth. We present VLT/FORS2 optical linear spectropolarimetry of the closest known LRD, SDSS J102530.29+140207.3, at z=0.1. In total light, we detect spatially extended narrow-H$α$ emission, probably tracing the host galaxy.… ▽ More Little Red Dots (LRDs) are compact active galactic nuclei (AGN) with unusual spectral energy distributions and broad Balmer emission, candidate signposts of rapid black-hole growth. We present VLT/FORS2 optical linear spectropolarimetry of the closest known LRD, SDSS J102530.29+140207.3, at z=0.1. In total light, we detect spatially extended narrow-H$α$ emission, probably tracing the host galaxy. We measure a nearly grey continuum polarisation $p_{\rm cont}=1.53\pm0.04$(rand.)$\pm$0.20(syst.) per cent, while broad H$α$ is less polarised, $p_{\rm Hα}=0.58-0.84$ per cent. We rule out polarisation by Milky Way dust and dilution by an unpolarised line. The polarised continuum with a depolarised line resembles local Seyfert-1 nuclei and favours a single dominant source over multi-source explanations. After Stokes-continuum subtraction, broad H$α$ shows no blue-to-red swing, but there is a significant (48$\pm$4)$^\circ$ continuum-to-line offset in polarisation angle. This implies a break of axial symmetry inside this object, posing interesting geometrical challenges to all existing LRD models and frameworks. We discuss different possible origins of this symmetry break and possible paths to discriminate between them with future observations. △ Less

Submitted 30 July, 2026; originally announced July 2026.

Comments: 21 pages, 12 figures. Submitted to MNRAS, comments welcome

Qwen-Audio-3.0-Gen-Preview Technical Report

Authors: Junyu Dai, Xiaoyue Duan, Xinyue Fan, Yihan Feng, Jingbei Li, Xiangang Li, Yunjia Li, Lejun Min, Yufei Shi, Xingchen Song, Yiran Wang, Cheng Wen, Menglin Wu, Bajian Xiang, Huaicheng Zhang, Han Zhao, Ruichen Zheng

Abstract: Existing single-domain and multi-task audio systems remain limited in directly organizing heterogeneous audio components, ambience, and multiple roles into long-form temporal scenes. We present Qwen-Audio-3.0-Gen-Preview, a unified non-autoregressive framework that uses a Diffusion Transformer (DiT) and a shared variational autoencoder (VAE) to generate the complete mixed waveform. Prompt enhancem… ▽ More Existing single-domain and multi-task audio systems remain limited in directly organizing heterogeneous audio components, ambience, and multiple roles into long-form temporal scenes. We present Qwen-Audio-3.0-Gen-Preview, a unified non-autoregressive framework that uses a Diffusion Transformer (DiT) and a shared variational autoencoder (VAE) to generate the complete mixed waveform. Prompt enhancement converts free-form requests into structured temporal records that are rendered as textual conditions, while a two-stage data curriculum and semantic conditional views train the proposed model to use these conditions across standalone and mixed-scene audio. A shared continuous VAE compresses 48kHz stereo waveforms into 25Hz latent sequences and incorporates semantic supervision, providing one representation for heterogeneous audio. On the public reference-conditioned benchmark, speaker similarity is the proposed model's clearest strength across all three subsets. Across the multi-speaker and rich-timeline benchmarks, its clearest comparative strengths are cross-turn consistency in both languages and temporal localization, respectively. On AudioCaps, its advantages are concentrated in evaluations using large audio-language models and AudioBox. These results demonstrate the potential of unified generation for temporally structured audio without task-specific branches. △ Less

Submitted 30 July, 2026; v1 submitted 29 July, 2026; originally announced July 2026.

The Twentieth Data Release of the Sloan Digital Sky Survey: First All-Sky BOSS Spectra, eROSITA-SDSS-V Mapper Coordinated Observations, and a Preview of the Local Volume Mapper

Authors: SDSS Collaboration, Mojgan Aghakhanloo, David Aguilar, James Aird, Andrés Almeida, Bella Abigail Sanabria Alonso, Hillary Diane Andales, Scott F. Anderson, Stefan Arseneau, Consuelo González Ávila, Shir Aviram, Catarina Aydar, Carles Badenes, Carolina Andonie, Jorge K. Barrera-Ballesteros, Franz E. Bauer, Chad Bender, Michelle A. Berg, F. Besser, Binod Bhattarai, Christian Moni Bidin, Jonathan C. Bird, Dmitry Bizyaev, Guillermo A. Blanc, Alexandra Bonkoski , et al. (251 additional authors not shown)

Abstract: This paper presents the twentieth data release (DR20) from the Sloan Digital Sky Survey, the third data release of its fifth generation (SDSS-V). SDSS-V is a panoptic spectroscopy survey that is mapping the stars, gas, and galaxies through three scientific programs: the Milky Way Mapper (MWM), the Local Volume Mapper (LVM), and the Black Hole Mapper (BHM). DR20 presents the first optical (BOSS) SD… ▽ More This paper presents the twentieth data release (DR20) from the Sloan Digital Sky Survey, the third data release of its fifth generation (SDSS-V). SDSS-V is a panoptic spectroscopy survey that is mapping the stars, gas, and galaxies through three scientific programs: the Milky Way Mapper (MWM), the Local Volume Mapper (LVM), and the Black Hole Mapper (BHM). DR20 presents the first optical (BOSS) SDSS-V spectra from southern hemisphere for the MWM and BHM surveys; new optical MWM and BHM data from the northern hemisphere are also available, for a total over 3 million spectra of 1.5 million stars and half a million galaxies and quasars, with galactic and extragalactic x-ray targets coordinate with eROSITA DR2. DR20 includes integral field spectroscopy maps from LVM of six targets and 169 tiles, spanning Galactic HII regions, planetary nebulae, and nearby galaxies. Additionally, eighteen value added catalogs are also released with DR20, based on SDSS-V MWM and BHM data, and we present a new LVM visualization tool including an RGB HiPS map as a value added product. △ Less

Submitted 28 July, 2026; originally announced July 2026.

Comments: 81 pages, 13 figures, 8 tables

Tau functions of the constrained matrix KP hierarchy

Authors: Xiaohan Fan, Jipeng Cheng, Jinbiao Wang

Abstract: The constrained matrix KP hierarchy $(L^{k})_{<0}=\sum_{i=1}^{m}Q_{i}\partial^{-1}R_{i}^{\intercal}$ is investigated from the aspects of tau functions. Firstly, the matrix KP hierarchy is viewed as one special reduction of the multi-component KP hierarchy. Then bilinear equations of the constrained matrix KP hierarchy as the multi-component KP hierarchy are given in terms of tau functions. Finally… ▽ More The constrained matrix KP hierarchy $(L^{k})_{<0}=\sum_{i=1}^{m}Q_{i}\partial^{-1}R_{i}^{\intercal}$ is investigated from the aspects of tau functions. Firstly, the matrix KP hierarchy is viewed as one special reduction of the multi-component KP hierarchy. Then bilinear equations of the constrained matrix KP hierarchy as the multi-component KP hierarchy are given in terms of tau functions. Finally based upon these results, the tau functions for the constrained matrix KP hierarchy are constructed by using the multi-component boson-fermion correspondence. Notice that the solutions of the constrained matrix KP hierarchy are derived without using quasi-determinants. △ Less

Submitted 28 July, 2026; originally announced July 2026.

Comments: 22 pages

MSC Class: 35C08; 35Q53; 37K10; 37K40

NEXT: Reasoning-Driven Video Recommendation via a Vision-Language Model

Authors: Yuming Liu, Hongye Yang, Harrison Zhao, Ellie Zhu, Bokai Cao, Lei Huang, Lizhu Zhang, Xiangjun Fan

Abstract: We present NEXT (Next-interest EXploration Transformer), a reasoning-driven video recommendation framework that reasons over the video a user has just watched, infers the viewer's next intent, and retrieves concrete follow-up videos. Explicit continuations such as episodes are linked directly; implicit cases are handled by generating intent queries and searching for matching candidates. This Item-… ▽ More We present NEXT (Next-interest EXploration Transformer), a reasoning-driven video recommendation framework that reasons over the video a user has just watched, infers the viewer's next intent, and retrieves concrete follow-up videos. Explicit continuations such as episodes are linked directly; implicit cases are handled by generating intent queries and searching for matching candidates. This Item-to-Intent-to-Item formulation produces directed recommendations beyond co-engagement correlation or semantic similarity. To make this framework reliable at scale, we train NEXT-8B, a purpose-trained 8B vision-language model with a three-stage recipe: Perception-Enhanced Reinforcement Learning for query-agnostic evidence extraction, Distribution-Aligned Supervised Fine-Tuning over real and synthetic visual QA mixtures, and Group Relative Policy Optimization for last-mile alignment. NEXT-8B achieves the best single-model DocVQA performance, ranking second overall only behind a multi-agent system while surpassing a substantially larger 200B+ scale model, and improves next-intent logic-wise quality by 3.3% over the base model in a task-specific LLM-as-a-judge evaluation. We deploy NEXT as an additional retrieval path in a large-scale social media recommendation system and observe statistically significant production gains, including +0.53% watch time and +0.51% distinct video exposure. Overall, NEXT shows that a carefully trained compact vision-language model can serve as a practical reasoning engine for next-interest exploration at production scale. △ Less

Submitted 27 June, 2026; originally announced July 2026.

Comments: 13 pages, 2 figures, 5 tables

Studying the tensor resonance contributions in $B \to PP\ell^+\ell^-$ and $B \to PV\ell^+\ell^-$ decays

Authors: Ru-Min Wang, Xiu-Ping Fan, Si-Yu Xu, Yi Qiao, Xiao-Dong Cheng, Yuan-Guo Xu

Abstract: We analyze the semileptonic $B \to T\ell^+\ell^-$, $B \to T(\to PP)\ell^+\ell^-$, and $B \to T(\to PV)\ell^+\ell^-$ decays with $\ell=e,μ,τ$ based on flavor SU(3) analysis in the standard model ($T$ denotes the light tensor meson, $P$ denotes the light pseudoscalar meson, and $V$ denotes the light vector meson). The hadronic amplitudes of the $B \to T\ell^+\ell^-$ decays are related by the nonpert… ▽ More We analyze the semileptonic $B \to T\ell^+\ell^-$, $B \to T(\to PP)\ell^+\ell^-$, and $B \to T(\to PV)\ell^+\ell^-$ decays with $\ell=e,μ,τ$ based on flavor SU(3) analysis in the standard model ($T$ denotes the light tensor meson, $P$ denotes the light pseudoscalar meson, and $V$ denotes the light vector meson). The hadronic amplitudes of the $B \to T\ell^+\ell^-$ decays are related by the nonperturbative parameters, and all branching ratios of the $B \to T\ell^+\ell^-$ decays are obtained by the experimental data of the branching ratio of $B^0_s\to f^{\prime}_{2}(1525)μ^+μ^-$ in three cases, and then the branching ratios of the $B \to T(\to PP)\ell^+\ell^-$ and $B \to T(\to PV)\ell^+\ell^-$ decays are predicted by the narrow width approximation and further considering finite width effects of the intermediate resonances. Compared with the narrow width results, the finite width effects slightly reduce the branching fractions for most decays. However, sizeable finite width effects are found in some near threshold modes. For the subthreshold $K_2^*(1430)\to Kη'$ relevant channels, the finite width of the tensor resonance can open a nonzero contribution. Compared with the measured $B \to PP\ell^+\ell^-$ and $B \to PV\ell^+\ell^-$ decays, we find that the branching ratios with the tensor resonance states are small. Therefore, other resonances, for example, the vector mesons, the scalar mesons, the axial-vector mesons or their excited states, might give the dominant contributions to the relevant decays. Our results might be tested in current and future experiments. △ Less

Submitted 27 July, 2026; originally announced July 2026.

Comments: 23 pages,15 tables

Precision Measurement of Decay Dynamics in $D^{0(+)}\to π^{-(0)}\ell^+ν_\ell$

Authors: BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, X. C. Ai, C. S. Akondi, R. Aliberti, A. Amoroso, Q. An, Y. H. An, M. S. Anderson, Y. Bai, O. Bakina, H. R. Bao, X. L. Bao, M. Barbagiovanni, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. B. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone , et al. (752 additional authors not shown)

Abstract: The branching fractions of $D^0\to π^-e^+ν_e$, $D^0\to π^-μ^+ν_μ$, $D^+\to π^0e^+ν_e$, and $D^+\to π^0μ^+ν_μ$ are precisely measured, using 20.3 fb$^{-1}$ of $e^+e^-$ collision data collected at the center-of-mass energy of 3.773 GeV with the BESIII detector. The ratios of the decay widths between muon and positron channels are examined in full, across several four-momentum transfer ranges of… ▽ More The branching fractions of $D^0\to π^-e^+ν_e$, $D^0\to π^-μ^+ν_μ$, $D^+\to π^0e^+ν_e$, and $D^+\to π^0μ^+ν_μ$ are precisely measured, using 20.3 fb$^{-1}$ of $e^+e^-$ collision data collected at the center-of-mass energy of 3.773 GeV with the BESIII detector. The ratios of the decay widths between muon and positron channels are examined in full, across several four-momentum transfer ranges of $\ell^+ν_{\ell}$. No lepton flavor universality violation is found in the current data. From a simultaneous fit to the precisely measured partial decay rates and the first measured forward-backward asymmetries of these four decays, the product of the hadronic transition form factor, $f^{D\toπ}_+(0)$, and the modulus of the $c\to d$ quark mixing element, $|V_{cd}|$, is measured with unprecedented precision to be $f^{D\toπ}_+(0)|V_{cd}|=0.1425\pm0.0005_{\rm stat.}\pm0.0003_{\rm syst.}$. Taking the value of $|V_{cd}|$ from the standard model global fit and $f^{D\toπ}_+(0)$ derived by the lattice quantum chromodynamics calculation as input, we obtain $f^{D\toπ}_+(0)=0.1425\pm0.0005_{\rm stat.}\pm0.0003_{\rm syst.}$ and $|V_{cd}|=0.2262\pm0.0008_{\rm stat.}\pm0.0005_{\rm syst.}\pm0.0018_{\rm LQCD.}$, respectively. The precision of each result is a factor of 2-3 better than the previous best measurements. Additionally, the real and imaginary parts of the scalar current contribution in the $c\to d \ell^+ν_{\ell}$ transition are measured for the first time to be Re $(C_S^μ)=$ $0.022 \pm 0.023_{\rm stat.}\pm 0.003_{\rm syst.}$ and $|\mathrm{Im} (C_S^μ)|=0.000 \pm 0.038_{\rm stat.}\pm 0.012_{\rm syst.}$. △ Less

Submitted 26 July, 2026; originally announced July 2026.

Comments: 11 pages, 3 figures

Precision measurements of semleptonic decays $D^0 \to π^-\ell^+ν_\ell$ and $D^+ \to π^0\ell^+ν_\ell$ ($\ell =e,μ$)

Authors: BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, X. C. Ai, C. S. Akondi, R. Aliberti, A. Amoroso, Q. An, Y. H. An, M. S. Anderson, Y. Bai, O. Bakina, H. R. Bao, X. L. Bao, M. Barbagiovanni, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. B. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone , et al. (752 additional authors not shown)

Abstract: The branching fractions of $D^0\to π^-e^+ν_e$, $D^0\to π^-μ^+ν_μ$, $D^+\to π^0e^+ν_e$, and $D^+\to π^0μ^+ν_μ$ are measured to be $(2.950\pm0.017_{\rm stat.}\pm 0.017_{\rm syst.})\times10^{-3}$, $(2.817\pm0.037_{\rm stat.}\pm 0.019_{\rm syst.})\times10^{-3}$, $(3.622\pm0.034_{\rm stat.}\pm 0.018_{\rm syst.})\times10^{-3}$, and $(3.507\pm0.043_{\rm stat.}\pm 0.026_{\rm syst.})\times10^{-3}$ using… ▽ More The branching fractions of $D^0\to π^-e^+ν_e$, $D^0\to π^-μ^+ν_μ$, $D^+\to π^0e^+ν_e$, and $D^+\to π^0μ^+ν_μ$ are measured to be $(2.950\pm0.017_{\rm stat.}\pm 0.017_{\rm syst.})\times10^{-3}$, $(2.817\pm0.037_{\rm stat.}\pm 0.019_{\rm syst.})\times10^{-3}$, $(3.622\pm0.034_{\rm stat.}\pm 0.018_{\rm syst.})\times10^{-3}$, and $(3.507\pm0.043_{\rm stat.}\pm 0.026_{\rm syst.})\times10^{-3}$ using $e^+e^-$ collision data with an integrated luminosity of 20.3 fb$^{-1}$ collected at the center-of-mass energy of 3.773 GeV with the BESIII detector. The partial decay rates of these four decays are measured with the best precision to date and their forward-backward asymmetries are determined for the first time. By performing a simultaneous fit to these results, the product of the hadronic transition form factor $f^{D\toπ}_+(0)$ and the modulus of the $c\to d$ Cabibbo-Kobayashi-Maskawa matrix element $|V_{cd}|$ is given by $f^{D\toπ}_+(0)|V_{cd}|=0.1425\pm0.0005_{\rm stat.}\pm0.0003_{\rm syst.}$. Taking the $|V_{cd}|$ provided by the standard model global fit and the $f^{D\toπ}_+(0)$ calculated from the lattice quantum chromodynamics as input, we obtain $f^{D\toπ}_+(0)=0.6339\pm0.0024_{\rm stat.}\pm0.0014_{\rm syst.}$ and $|V_{cd}|=0.2262\pm0.0008_{\rm stat.}\pm0.0005_{\rm syst.}\pm0.0018_{\rm LQCD.}$, respectively. The reported results have the best precision to date. We also search for the scalar current contribution in the $c\to d \ell^+ν_{\ell}$ transition and determine Re$(C_S^μ)=$ $0.022 \pm 0.023_{\rm stat.}\pm 0.003_{\rm syst.}$ and $|{\rm Im}(C_S^μ)|=0.000 \pm $ $0.038_{\rm stat.} \pm 0.012_{\rm syst.}$. In addition, the lepton flavor universality is tested with the ratios of the decay rates between semimuonic and semielectronic decays in full and several $\ell^+ν_\ell$ four-momentum transfer ranges. △ Less

Submitted 26 July, 2026; originally announced July 2026.

Comments: 34 pages, 17 figures

Neuromorphic Object Detection: An In-Depth Study and Future Directions

Authors: Jianing Li, Dianze Li, Arren Glover, Xiaopeng Fan, Guoqi Li, Chiara Bartolozzi, Ryad B. Benosman, Yonghong Tian

Abstract: Conventional frame-based cameras face significant challenges in detecting objects under high-speed motion blur or in low-light environments. Neuromorphic cameras provide asynchronous visual streams with high temporal resolution and a wide dynamic range, offering a promising solution for object detection under challenging conditions. Despite the development of numerous models and the emergence of v… ▽ More Conventional frame-based cameras face significant challenges in detecting objects under high-speed motion blur or in low-light environments. Neuromorphic cameras provide asynchronous visual streams with high temporal resolution and a wide dynamic range, offering a promising solution for object detection under challenging conditions. Despite the development of numerous models and the emergence of various applications in neuromorphic object detection, there is still a lack of deep understanding and standardized benchmarks to assess progress and address key challenges. In this paper, we provide a comprehensive survey and benchmark of existing neuromorphic object detection algorithms. Specifically, we first present a problem description, review the available datasets, and revisit the evaluation metrics. We then explore existing neuromorphic object detection approaches from various perspectives, including event representation, temporal modeling, multimodal fusion, asynchronous processing, low-latency processing, and energy-efficient computing. Furthermore, we evaluate a wide range of representative neuromorphic object detection models and offer detailed analyses of the comparative results. Finally, we discuss unresolved issues in neuromorphic object detection and propose potential future research directions. We hope this survey and benchmark will be a valuable resource for researchers and provide guidance for future advancements in neuromorphic object detection. △ Less

Submitted 26 July, 2026; originally announced July 2026.

Comments: Accepted by Proceedings of the IEEE

A quasar hatching from a buried red phase at z = 3.7

Authors: Zheng Ma, Yongda Zhu, Zhiyuan Ji, Eiichi Egami, Marcia J. Rieke, Xiaohui Fan, Jianwei Lyu, George H. Rieke, Fengwu Sun, Yang Sun, George D. Becker, Andrew J. Bunker, Francesco D'Eugenio, Xiangyu Jin, Ignas Juodžbalis, Weizhe Liu, Roberto Maiolino, Pierluigi Rinaldi, Feige Wang, Christopher N. A. Willmer, Yunjing Wu, Jinyi Yang, Junyu Zhang, Peixin Zhu

Abstract: We present JADES-GS 209777, previously cataloged as CANDELS J033238.02-274626.2, hereafter "the Hatchling," a red quasar at $z=3.711$. While the source has been reported in earlier deep-field catalogs, our multiwavelength analysis reveals a visible active nucleus still embedded in a dense gas- and dust-rich environment. Red quasar continua are often attributed to dust attenuation, including non-st… ▽ More We present JADES-GS 209777, previously cataloged as CANDELS J033238.02-274626.2, hereafter "the Hatchling," a red quasar at $z=3.711$. While the source has been reported in earlier deep-field catalogs, our multiwavelength analysis reveals a visible active nucleus still embedded in a dense gas- and dust-rich environment. Red quasar continua are often attributed to dust attenuation, including non-standard extinction curves, but the highly comprehensive multiwavelength data for this source provide direct constraints on the material being cleared. Using JWST/NIRSpec, NIRCam, MIRI, HST, MUSE, Chandra, ALMA, and VLA data, we detect broad emission lines and strong X-ray emission, showing that the active nucleus is at least partially exposed. We also detect H$α$ and He I absorption, indicating dense gas close to the nucleus. Kinematically disturbed O I, Mg II, Na D, and [O III] features, together with extended Ly$α$ emission over $\gtrsim 20$ kpc, further show that multiphase gas is being accelerated from the nuclear region into the host-galaxy environment. The ALMA detection reveals strong dust emission, with the inferred infrared luminosity placing the system in the ULIRG regime. The continuum is red and sharply declining toward the rest-frame UV, resembling compact red AGNs, and may reflect extreme dust attenuation, gas reprocessing, possible BAL-like absorption, or a combination of these effects. Regardless of which mechanism dominates the continuum shape, the line diagnostics show that the visible nucleus remains partially obscured by nearby material. The Hatchling therefore represents a unique opportunity to explore a poorly known transition phase in which feedback is likely clearing an enshrouded quasar and allowing it to emerge toward a more unobscured active nucleus. △ Less

Submitted 24 July, 2026; originally announced July 2026.

Comments: 26 pages, 5 main figures, and 10 Extended Data figures. Submitted, comments are welcome

Learning Adaptive Semantic Gaussian Allocation for 3D Occupancy

Authors: Kanglin Ning, Yiran Zhao, Wenrui Li, Houde Quan, Qifan Li, Xingtao Wang, Xiaopeng Fan

Abstract: Semantic 3D Gaussians provide a compact representation for 3D semantic occupancy prediction by rendering semantic primitives into a voxel volume under voxel-wise supervision. Recent methods have improved the modeling ability and efficiency of this representation through more flexible primitive shapes, geometry-guided initialization, and progressive densification. However, these advances mainly det… ▽ More Semantic 3D Gaussians provide a compact representation for 3D semantic occupancy prediction by rendering semantic primitives into a voxel volume under voxel-wise supervision. Recent methods have improved the modeling ability and efficiency of this representation through more flexible primitive shapes, geometry-guided initialization, and progressive densification. However, these advances mainly determine how primitives are represented, initialized, or added, and do not explicitly address how to select the most useful Gaussians when their total number must be limited to control memory and computation. This imbalance creates an allocation bottleneck: redundant Gaussians remain in simple regions, while difficult regions receive insufficient semantic support. We propose the Semantic Gaussian Allocation Transformer (SAGFormer), which uses Gaussian attributes and local geometric-semantic features to score candidates and select a fixed final Gaussian set. Experiments on nuScenes-SurroundOcc and SSCBench-KITTI-360 show that SAGFormer improves occupancy prediction under the evaluated protocols and yields more semantically consistent and better-utilized Gaussian representations. Under similar final counts and raw coverage, it reduces semantic mixing, strengthens class-consistent voxel support, and produces fewer unused Gaussians. The results indicate that explicit capacity allocation is a useful complement to Gaussian refinement for semantic occupancy prediction. △ Less

Submitted 23 July, 2026; originally announced July 2026.

CLUIE: Clustering-Aware Recurrent Propagation with Local Structural Compensation for Underwater Image Enhancement

Authors: Kui Jiang, Zefan Feng, Laibin Chang, Yan Luo, Junjun Jiang, Xiaopeng Fan

Abstract: Underwater image enhancement remains challenging due to wavelength-dependent light absorption, scattering, and backscattering, which jointly cause color distortion, contrast degradation, and detail loss. Since these degradations vary with scene depth and imaging conditions, different regions within the same image often exhibit heterogeneous degradation patterns and thus require region-adaptive res… ▽ More Underwater image enhancement remains challenging due to wavelength-dependent light absorption, scattering, and backscattering, which jointly cause color distortion, contrast degradation, and detail loss. Since these degradations vary with scene depth and imaging conditions, different regions within the same image often exhibit heterogeneous degradation patterns and thus require region-adaptive restoration. Although visual RWKV models offer an efficient linear-complexity solution for long-range dependency modeling, their predefined scanning orders are content-agnostic and therefore fail to adapt recurrent state propagation to spatially non-uniform restoration demands. To address this limitation, we propose a Clustering-aware RWKV framework, termed CRWKV, which reformulates the fixed recurrent propagation path of conventional RWKV into a content-adaptive token trajectory. Specifically, we introduce Clustering-aware Semantic Dynamic Reordering (CSDR), which groups tokens according to semantic feature similarity and derives a dynamic traversal order from inter-cluster contextual relations. This design enables WKV states to be accumulated along semantically correlated regions rather than fixed spatial or spectral orders. Since dynamic reordering may disrupt the local continuity of original spatial neighborhoods, we further propose Dark-response Modulated Local Propagation (DMLP), which extracts local structural responses via depth-wise convolution and adaptively modulates their propagation strength using a neighborhood-aware pseudo-dark response map. In this way, local structural cues are compensated before recurrent aggregation while preserving content-adaptive long-range modeling. Extensive experiments on multiple underwater image enhancement benchmarks demonstrate that CRWKV achieves state-of-the-art quantitative performance and superior visual quality. △ Less

Submitted 23 July, 2026; originally announced July 2026.

Comments: 13 pages, 12 figures, IEEE Transactions on Image Processing journal paper, code available at https://github.com/geekpool/CLUIE. This paper presents CLUIE, a clustering-aware recurrent RWKV framework for spatially heterogeneous underwater image enhancement, with full-reference/no-reference quantitative comparisons, comprehensive ablation studies and feature visualization for CSDR and DMLP modules

Pushing the Frontier of Full-Song Generation: Hierarchical Autoregressive Planning Meets Flow-Matching Rendering

Authors: Junyu Dai, Xinyue Fan, Weiqin Li, Xiangang Li, Yunjia Li, Bin Ma, Yukun Ma, Chongjia Ni, Yufei Shi, Biao Tian, Haoxu Wang, Menglin Wu, Jianwei Yu, Huaicheng Zhang, Han Zhao, Shengkui Zhao, Haina Zhu

Abstract: In this report, we present a unified song generation framework capable of producing high-quality full-length music from lyrics, text descriptions, and musical attributes. The proposed framework supports three tasks: Lyrics-to-Song Generation, which generates complete songs from text descriptions, lyrics, and musical attributes; Instrumental Music Generation, which creates music without vocals; and… ▽ More In this report, we present a unified song generation framework capable of producing high-quality full-length music from lyrics, text descriptions, and musical attributes. The proposed framework supports three tasks: Lyrics-to-Song Generation, which generates complete songs from text descriptions, lyrics, and musical attributes; Instrumental Music Generation, which creates music without vocals; and Cover Song Generation, which reinterprets existing songs with different styles while preserving their melodic content. Architecturally, our system consists of four main components: a semantic-aware tokenizer, hybird-LM, FullDiT, and a two-level melody module. The tokenizer encodes audio into 8-codebook RVQ tokens for efficient discrete music representation. Based on these tokens, hybird-LM performs hierarchical autoregressive audio-token modeling for full-song generation. To improve audio fidelity, FullDiT performs full-song flow matching in a continuous VAE latent space conditioned on codec tokens, lyrics, and text captions. For cover song generation, the melody module extracts and discretizes melody cues from reference audio to guide generation while preserving the original melodic content. Finally, we investigate DPO, GRPO, and OPD as reward-based post-training strategies for hybird-LM and apply flow-based GRPO to FullDiT to improve musicality and rendering quality. Experimental results on a multilingual automatic benchmark, complemented by the Artificial Analysis Music with Vocals leaderboard, show that the proposed framework achieves competitive performance in the evaluated settings. △ Less

Submitted 29 July, 2026; v1 submitted 22 July, 2026; originally announced July 2026.

GWTC-5.0: Tests of General Relativity

Authors: The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac, A. Abe, I. Abouelfettouh, F. Acernese, K. Ackley, A. Adam, S. Adhicary, D. Adhikari, R. X. Adhikari, V. K. Adkins, S. Afroz, A. Agapito, D. Agarwal, M. Agathos, N. Aggarwal, S. Aggarwal, O. D. Aguiar, I. -L. Ahrend, L. Aiello, A. Ain, P. Ajith, T. Akutsu , et al. (1800 additional authors not shown)

Abstract: The signals from the LIGO-Virgo-KAGRA network of gravitational-wave (GW) detectors allow us to perform sensitive tests of general relativity (GR) in the dynamical and strong-field regime of gravity. We present the results of seven tests of GR using the observed binary signals in the fifth GW Transient Catalog (GWTC-5.0), i.e., up to and including the second part of the fourth observing run (O4b).… ▽ More The signals from the LIGO-Virgo-KAGRA network of gravitational-wave (GW) detectors allow us to perform sensitive tests of general relativity (GR) in the dynamical and strong-field regime of gravity. We present the results of seven tests of GR using the observed binary signals in the fifth GW Transient Catalog (GWTC-5.0), i.e., up to and including the second part of the fourth observing run (O4b). We restrict our analysis to the confident signals, henceforth called events, observed by at least two detectors that have estimated false alarm rates $\le 10^{-3} \ \rm{yr}^{-1}$. These include 72 events from O4b and five events from the first part of the fourth observing run that are now analyzed due to their increased significance from updated search results, bringing the total number of events for tests of GR in the cumulative GWTC to 168. After subtracting the best-fit waveforms, we find the residuals are consistent with detector noise for all events considered. We also find no strong evidence for additional polarizations beyond those predicted by GR. We perform tests of GW generation, improving the constraints on deviations from the GR post-Newtonian coefficients by factors of 1.2-2.6. Finally, we find overall consistency of the remnants with GR using both time- and frequency-domain methods. For GW240621_195059, postmerger data are consistent with the dominant quadrupolar ($\ell=|m|=2$) mode of a Kerr black hole and its first overtone, with spurious high-frequency content preventing a spectroscopic constraint of GR. In the frequency-domain ringdown analysis, the GR prediction lies in the tails of the combined results, possibly due to the limited catalog size. However, the combined results indicate improved consistency with GR over GWTC-4.0, owing to the contribution of GW250114 with a network matched-filter signal-to-noise ratio of 76.9. Overall, we find no evidence for physics beyond GR. △ Less

Submitted 21 July, 2026; originally announced July 2026.

Comments: 44 pages and 10 figures

Report number: LIGO-P2500781

HPD-Parsing: Hierarchical Parallel Document Parsing

Authors: Shu Wei, Jingjing Wu, Lingshu Zhang, Qunyi Xie, Hao Zou, Le Xiang, Xu Fan, Yangliu Xu, Manhui Lin, Xiaolong Ma, Cheng Cui, Tengyu Du, YY

Abstract: Efficient teamwork typically combines global coordination with parallel execution, a principle not yet fully reflected in unified Vision-Language Model (VLM)-based document parsers. Existing unified parsers process an entire page jointly but generate its output through a single token-by-token autoregressive trajectory, creating a sequential bottleneck that grows with document length. Such full-pag… ▽ More Efficient teamwork typically combines global coordination with parallel execution, a principle not yet fully reflected in unified Vision-Language Model (VLM)-based document parsers. Existing unified parsers process an entire page jointly but generate its output through a single token-by-token autoregressive trajectory, creating a sequential bottleneck that grows with document length. Such full-page sequential generation overlooks a key property of document parsing: layout must be analyzed globally, whereas block content can be parsed in parallel. Based on this observation, we introduce HPD-Parsing, which replaces full-page autoregressive generation with a Hierarchical Parallel Decoding paradigm. A main layout branch organizes the overall document structure and dynamically assigns block-level content decoding to concurrent branches, while progressive multi-token prediction (P-MTP) further reduces the decoding steps within each branch. Experiments on public benchmarks show that HPD-Parsing achieves 4,752 tokens per second, delivering $2.62\times$ the throughput of the fastest existing document parsing model and $3.06\times$ that of the vanilla autoregressive baseline, while maintaining competitive parsing accuracy. These results establish hierarchical parallel decoding as an effective alternative to full-page autoregressive generation, opening a new direction for efficient unified document parsing. △ Less

Submitted 21 July, 2026; originally announced July 2026.

Quantum sensing of low-frequency electric signal enabled by modulated auxiliary field in Rydberg atoms

Authors: Xiayang Fan, Shenchao Jin, Jiatian Liu, Jialiang Zhang, Qichao Qi, Yuan Sun

Abstract: Rydberg atoms have emerged as a versatile and efficient platform for high-sensitivity quantum sensing of free-space electric fields, with remarkable progress in detecting low-frequency signals. To date, low-frequency Rydberg receivers have relied on a constant bias field, typically realized via intra-cell electrodes or Rydberg plasmas generated by photoelectric effects or inter-atomic interactions… ▽ More Rydberg atoms have emerged as a versatile and efficient platform for high-sensitivity quantum sensing of free-space electric fields, with remarkable progress in detecting low-frequency signals. To date, low-frequency Rydberg receivers have relied on a constant bias field, typically realized via intra-cell electrodes or Rydberg plasmas generated by photoelectric effects or inter-atomic interactions. While these approaches improve sensitivity, they suffer from inherent challenges in calibration, long-term stability, and robustness, hindering practical deployment. Here, we propose, design, and experimentally demonstrate a quantum sensing scheme for low-frequency electric signals using modulated auxiliary fields in Rydberg atoms. Unlike conventional methods that employ external DC electric fields that are often fully shielded by adsorbed atom layers on the cell walls, we introduce an AC-field modulation strategy. The incoming low-frequency signal mixes with the auxiliary field, and together they induce Stark shifts of the Rydberg level. These shifts are mapped onto the probe laser via electromagnetically induced transparency (EIT), in a manner analogous to heterodyne detection. We demonstrate a sensitivity of $7.5 \pm 2.6~\mathrm{μV/(cm\cdot Hz^{1/2})}$ at 5 kHz and a minimal detectable field of $0.26 \pm 0.04~\mathrm{μV/cm}$ with an integration time of 1000 s. Furthermore, we extend this approach to systematically analyze the performance of generalized auxiliary fields containing multiple frequency components. By virtue of modulated auxiliary field and quantum frequency mixing, our results establish a robust and systematic framework for quantum sensing of low-frequency electric fields with Rydberg atoms, offering improved sensitivity, stability, and immunity to environmental drifts. △ Less

Submitted 21 July, 2026; originally announced July 2026.

Comments: 8 pages, 4 figures

Ah-SCDFT:A general approach for superconductivity with an-harmonic corrections

Authors: Xiaozheng Fan, Panshi Jing, Chuanguang Zhang, Junshuai Wang, Chunlan Ma, Shijing Gong, Chuanxi Zhao, Tianxing Wang, Yipeng An

Abstract: First-principles studies of superconductivity often neglect anharmonic effects (AHE), despite their crucial role in achieving quantitative accuracy in many materials. To bridge this gap, we introduce a general computational approach, termed anharmonic superconducting density functional theory (ah-SCDFT) which systematically incorporates anharmonic corrections into standard SCDFT. This approach all… ▽ More First-principles studies of superconductivity often neglect anharmonic effects (AHE), despite their crucial role in achieving quantitative accuracy in many materials. To bridge this gap, we introduce a general computational approach, termed anharmonic superconducting density functional theory (ah-SCDFT) which systematically incorporates anharmonic corrections into standard SCDFT. This approach allows for high-fidelity predictions of superconducting properties with only a modest increase in computational cost for a limited number of superconducting calculation convergence steps. We demonstrate the effectiveness and reliability of ah-SCDFT by applying it to the prototypical superconductor MgB2, accurately reproducing its superconducting behavior under both ambient conditions and applied pressure in excellent agreement with experiment. Our results establish ah-SCDFT as a powerful, efficient, and broadly applicable approach for quantitatively reliable studies of superconductivity and a promising tool for the prediction of new superconducting materials. △ Less

Submitted 20 July, 2026; originally announced July 2026.

Comments: 7 pages, 4 figures

Journal ref: Physical Review B 113, 214521 (2026)

Spatial nonlocality imaging via metasurface

Authors: Jian Li, Zi-Mu Fan, Qing-Yuan Wu, Wen-Kai Yu, Zhe Meng, Xing-Yan Fan, Wen-Hao Wang, Jie Ma, Xia Guo, An-Ning Zhang

Abstract: Bell nonlocality is both a defining signature of entanglement and a key quantum information resource. However, visualizing and certifying nonlocal correlations across a spatially multimode photonic field remains challenging due to the rapidly growing measurement cost of spatially resolved projective tests. To address this issue, we build a spatial nonlocality imaging scheme that directly reveals t… ▽ More Bell nonlocality is both a defining signature of entanglement and a key quantum information resource. However, visualizing and certifying nonlocal correlations across a spatially multimode photonic field remains challenging due to the rapidly growing measurement cost of spatially resolved projective tests. To address this issue, we build a spatial nonlocality imaging scheme that directly reveals the spatial distribution of quantum nonlocality by integrating a metasurface that performs parallel polarization projections with a quantum-adaptive neural network. Spatially resolved Clauser--Horne--Shimony--Holt (CHSH) tests are realized over a 400-pixel biphoton field using an average of only 1.7 detected coincidence pairs per pixel per basis. This approach yields a nonlocality image that maps the two-dimensional spatial distribution of Bell violations across the optical field and reveals the target-state-dependent spatial evolution of Bell violations. It provides a highly resource-efficient route to large-scale Bell certification and opens new possibilities for exploiting spatially multimode entanglement in quantum imaging, quantum networking, and scalable photonic quantum technologies. △ Less

Submitted 20 July, 2026; originally announced July 2026.

Comments: 18 pages, 5 figures, with 21 pages of Supplementary Materials. Comments are welcome; please contact the corresponding authors for inquiries

Differentiable Hybrid Neural-CFD Modelling of Wall-Bounded Turbulence: Coupled Learning of Subgrid-Scale and Wall Closures

Authors: Xiantao Fan, Yi Liu, Meng Wang, Jian-Xun Wang

Abstract: Wall-modelled large-eddy simulation (WMLES) treats the subgrid-scale (SGS) closure, wall closure and numerical discretization as independent components, although their effects are coupled through the same resolved field. We present a differentiable hybrid neural--CFD framework in which the SGS and wall closures are learned jointly, end-to-end, within a differentiable flow solver, using only low-or… ▽ More Wall-modelled large-eddy simulation (WMLES) treats the subgrid-scale (SGS) closure, wall closure and numerical discretization as independent components, although their effects are coupled through the same resolved field. We present a differentiable hybrid neural--CFD framework in which the SGS and wall closures are learned jointly, end-to-end, within a differentiable flow solver, using only low-order statistics as training targets. Each closure is a composed neural operator: a trainable neural network followed by a fixed differentiable layer that preserves the structure of its conventional counterpart, so that the network learns only the functions left undetermined by the conventional form. Because every operation is differentiable, gradients of the training loss are back-propagated through the coupled solver, allowing both neural closures to be optimized consistently against the flow field, rather than fitted offline or in isolation. We demonstrate the framework, denoted Hybrid-Joint, on a zero-pressure-gradient turbulent boundary layer across a posteriori tests spanning Re_θ= 600--6500, computational domains and mesh resolutions. The model outperforms WMLES baselines, extrapolates to more than four times the highest training Reynolds number, and transfers to grids and domains absent from training. It recovers a logarithmic mean-velocity region, not imposed by the wall closure, and reproduces the resolved energy spectra accurately, although spectral information is excluded from the training objective. Ablation studies show that learning either closure alone is insufficient and that only joint optimization recovers the full set of statistics, confirming that SGS closure, wall closure and discretization are coupled and must be trained jointly. Once trained, the closures are reused without retraining across all cases, so that training cost is amortized over repeated deployment. △ Less

Submitted 19 July, 2026; originally announced July 2026.

Comments: 39 pages, 22 figures

Text2Villa: Hierarchical Generation of 3D Indoor Environments with Physics-Aware Analysis-by-Synthesis

Authors: Xiang Tang, Ruotong Li, Xiaopeng Fan

Abstract: Generating 3D indoor scenes from natural language holds tremendous potential, yet existing methods predominantly fail to generate multi-room structures with vertical connectivity and arbitrary polygonal boundaries. Furthermore, they lack a deep grounding in continuous 3D physical laws, leading to severe geometric penetrations and floating artifacts. In this work, we propose Text2Villa, a novel hie… ▽ More Generating 3D indoor scenes from natural language holds tremendous potential, yet existing methods predominantly fail to generate multi-room structures with vertical connectivity and arbitrary polygonal boundaries. Furthermore, they lack a deep grounding in continuous 3D physical laws, leading to severe geometric penetrations and floating artifacts. In this work, we propose Text2Villa, a novel hierarchical generative framework. At the macro level, we construct a multi-story dataset to fine-tune an autoregressive layout generator, ensuring the direct parsing of text into 3D building foundations featuring polygonal boundaries and multi-story connectivity. To enforce physical laws during micro-level asset arrangement, we introduce the Affordance-driven Physical-Semantic Scene Graph (A-PSSG) to explicitly abstract physical affordances (such as support surfaces and containment cavities) into node attributes, establishing strict geometric and semantic edge constraints. Guided by the A-PSSG, we formulate scene instantiation as a constrained closed-loop optimization problem following the analysis-by-synthesis paradigm. By integrating an underlying geometric collision detection engine with the high-level semantic reasoning of multimodal large language models (MLLMs), our heuristic solver dynamically executes physics-aware actions under the observation-evaluation-modification mechanism to effectively resolve mesh collisions, floating artifacts, and fine-grained cavity containment failures. Extensive experiments demonstrate that Text2Villa outperforms previous methods across various metrics, robustly generating high-fidelity and physically plausible villa-level 3D environments from text, thereby providing a reliable and interactive 3D content foundation for downstream applications. △ Less

Submitted 7 August, 2026; v1 submitted 19 July, 2026; originally announced July 2026.

Comments: 17 pages, 12 figures, Project page: https://xdlbw.github.io/Text2Villa/