Showing 1–50 of 3,537 results for author: Xu, Q

Architecture and Compilation Co-Design for High-Rate Quantum Product Codes on Neutral Atom Arrays

Authors: Adrian Liu, Wan-Hsuan Lin, Daniel Bochen Tan, Qian Xu, Jason Cong

Abstract: Achieving fault-tolerant quantum computing at a practical scale demands quantum error correction (QEC) codes with high encoding rates. Quantum low-density parity-check (qLDPC) codes emerge as a promising candidate, especially given the rise of neutral atom arrays that provide dynamic long-range connectivity via atom movements. In general, synthesizing valid and efficient physical execution plans f… ▽ More Achieving fault-tolerant quantum computing at a practical scale demands quantum error correction (QEC) codes with high encoding rates. Quantum low-density parity-check (qLDPC) codes emerge as a promising candidate, especially given the rise of neutral atom arrays that provide dynamic long-range connectivity via atom movements. In general, synthesizing valid and efficient physical execution plans for QEC is a provably hard combinatorial problem, forming a critical compilation bottleneck that worsens as code sizes grow. To overcome this complexity, we focus on an important product family of qLDPC codes with dimension-reduction properties, and propose ONEX. This framework decomposes complex 2D physical execution planning into independent 1D subproblems, each solved to optimal execution depth within practical compilation time. First, we formulate the 1D execution plan with an explicit satisfiability modulo theories (SMT) encoding. This protocol produces provably depth-optimal solutions with substantial duration reduction. Second, we develop a multi-stage compilation pipeline featuring anytime optimization, movement compaction, and iterative feedback. This pipeline maintains practical wall-clock times while providing progressive refinement and on-demand retrieval of quality solutions. Third, we evaluate ONEX in the application of hypergraph product (HGP) code memory mapped onto neutral atom arrays, achieving 3.7x to 6.1x and 29.8x to 42.1x higher clock rates than the constructive 1D algorithm and the general 2D compiler, respectively, while scaling efficiently to codes with 2,500 data qubits. Finally, we extend ONEX to zoned layouts, revealing architectural insights into the associated trade-offs, and demonstrate its applicability to the broader lifted-product (LP) code family through a representative example. △ Less

Submitted 20 August, 2026; originally announced August 2026.

Comments: 20 pages, 16 figures

Gradient regularity and potential estimates for fractional drift--diffusion equations in the critical and subcritical ranges

Authors: Qi Xue, Chao Zhang

Abstract: We establish scale-invariant interior $C^{1,α}$ estimates for bounded viscosity solutions of $(-Δ)^su+b\cdot\nabla u=f$ for $s\in[1/2,1)$ with locally Hölder $b$ and $f$. The critical case uses Silvestre's parabolic theorem; the subcritical case uses Schauder estimates and interpolation. Applying this viscosity estimate to drifted Green sections, for finite Radon data above the critical order we o… ▽ More We establish scale-invariant interior $C^{1,α}$ estimates for bounded viscosity solutions of $(-Δ)^su+b\cdot\nabla u=f$ for $s\in[1/2,1)$ with locally Hölder $b$ and $f$. The critical case uses Silvestre's parabolic theorem; the subcritical case uses Schauder estimates and interpolation. Applying this viscosity estimate to drifted Green sections, for finite Radon data above the critical order we obtain sharp solution and gradient potentials of orders $2s$ and $2s-1$, together with weak-*--to--strong local $W^{1,1}$ stability; hence the Green-potential SOLA is approximation-independent. For the normalized whole-space kernels, we identify the classical second-order limits as $s\uparrow1$, including the logarithmic kernel in dimension two; at the critical order, the whole-space gradient becomes a zero-order singular integral. For zero-exterior problems with compactly supported drift, we also prove $u/d^s\in C^{s-\varepsilon}(\overlineΩ)$ and identify the obstruction when the drift reaches the boundary. △ Less

Submitted 19 August, 2026; originally announced August 2026.

Many-Anyon Braiding in Non-Abelian Fractional Quantum Hall Effect with Hybrid Monte Carlo Simulation

Authors: Ting-Tung Wang, Ha Quang Trung, Qianhui Xu, Min Long, Bo Yang, Zi Yang Meng

Abstract: We employ the hybrid Monte Carlo method to efficiently compute the many-anyon non-Abelian braiding matrices associated with different braiding schemes of the Moore-Read quasiholes. A novel proposal in this work is that anyon braiding schemes based on a global rotation are robust against finite-size effects, as demonstrated by benchmarking their errors in the braiding matrix against those of a simp… ▽ More We employ the hybrid Monte Carlo method to efficiently compute the many-anyon non-Abelian braiding matrices associated with different braiding schemes of the Moore-Read quasiholes. A novel proposal in this work is that anyon braiding schemes based on a global rotation are robust against finite-size effects, as demonstrated by benchmarking their errors in the braiding matrix against those of a simple two-anyon exchange. Moreover, we investigate how electron-electron interactions and local electrostatic trapping potentials influence the energetic preference of different fusion channels. Their effect on the non-Abelian braiding matrices has been verified, a surprising phenomenon that demonstrates long-range entanglement of non-Abelian states. Our results are relevant to the experimental realization of non-Abelian physics in fractional quantum Hall and other analogous systems, including the fast-growing field of fractional quantum anomalous Hall states in moiré materials. △ Less

Submitted 18 August, 2026; originally announced August 2026.

Comments: 8+10 pages, 3+1 figures

First measurements of the branching fractions of $J/ψ$ and $ψ(3686) \to Σ^{0} \barΣ^{0}η$

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, 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, I. Boyko , et al. (750 additional authors not shown)

Abstract: Based on $(10087 \pm 44) \times 10^6$ $J/ψ$ and $(2712 \pm 14) \times 10^6$ $ψ(3686)$ events collected with the BESIII detector at the BEPCII collider, the hadronic decays $J/ψ\to Σ^{0} \barΣ^{0} η$ and $ψ(3686) \to Σ^{0} \barΣ^{0} η$ are observed for the first time. The corresponding branching fractions are measured to be… ▽ More Based on $(10087 \pm 44) \times 10^6$ $J/ψ$ and $(2712 \pm 14) \times 10^6$ $ψ(3686)$ events collected with the BESIII detector at the BEPCII collider, the hadronic decays $J/ψ\to Σ^{0} \barΣ^{0} η$ and $ψ(3686) \to Σ^{0} \barΣ^{0} η$ are observed for the first time. The corresponding branching fractions are measured to be $\mathcal{B}(J/ψ\to Σ^{0} \barΣ^{0}η)= (7.5 \pm 0.3 \pm 0.8) \times 10^{-5}$ and $\mathcal{B}(ψ(3686) \to Σ^{0} \barΣ^{0}η)= (1.3\pm 0.1 \pm 0.1) \times 10^{-5}$, respectively, where the first uncertainties are statistical, and the second systematic. The ratio $\text{Q} \approx \frac{\mathcal{B}(ψ(3686) \to Σ^{0} \barΣ^{0} η)}{\mathcal{B}(J/ψ\to Σ^{0} \barΣ^{0} η)}$ is determined to be $(17.3 \pm 1.5 \pm 1.7)\%$, which is con sistent with the 12\%-rule within 3.0$σ$.~No significant intermediate states or threshold enhancements are observed in the $Σ^0$($\barΣ^{0}$)$η$ and $Σ^0$$\barΣ^{0}$ invariant mass spectra. △ Less

Submitted 17 August, 2026; originally announced August 2026.

Real-Variable Characterizations and Their Applications of Anisotropic Besov Spaces with Matrix $\mathcal A_\infty$ Weights

Authors: Fan Bu, Shuaijun Feng, Qingying Xue, Dachun Yang, Wen Yuan

Abstract: Let $α\in\mathbb{R}$, $p\in(0,\infty)$, and $q\in(0,\infty]$. In this article, we develop a theory of matrix-weighted anisotropic Besov spaces associated with an expansive matrix $A$ and an $\mathcal A_{p,\infty}$-matrix weight $W$. We first introduce the homogeneous spaces $\dot B_{p,q}^α(A,W)$ and establish their $\varphi$-transform characterization. Then we construct counterexamples to show tha… ▽ More Let $α\in\mathbb{R}$, $p\in(0,\infty)$, and $q\in(0,\infty]$. In this article, we develop a theory of matrix-weighted anisotropic Besov spaces associated with an expansive matrix $A$ and an $\mathcal A_{p,\infty}$-matrix weight $W$. We first introduce the homogeneous spaces $\dot B_{p,q}^α(A,W)$ and establish their $\varphi$-transform characterization. Then we construct counterexamples to show that the assumption $W\in\mathcal A_{p,\infty}$ in this characterization cannot be relaxed to $W\in\bigcup_{r\in(0,\infty)}\mathcal A_r$. The same counterexamples also show that this weaker condition $W\in\bigcup_{r\in(0,\infty)}\mathcal A_r$ is insufficient to ensure the well-definedness of $\dot B_{p,q}^α(A,W)$. Next we characterize $\mathcal A_{p,\infty}$-matrix weights via the rescaled maximal operator, which leads naturally to a new concept of the critical rescaling index that quantitatively captures the self-improving behavior of matrix weights. In terms of this index, we obtain optimal boundedness for almost diagonal operators on the associated sequence spaces $\dot b_{p,q}^α(A,W)$. Based on these, we further establish the molecular characterization of $\dot B_{p,q}^α(A,W)$ and some sharp boundedness results for pseudo-differential operators on these spaces. △ Less

Submitted 17 August, 2026; originally announced August 2026.

Comments: 96 pages

MSC Class: Primary 46E35; Secondary 47A56; 42B25; 42B35; 35S05

Measurement of Branching Fraction and Transition Magnetic Moment of the Hyperon Dalitz Decay $Σ^0 \rightarrow Λe^+e^-$

Authors: BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson, X. C. Ai, R. Aliberti, A. Amoroso, Q. An, Y. Bai, O. Bakina, Y. Ban, H. -R. Bao, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. B. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone, I. Boyko, R. A. Briere, A. Brueggemann, H. Cai , et al. (683 additional authors not shown)

Abstract: Based on a data sample of 10 billion $J/ψ$ events collected with the BESIII detector operating at the BEPCII collider, the Dalitz decay $Σ^0 \rightarrow Λe^+e^-$ is studied experimentally for the first time. The $Σ^0$ hyperons are produced through the process $J/ψ\rightarrow Σ^0\barΣ^0$ and analyzed using a double-tag method. The absolute branching fraction is measured to be… ▽ More Based on a data sample of 10 billion $J/ψ$ events collected with the BESIII detector operating at the BEPCII collider, the Dalitz decay $Σ^0 \rightarrow Λe^+e^-$ is studied experimentally for the first time. The $Σ^0$ hyperons are produced through the process $J/ψ\rightarrow Σ^0\barΣ^0$ and analyzed using a double-tag method. The absolute branching fraction is measured to be $\mathcal{B}(Σ^0 \rightarrow Λe^+e^-) = (6.34 \pm 0.25_{\rm stat.} \pm 0.23_{\rm syst.}) \times 10^{-3}$. This result shows a $2σ$ discrepancy from the theoretical calculation quoted in the PDG, where the uncertainties are statistical and systematic, respectively. In addition to the branching fraction, the transition magnetic moment $μ$ is determined to be $(1.74 \pm 0.03_{\rm stat.} \pm 0.09_{\rm syst.})\,μ_N$, where $μ_N=e/(2m_p)$ represents the nucleon magnetic moment, providing valuable insight into the intrinsic structure of the $Σ^0$ hyperon. △ Less

Submitted 17 August, 2026; originally announced August 2026.

Comments: 10 pages, 3 figures; supplemental material included

Revisiting environmental effects on black hole quasibound-state spectra with relativistic perturbation theory

Authors: Yin-Da Guo, Qi-Xuan Xu, Richard Brito, Enrico Cannizzaro

Abstract: We present a relativistic framework for computing corrections to the eigenfrequency spectrum of a massive scalar field in perturbed black-hole spacetimes, including first-order shifts to decay rates and second-order mode-mixing effects. We also clarify the regime of validity of non-relativistic treatments and show that the accuracy of completeness-based descriptions is limited, highlighting the no… ▽ More We present a relativistic framework for computing corrections to the eigenfrequency spectrum of a massive scalar field in perturbed black-hole spacetimes, including first-order shifts to decay rates and second-order mode-mixing effects. We also clarify the regime of validity of non-relativistic treatments and show that the accuracy of completeness-based descriptions is limited, highlighting the non-Hermitian nature of the spectrum. Using galactic halos and accretion disks as physically motivated perturbations, we benchmark the relativistic perturbative predictions to the eigenfrequency shifts against non-perturbative numerical solutions. We also present first-order relativistic eigenfrequency shifts induced by binary companions, whose potentially stronger impact on superradiant dynamics of massive scalar fields around spinning black holes motivates future dedicated analyses. Our results suggest that previous estimates of the termination of superradiance due to binary companions and disks should be revisited within a relativistic framework. △ Less

Submitted 14 August, 2026; originally announced August 2026.

Comments: 19 pages, 9 figures

Exposing SIMD Parallelism in SQIsign: An AVX-512 Implementation

Authors: Weize Wang, Chutong Wang, Yu Wu, Qifan Xue, Jieyu Zheng, Yunlei Zhao

Abstract: Modern isogeny-based cryptosystems spend much of their running time in finite-field, elliptic-curve, and higher-dimensional isogeny arithmetic. Exploiting SIMD parallelism is nontrivial: routines such as Montgomery ladders contain loop-carried dependencies, while point, pairing, and theta-coordinate formulas expose only irregular fine-grained parallelism. We show that substantial SIMD parallelism… ▽ More Modern isogeny-based cryptosystems spend much of their running time in finite-field, elliptic-curve, and higher-dimensional isogeny arithmetic. Exploiting SIMD parallelism is nontrivial: routines such as Montgomery ladders contain loop-carried dependencies, while point, pairing, and theta-coordinate formulas expose only irregular fine-grained parallelism. We show that substantial SIMD parallelism can be recovered by reorganizing the arithmetic dependency graphs of higher-level primitives rather than vectorizing field multiplication in isolation. We develop an end-to-end AVX-512IFMA implementation of SQIsign in which data remain in a radix-$2^{51}$ vector representation across most of the curve-side computation. Our redesign includes projective xDBLADD schedules, batched point doubling in several coordinate systems, a vectorized biscalar ladder, fused cubical-arithmetic pairing steps, and batched one- and two-dimensional isogeny evaluation. Relative to the reference C implementation, we achieve end-to-end speedups of $1.76\times$, $1.71\times$, and $3.18\times$ for key generation, signing, and verification at NIST level~I; combined with Qlapoti, key-generation and signing speedups rise to $2.90\times$ and $2.69\times$. We further apply the same backend and methodology to CORAL, a recent isogeny group action for post-quantum non-interactive key exchange based on two-dimensional $2$-isogenies. Across five parameter sets, this yields $1.28$--$1.40\times$ speedups for key generation and $1.92$--$2.46\times$ for shared-key computation. These results provide cross-scheme evidence that algorithm-level SIMD scheduling is a reusable optimization dimension for higher-dimensional isogeny cryptography. △ Less

Submitted 17 August, 2026; v1 submitted 14 August, 2026; originally announced August 2026.

Sensorimotor Stickies: A Reconfigurable On-Body Platform for Closed-Loop Sensorimotor Training

Authors: Tianhong Catherine Yu, Jiwei Zheng, Chi-Jung Lee, Qifeng Yang, Tingyu Cheng, Qiuyue Shirley Xue, Cheng Zhang, Yiyue Luo

Abstract: Closed-loop sensorimotor training systems can improve learning by sensing movement and delivering real-time feedback, yet most are built as fixed implementations tied to a single task, even though the core technology (inertial and tactile sensing, vibrotactile cueing, rule-based logic) remains the same. We present Sensorimotor Stickies, a reconfigurable on-body platform that treats sensing and vib… ▽ More Closed-loop sensorimotor training systems can improve learning by sensing movement and delivering real-time feedback, yet most are built as fixed implementations tied to a single task, even though the core technology (inertial and tactile sensing, vibrotactile cueing, rule-based logic) remains the same. We present Sensorimotor Stickies, a reconfigurable on-body platform that treats sensing and vibrotactile feedback as modular stickies that can be patched onto the body as needed. The platform includes miniaturized adhesive modules for IMU sensing, optional tactile sensing, and vibrotactile actuation; low-power firmware and BLE infrastructure for raw streaming and motor control without task-specific rewrites; and a companion mobile app that provides a shared body-centered model for placement, calibration, and feedback authoring. Together, these components enable reconfiguration across training scenarios, user needs, and feedback setups. We evaluate the platform through technical characterization, configured application demonstration, practitioner-mediated configuration sessions, and an end-user study, demonstrating technical feasibility, reconfiguration breadth, and end-user configurability for first-time setup, calibration, and within-task feedback reconfiguration. △ Less

Submitted 16 August, 2026; v1 submitted 13 August, 2026; originally announced August 2026.

UniTraffic-Agent: Unified Traffic Video Reasoning for AI City Challenge 2026 Track 3 with Two Out-of-Domain Evaluations

Authors: Peng Li, Qianqian Xu, Shilong Bao, Yangbangyan Jiang, Qingming Huang

Abstract: Traffic video understanding has become an important problem in intelligent transportation, as road videos provide direct evidence for accidents, violations, and interactions between vehicles and vulnerable road users. A useful system should explain how a traffic event develops, why it happens, and when the relevant interaction occurs, yet this remains difficult for multimodal large language models… ▽ More Traffic video understanding has become an important problem in intelligent transportation, as road videos provide direct evidence for accidents, violations, and interactions between vehicles and vulnerable road users. A useful system should explain how a traffic event develops, why it happens, and when the relevant interaction occurs, yet this remains difficult for multimodal large language models (MLLMs) because traffic videos contain sparse events and varied viewpoints. We introduce UniTraffic-Agent, the MR-CAS solution for Track~3 of the 10th AI City Challenge, which includes Traffic Anomaly Reasoning (TAR) and two out-of-domain evaluations: FETV for fisheye traffic events and PSI-VQA for pedestrian intention reasoning. UniTraffic-Agent follows an observe--reason--act--verify workflow that samples timestamped visual evidence, reasons over all questions from the same clip in one request, and converts responses through task-specific action adapters. On the official Public leaderboards, MR-CAS ranks 16th on TAR with a score of 0.5780, 2nd on FETV with 0.4884, and 4th on PSI-VQA with 64.4161. The code is available at https://github.com/Roclp/UniTraffic-Agent. △ Less

Submitted 13 August, 2026; originally announced August 2026.

Comments: This paper has been accepted to ECCV 2026 AI City Challenge Workshop

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.

Spec-Driven Hardware Evolution via Executable Contract Refinement and Proof-Guided RTL Update

Authors: Shibo Zhao, Yang Zhang, Mengxia Tao, Baoqi Zhang, Kezhi Li, Qiang Xu, Binwu Zhu, Hao Yan, Min Li

Abstract: Hardware development is inherently evolutionary: major revisions typically begin by changing intended behavior and then updating a previously validated implementation, rather than regenerating RTL from scratch. Yet most recent LLM-based hardware research still frames the task primarily as prompt-to-RTL generation, offering limited support for semantic version evolution of trusted legacy designs. W… ▽ More Hardware development is inherently evolutionary: major revisions typically begin by changing intended behavior and then updating a previously validated implementation, rather than regenerating RTL from scratch. Yet most recent LLM-based hardware research still frames the task primarily as prompt-to-RTL generation, offering limited support for semantic version evolution of trusted legacy designs. We present spec-driven hardware evolution, a contract-centered formulation for RTL version iteration. Instead of treating a new feature request as a direct prompt for RTL generation, we refine it into a reviewed executable contract for the next version. This contract specifies what must hold at the externally visible transactional level through a behavior-level reference together with explicit observation and checking semantics, while leaving how the change is realized in RTL to the evolution process. Based on this formulation, we organize hardware evolution into four stages: Specify, Plan, Implement, and Validate. After contract approval, the remaining stages proceed automatically: Plan derives cross-version semantic deltas and localizes affected RTL regions, aided by mutation-based semantic probing; Implement and Validate then perform legacy-aware RTL update under proof-guided checking and iterative repair. We evaluate the framework on a controlled version-evolution case study of a representative TPU datapath block under data-format changes. The results support the feasibility of contract-driven hardware evolution and demonstrate that the proposed backend workflow can effectively drive validated legacy RTL toward next-version functional convergence under a reviewed executable contract. An anonymous artifact for reproducibility is available at https://anonymous.4open.science/r/SDHE-3A6C. △ Less

Submitted 12 August, 2026; originally announced August 2026.

4$π$ Planning for the Reduction of Predicted Hematologic Toxicity Risk in Cervical Cancer Radiotherapy

Authors: Haotian Feng, Yan Kong, Qifan Xu, Ke Sheng

Abstract: Purpose: In conventional coplanar radiotherapy for cervical cancer, nearby pelvic bones receive high radiation doses, increasing the risk of acute hematologic toxicity (HT). This study aims to estimate the HT risk reduction achievable with non-coplanar (4$π$) radiotherapy. Methods: We retrospectively analyzed 114 cervical cancer patients treated with coplanar volumetric modulated arc therapy (VMAT… ▽ More Purpose: In conventional coplanar radiotherapy for cervical cancer, nearby pelvic bones receive high radiation doses, increasing the risk of acute hematologic toxicity (HT). This study aims to estimate the HT risk reduction achievable with non-coplanar (4$π$) radiotherapy. Methods: We retrospectively analyzed 114 cervical cancer patients treated with coplanar volumetric modulated arc therapy (VMAT) between 2021 and 2023. Radiomic features from planning CTs were extracted and combined with clinical and dosimetric data to train predictive machine learning models. Patients were then replanned using integrated non-coplanar beam orientation and fluence map optimization (4$π$ planning). The top performing model was applied to these new plans to evaluate potential HT reduction. Results: Models combined radiomics, clinical, and dosimetric features achieved the highest predictive performance (AUC = 0.79). Feature importance analysis highlighted CT radiomic and dosimetric variables as the strongest predictors. Compared to VMAT, 4$π$ non-coplanar planning significantly reduced doses to the bone marrow (V10Gy, V20Gy, V30Gy, and V40Gy by 28%, 52%, 47%, and 33%, respectively) while significantly reducing dose to other pelvic organs at risk (OAR). When evaluated by the model, this improved dosimetry translated into a 23% reduction in predicted HT risk (risk ratio: 0.77; 95% CI: 0.75-0.79 and odds ratio: 0.68; 95% CI:0.65-0.71). Conclusions: Non-coplanar 4$π$ radiotherapy significantly lowers radiation doses to major pelvic bones during cervical cancer treatment without compromising target coverage or sparing of other OARs. Based on our predictive model, this superior dosimetry should translate to a marked reduction in acute hematologic toxicity. △ Less

Submitted 12 August, 2026; originally announced August 2026.

High-dimensional Multi-objective Bayesian Optimization with Learned Variable Interactions

Authors: Hongyan Wang, Jiayu Huang, Haotian Zheng, Xin Gao, Chi Ding, Ying Liu, Xia Wang, Qing Xu, Keqiang Li

Abstract: Multi-objective Bayesian optimization (MOBO) is effective in identifying the Pareto fronts for expensive black-box problems. However, most current MOBO approaches are limited to low-dimensional decision space due to its exponential sampling complexity. This paper presents decision variable interaction analysis-based MOBO, ViaMOBO, a generic framework for expensive multi-objective problems with hig… ▽ More Multi-objective Bayesian optimization (MOBO) is effective in identifying the Pareto fronts for expensive black-box problems. However, most current MOBO approaches are limited to low-dimensional decision space due to its exponential sampling complexity. This paper presents decision variable interaction analysis-based MOBO, ViaMOBO, a generic framework for expensive multi-objective problems with high-dimensional decision space. The key idea of ViaMOBO is that it utilizes a variable interaction analysis model to determine whether the decision space can be completely or partially divided, and then performs local Bayesian optimization in the divided decision subspaces. Through the variable analysis model, it can be derived whether the objectives in black-box problems are separable, partially separable, or non-separable based on the potential independent or interdependent relationships among decision variables without any strong assumptions. We compare ViaMOBO with the state-of-the-art MOBO methods on both synthetic and real-world benchmarks. The experimental results demonstrate that ViaMOBO outperforms other related MOBO baselines in approximating the Pareto front of high-dimensional expensive multi-objective problems. △ Less

Submitted 12 August, 2026; originally announced August 2026.

Comments: 13 pages, 15 figures, 3 tables

FaithformBench: Benchmarking Faithfulness of Mathematical Chain-of-Thought Autoformalisation

Authors: Rob Cornish, Iacopo Ghinassi, Po-Hung Yeh, Shuqi Liu, Qiyuan Xu, Haoxuan Yin, Dominik Wagner, Wenda Li, Yee Whye Teh, Luke Ong

Abstract: Autoformalisation (AF) systems map natural language reasoning steps into formal statements in a proof assistant such as Lean. We consider how to assess the faithfulness of these systems. Existing approaches require expensive human-annotated ground truth, or rely on LLM judges or embedding models, which come with limited guarantees of accuracy. In addition, these methods typically only consider inp… ▽ More Autoformalisation (AF) systems map natural language reasoning steps into formal statements in a proof assistant such as Lean. We consider how to assess the faithfulness of these systems. Existing approaches require expensive human-annotated ground truth, or rely on LLM judges or embedding models, which come with limited guarantees of accuracy. In addition, these methods typically only consider inputs that are known to be correct, and therefore do not assess whether the AF translates incorrect inputs faithfully. To address these limitations, we propose a new benchmark for AF faithfulness that is cheap to apply, sound under weak assumptions, and assesses both positive and negative examples. Our method is based on automatically generating perturbed reasoning steps that are designed to be invalid, and then measuring validity preservation on unperturbed steps and invalidity preservation on perturbed steps. We apply our method to eight AF systems across four mathematical datasets, and observe pervasive sycophancy: many AFs "silently correct" invalid inputs into provable statements. The most validity-preserving fine-tuned AFs are also the most sycophantic, suggesting a tension between validity and invalidity preservation in current AF systems. △ Less

Submitted 11 August, 2026; originally announced August 2026.

ACM Class: I.2.3; I.2.7; I.2.2

HINT: Toward an Executable Hardware-Intent Representation Layer for LLM-Driven RTL Generation

Authors: Tairan Cheng, Yi Liu, Dongsheng Zuo, Zhengyuan Shi, Hongji Zhang, Xiangfei Hu, Maoshuo He, Hao Yan, Qiang Xu

Abstract: Generating implementation-quality RTL with large language models (LLMs) remains difficult because direct generation must resolve microarchitecture while simultaneously producing and debugging low-level code. We present HINT, an executable hardware-intent intermediate representation layer between behavioral specifications or executable oracles and RTL. HINT makes RTL-relevant microarchitecture expl… ▽ More Generating implementation-quality RTL with large language models (LLMs) remains difficult because direct generation must resolve microarchitecture while simultaneously producing and debugging low-level code. We present HINT, an executable hardware-intent intermediate representation layer between behavioral specifications or executable oracles and RTL. HINT makes RTL-relevant microarchitecture explicit, supports pre-RTL checking, and supplies explicit RTL-lowering obligations. We evaluate HINT using both a minimal single-agent flow and a full staged workflow. Across seven operator cases, the HINT-mediated route, with no post-synthesis QoR refinement, produces contract-compliant synthesizable RTL on 7/7 cases; Direct C2RTL and C2HLSC apply to five cases and succeed on 5/5 and 1/5, respectively. Under matched Design Compiler synthesis, HINT reduces area by 5.0\%--26.2\% relative to five manual RTL implementations and by 8.9\%--86.1\% relative to five accepted Direct C2RTL results. RealBench AES and SDC, together with a Vortex VPU synthesizing to 561.67k~$μ\mathrm{m}^2$, further demonstrate specification-driven, protocol-rich, memory-rich, and hierarchical designs. In the controlled operator study, the HINT-mediated route shows better observed convergence and avoids the severe implementation-quality degradation seen in several direct-generation results. △ Less

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

Search for the charged lepton flavour violating decay $η'\to eμ$

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. (744 additional authors not shown)

Abstract: Based on $(8998\pm40)\times10^6$ $J/ψ$ events collected in $e^+e^-$ collisions at $\sqrt{s} = 3.097$ GeV with the BESIII detector, we present a search for the charged lepton flavour violating decay $η'\to eμ$ with $J/ψ\toγη'$. No significant signal is observed, and an upper limit on its decay branching fraction is set to be $6.3\times10^{-7}$ at the 90% confidence level, improving the previous bes… ▽ More Based on $(8998\pm40)\times10^6$ $J/ψ$ events collected in $e^+e^-$ collisions at $\sqrt{s} = 3.097$ GeV with the BESIII detector, we present a search for the charged lepton flavour violating decay $η'\to eμ$ with $J/ψ\toγη'$. No significant signal is observed, and an upper limit on its decay branching fraction is set to be $6.3\times10^{-7}$ at the 90% confidence level, improving the previous best result by nearly three orders of magnitude. △ Less

Submitted 6 August, 2026; originally announced August 2026.

Comments: 20 pages, 5 figures, 3 tables

DistMedVL: Distributional Vision-Language Alignment for Uncertainty-Aware Medical Image Segmentation

Authors: Jiaxuan Li, Qing Xu, Xiangjian He, Yue Li, Daokun Zhang, Fiseha B. Tesema, Rong Qu

Abstract: Cross-modal alignment of visual and textual representations is fundamental to multimodal medical image understanding, yet remains hindered by uncertainty in both modalities under real-world clinical conditions. Existing vision-language segmentation methods rely on deterministic cross-modal matching, which overlooks aleatoric uncertainty from ambiguous boundaries and epistemic uncertainty from limi… ▽ More Cross-modal alignment of visual and textual representations is fundamental to multimodal medical image understanding, yet remains hindered by uncertainty in both modalities under real-world clinical conditions. Existing vision-language segmentation methods rely on deterministic cross-modal matching, which overlooks aleatoric uncertainty from ambiguous boundaries and epistemic uncertainty from limited training data, leading to fragile performance under domain shift. To address this issue, we propose DistMedVL, a probabilistic vision-language framework that introduces a lightweight Probabilistic Cross-Modal Adapter (PCM-Adapter) upon frozen encoders to explicitly model representational uncertainty. Specifically, the PCM-Adapter comprises two sequential modules for progressive probabilistic alignment. We first devise a Mahalanobis Alignment Module (MAM) that models textual tokens as Gaussian distributions and computes patch-text compatibility via Mahalanobis distance, yielding variance-conditioned matching that downweights unreliable feature dimensions. Moreover, we devise a Distribution Flow Module (DFM) that estimates modality-wise confidence parameters and performs vision-guided refinement of textual distributions, accommodating distributional variation across imaging modalities. Extensive experiments across eight medical segmentation benchmarks demonstrate that DistMedVL outperforms state-of-the-art methods with only 6.3M trainable parameters, exhibiting superior data efficiency, perturbation robustness and cross-dataset generalization. △ Less

Submitted 6 August, 2026; originally announced August 2026.

Comments: 10 pages, 5 figures

ACM Class: I.5.1; I.4.6

PromptShield Home: Ambient Multimodal Prompt Injection Defense for Smart-Home Agents

Authors: He Zhang, Feilong Li, Dingning Long, Yilin Cui, Peijun Zhang, Yuewen Zhang, Qianyao Xu, Xinyi Fu

Abstract: Smart-home assistants increasingly use multimodal large language models (MLLMs) that perceive video and audio directly. This raises a safety question specific to the home: can the agent tell a genuine user command from ambient or externally-sourced content, television speech, on-screen text, or an overheard conversation, that merely looks like a command? We introduce PromptShield-Home, a pilot ben… ▽ More Smart-home assistants increasingly use multimodal large language models (MLLMs) that perceive video and audio directly. This raises a safety question specific to the home: can the agent tell a genuine user command from ambient or externally-sourced content, television speech, on-screen text, or an overheard conversation, that merely looks like a command? We introduce PromptShield-Home, a pilot benchmark of realistic smart-home scenarios spanning addressee ambiguity, screen/audio injection, health-monitor false triggers, mixed occupancy, and a legitimate-command floor, and use it to compare three abstraction layers: traditional detectors (L0), a single MLLM agent (L1; vision, vision+ASR, and audio-visual), and multi-agent mediation (L2; voting, role specialists, cross-model arbitration). Because the label distribution is skewed toward inaction, aggregate accuracy is misleading, a constant always-block predictor scores 82%, so we report unsafe-execution and safe-completion rates separately. The two paradigms fail in opposite ways: detectors act on everything, while every MLLM configuration over-refuses, completing almost no genuine command and missing a true fall in every case. Crucially, their correct sets are disjoint: an oracle that always picks the right layer reaches 94.1%, against 76.5% for the best single layer. We report this as an upper bound, not a system - no router is implemented - and argue that home-agent safety is best served by learned routing and sensor fusion, not by replacing detectors with an MLLM. △ Less

Submitted 5 August, 2026; originally announced August 2026.

Comments: This work has been accepted as a poster to UbiComp 2026

Disentangling 3D Modeling from Spatial Reasoning

Authors: Haoze Sun, Jiequan Cui, Qingshan Xu, Richang Hong

Abstract: In this work, we explore an alternative paradigm for spatial reasoning by explicitly disentangling 3D perception from reasoning, rather than jointly acquiring implicit 3D perception and reasoning through large-scale training. Our key observation is that modern perception models excel at estimating continuous 3D geometry, whereas large language models (LLMs) are particularly effective at compositio… ▽ More In this work, we explore an alternative paradigm for spatial reasoning by explicitly disentangling 3D perception from reasoning, rather than jointly acquiring implicit 3D perception and reasoning through large-scale training. Our key observation is that modern perception models excel at estimating continuous 3D geometry, whereas large language models (LLMs) are particularly effective at compositional and symbolic reasoning. Motivated by these complementary strengths, we propose the Disentangled Spatial Reasoner (DiSR), a simple yet effective framework that reconstructs the physical world into structured 3D evidence using off-the-shelf expert perception models and fine-tunes an LLM with LoRA to perform reasoning solely over this explicit geometric evidence. Without large-scale 3D VQA training or complex tool-use policies, DiSR achieves competitive performance on popular spatial reasoning benchmarks. Beyond its strong performance, DiSR offers improved interpretability, modularity, and computational efficiency, demonstrating that explicit separation of perception and reasoning is a scalable and effective alternative paradigm to end-to-end modeling for spatial intelligence. △ Less

Submitted 6 August, 2026; v1 submitted 5 August, 2026; originally announced August 2026.

TwinIR: Coordinated Invisible Dual-Point Attacks on Online HD Map Construction

Authors: Haibo Hu, Jianghuai Deng, Chen Tang, Yang Lou, Qian Xu, Jianping Wang

Abstract: Online HD map construction is critical to prediction and planning in autonomous driving. We find that existing physical attacks against online map construction are limited by a cross-boundary compensation effect: after the target boundary is perturbed, another visible boundary may retain sufficient geometric cues for the model to recover the original road geometry. Based on this observation, we pr… ▽ More Online HD map construction is critical to prediction and planning in autonomous driving. We find that existing physical attacks against online map construction are limited by a cross-boundary compensation effect: after the target boundary is perturbed, another visible boundary may retain sufficient geometric cues for the model to recover the original road geometry. Based on this observation, we propose TwinIR, a new mechanism-guided physical attack methodology for online map construction. TwinIR jointly optimizes attack effectiveness and point sparsity, seeking the minimum number of attack points needed to suppress compensating geometric cues from surrounding boundaries. To reduce the perceptibility of multi-point attacks, TwinIR models camera responses to near-infrared illumination and maps optimized attack points to feasible physical placements, producing camera-visible interference with minimal visible-spectrum changes. Experiments on nuScenes across state-of-the-art online map construction models show that TwinIR reduces mAP by 8.18-8.96 percentage points under RSA and 2.84-5.62 points under ETA, while increasing the unreachable-goal rate by 25-28 points and the unsafe-planned-trajectory rate by 19-20 points over clean inputs. These attacks are also validated on a real-world testbed AV, where TwinIR successfully induces both road straightening and early-turn deformations while remaining inconspicuous in full-color views. △ Less

Submitted 5 August, 2026; originally announced August 2026.

CARE: A Cascaded Framework for Efficient and Reliable Time Series Anomaly Detection

Authors: Zemin Chao, Qianhui Xu, Jianhe Cen, Guangzhi Ge, Xiao Chen, Hoangzhi Wang

Abstract: While deep learning models have achieved state-of-the-art performance in time series anomaly detection, their complex architectures incur substantial inference overhead. Existing methods typically apply a uniform inference strategy across all data points, which is inefficient given that anomalies are inherently scarce and the vast majority of temporal data consists of predictable normal patterns.… ▽ More While deep learning models have achieved state-of-the-art performance in time series anomaly detection, their complex architectures incur substantial inference overhead. Existing methods typically apply a uniform inference strategy across all data points, which is inefficient given that anomalies are inherently scarce and the vast majority of temporal data consists of predictable normal patterns. To mitigate this bottleneck, we propose CARE, a model-agnostic cascaded inference framework that integrates a Lightweight Pre-filter Model (LPM) with an existing high-capacity Complex Detection Model (CDM). The LPM rapidly filters high-confidence normal samples using a Residual MLP AutoEncoder and a Normality-Conditioned Gating mechanism. Crucially, we introduce a Structure Attention module to explicitly capture channel-wise anomaly contributions, and optimize the gating network via a confidence-guided selective routing objective that learns reliable routing decisions to reduce unnecessary CDM invocations. Extensive experiments across eight real-world benchmarks demonstrate that CARE effectively isolates high-confidence normal samples. By routing only uncertain samples to the CDM, our framework achieves $2.7\times$ to $4.8\times$ inference speedup compared to the most accurate SOTA approaches, while still maintaining competitive detection quality. △ Less

Submitted 3 August, 2026; originally announced August 2026.

Microwave Response of the Superconducting Diode Effect in Proximitized Bilayer Graphene Interferometers

Authors: Shili Yan, Rubén Seoane Souto, Yi Luo, Jeroen Danon, Haitian Su, Junze Zhang, Han Gao, Xingjun Wu, Ji-Yin Wang, H. Q. Xu

Abstract: Microwave irradiation has emerged as a promising means to tune the superconducting diode effect (SDE) in Josephson junction devices. Previous experimental studies have mainly focused on the adiabatic-driving regime, in which the diode efficiency increases monotonically with microwave power and can approach the ideal value of unity. Beyond this regime, however, the microwave response of the SDE rem… ▽ More Microwave irradiation has emerged as a promising means to tune the superconducting diode effect (SDE) in Josephson junction devices. Previous experimental studies have mainly focused on the adiabatic-driving regime, in which the diode efficiency increases monotonically with microwave power and can approach the ideal value of unity. Beyond this regime, however, the microwave response of the SDE remains largely unexplored experimentally. In this work, we investigate the microwave response of the SDE in bilayer-graphene-based superconducting quantum interference devices (SQUIDs) under a broad range of driving frequencies. We show that increasing the driving frequency changes the response characteristics of the diode efficiency to microwave power--the dependence of the diode efficiency evolves from monotonic enhancement with increasing microwave power in the adiabatic regime to non-monotonic behavior beyond this regime, and ultimately to sign-reversal as well oscillatory characteristics at sufficiently high frequencies. We find that these experimentally observed frequency-dependent power response characteristics of the diode efficiency can be qualitatively captured by simulations based on the resistively shunted junction model using the device current-phase relations extracted from the experiments. These results establish SQUIDs made from bilayer graphene as a versatile platform for studying dynamic properties of superconducting junction devices. △ Less

Submitted 2 August, 2026; originally announced August 2026.

Look Up and Look Back: Hidden Attention and Latent Orientation in a Frozen Foundation Model for Panoramic SLAM

Authors: Zhuang Xiong, Guohao Zhang, Chen Zhang, Zheyu Jiang, Yuchao Mei, Qingshan Xu, Wenbing Tao

Abstract: Monocular panoramic SLAM benefits from substantial visual overlap under large camera rotations, yet remains prone to errors caused by camera tilt, scale drift, and false loop closures. We show that a frozen panoramic geometry foundation model provides useful internal cues beyond its explicit geometric outputs: intermediate tokens encode gravity in the camera frame, while cross-view attention provi… ▽ More Monocular panoramic SLAM benefits from substantial visual overlap under large camera rotations, yet remains prone to errors caused by camera tilt, scale drift, and false loop closures. We show that a frozen panoramic geometry foundation model provides useful internal cues beyond its explicit geometric outputs: intermediate tokens encode gravity in the camera frame, while cross-view attention provides a compatibility cue for potential revisits. Building on these cues, we present HALO-SLAM. A gravity readout enables IMU-free spherical upright canonicalization. For loop closure, we introduce a cost-aware three-stage cascade combining DBoW2 event-level retrieval, attention-based compatibility filtering, and dense geometric validation through symmetric submap augmentation. Accepted revisits yield pixel-aligned 3D--3D correspondences in both local gauges, from which robust $\mathrm{Sim}(3)$ constraints are estimated and jointly optimized with sequential constraints in a global pose graph. Across 125 sequences from five real-world panoramic benchmarks, our method achieves \textbf{100\%} sequence success (\textbf{125/125}) under the stated criterion and the lowest ATE among the evaluated methods on all five benchmarks, reducing ATE by \textbf{30--88\%} relative to the best ERP-native baseline on each benchmark. △ Less

Submitted 1 August, 2026; originally announced August 2026.

Exponential Reward Weighting for Fine-Tuning Generative Recommenders under Sparse and Noisy Feedback

Authors: Keertana Chidambaram, Sanath Kumar Krishnamurthy, Qiuling Xu, Ko-Jen Hsiao, Moumita Bhattacharya

Abstract: In recommendation systems, users interact with only a small fraction of a vast item catalog, producing feedback that is both sparse and noisy. This challenges post-training generative recommenders: reward models trained from logged interactions often fail to generalize, while directly optimizing imperfect rewards can lead to reward over-optimization. We propose Exponential reward-weighted fine-tun… ▽ More In recommendation systems, users interact with only a small fraction of a vast item catalog, producing feedback that is both sparse and noisy. This challenges post-training generative recommenders: reward models trained from logged interactions often fail to generalize, while directly optimizing imperfect rewards can lead to reward over-optimization. We propose Exponential reward-weighted fine-tuning (Exp-RSFT), where each logged interaction is weighted by $\exp(r/λ)$, avoids this failure by optimizing directly on the logged rewards, with the temperature $λ$ regularizing against their noise. We theoretically show that Exp-RSFT's suboptimality decomposes into two costs: a coverage cost arising from limitations of the logging policy and a noise cost from imperfect feedback. The temperature $λ$ balances these competing effects, yielding an optimal tradeoff between exploiting high-reward behavior and robustness to noise. Across three public benchmarks and a large-scale industrial dataset, we verify this theoretical prediction: performance follows an inverted-U trend as a function of $λ$, while PPO and DPO often over-optimize unreliable reward models and degrade recommendation quality. Exp-RSFT consistently improves ranking performance without requiring online exploration or preference data. △ Less

Submitted 1 August, 2026; originally announced August 2026.

Data-Driven Batteryless Channel Sounding for Wi-Fi 8-Inspired Downlink MU-MIMO

Authors: Muhan Zhang, Chuqi Zhang, Qitong Xu, Zhaoyu Liu, Liu Cao, Lyutianyang Zhang, Ming Gan

Abstract: Batteryless overlays couple passive throughput to Wi-Fi sounding overhead and channel state information (CSI) aging. This paper investigates channel sounding for ultra-high reliability (UHR) operation in a Wi-Fi 8/IEEE 802.11bn-inspired downlink multi-user multiple-input multiple-output (MU-MIMO) system with a batteryless passive overlay. We optimize the post-sounding transmission interval to maxi… ▽ More Batteryless overlays couple passive throughput to Wi-Fi sounding overhead and channel state information (CSI) aging. This paper investigates channel sounding for ultra-high reliability (UHR) operation in a Wi-Fi 8/IEEE 802.11bn-inspired downlink multi-user multiple-input multiple-output (MU-MIMO) system with a batteryless passive overlay. We optimize the post-sounding transmission interval to maximize the aggregate throughput of the active Wi-Fi and passive links, while jointly accounting for sounding overhead, CSI aging, modulation and coding scheme (MCS), passive attenuation, and passive data rate. A packet-level cross-layer model evaluates the cycle-average throughput, and a data-driven search identifies the optimal interval under different operating conditions. Simulations demonstrate that passive overlay reshapes the conventional sounding tradeoff: depending on the MCS and passive-link configuration, the additional passive throughput may or may not compensate for the associated Wi-Fi reliability loss, causing the optimal interval to shift. The results provide design guidance for reliable and low-power MU-MIMO WLANs. △ Less

Submitted 31 July, 2026; originally announced July 2026.

Comments: This work has been accepted to the 2026 IEEE/CIC International Conference on Communications in China (ICCC Workshops).6 pages,4 figures,conference paper

Federated Foundation Models Fine-Tuning with Heterogeneous Compressed Clients

Authors: Shengkun Zhu, Jinshan Zeng, Zhihua Allen-Zhao, Mayi Xu, Quanqing Xu, Wei Ren, Qiang Yang, Yang Liu

Abstract: Federated learning of foundation models faces a fundamental resource-asymmetry challenge: the institutions holding the most valuable domain-specific data cannot host billion-parameter models. Existing heterogeneous federated approaches attempt to bridge this gap through parameter-efficient tuning, model pruning, or knowledge distillation, yet each trades away a critical property, whether full-mode… ▽ More Federated learning of foundation models faces a fundamental resource-asymmetry challenge: the institutions holding the most valuable domain-specific data cannot host billion-parameter models. Existing heterogeneous federated approaches attempt to bridge this gap through parameter-efficient tuning, model pruning, or knowledge distillation, yet each trades away a critical property, whether full-model memory reduction, architectural self-containedness, or representational fidelity, leaving the core tension unresolved. We propose FedSLM, a parameter-centric framework for federated fine-tuning with heterogeneous compressed clients. FedSLM uses SVD-based decomposition to produce self-contained client models, whose low-rank subspaces form nested manifolds that are structurally compatible for aggregation. It then applies a two-stage protocol that synchronizes lightweight adapters within compression groups and fuses full-rank reconstructions across groups via structural alignment. Finally, a weak-to-strong elicitation step with auxiliary confidence loss transfers the aggregated knowledge to the full-scale server, while an explicit bias--variance trade-off mitigates compression artifacts. We provide theoretical guarantees for adapter-level aggregation, subspace-alignment bounds for cross-group fusion, and a characterization of how the confidence loss mitigates weak-supervision noise. Experiments on natural language and vision--language benchmarks show that FedSLM outperforms existing federated baselines under both IID and non-IID partitions, while client models operate at roughly 50% of the GPU memory required by the full model. △ Less

Submitted 31 July, 2026; originally announced July 2026.

High-rate qLDPC processors

Authors: Aditya Bhardwaj, Muzhou Ma, Nadine Meister, Robbie King, Dolev Bluvstein, John Preskill, Madelyn Cain, Qian Xu, Hsin-Yuan Huang

Abstract: Despite significant progress on quantum low-density parity-check (qLDPC) codes, building qLDPC processors that are high-rate, high-throughput, hardware-friendly, and fast-to-decode remains a challenge. We introduce mitten codes, a family of qLDPC processor codes of encoding rate $20\%$ and check weight $9$, based on non-abelian groups. Their non-abelian structure evades distance bounds constrainin… ▽ More Despite significant progress on quantum low-density parity-check (qLDPC) codes, building qLDPC processors that are high-rate, high-throughput, hardware-friendly, and fast-to-decode remains a challenge. We introduce mitten codes, a family of qLDPC processor codes of encoding rate $20\%$ and check weight $9$, based on non-abelian groups. Their non-abelian structure evades distance bounds constraining abelian counterparts, allowing mitten codes to reach distance $18$ and beyond with just a few hundred data qubits. The logical operators of a mitten code are related by the group action, yielding a modular, low-overhead logical toolkit: full Clifford operations follow from bridging two reusable seed surgery gadgets or from a single fixed extractor. Furthermore, qLDPC processors based on mitten codes support high-rate surgery that executes many logical measurements in parallel, and parallel magic-state injection into all logical qubits at once. Under circuit-level noise, with our fast decoder, the $[\![300,60,14]\!]$ mitten code achieves, without extrapolation, a block logical error rate of ${\sim}10^{-11}$ per round at $0.1\%$ physical error rate (PER), while the $[\![ 975,195,\leq 24 ]\!]$ code reaches ${\sim}10^{-8}$ at $0.4\%$ PER. Decoding $15$ billion surgery experiments on the $[\![540,108,18]\!]$ code at $0.1\%$ PER, we observe only two logical failures, demonstrating a qLDPC processor capable of running ${\sim}10^{10}$ logical operations. Our decoder is compatible with sub-millisecond average latency per logical cycle, sufficient for real-time decoding on neutral atom hardware. Discovered by an end-to-end design pipeline built on sQetch, a distance estimator orders of magnitude faster than existing tools, and mapping efficiently onto near-term neutral atom and superconducting hardware, mitten codes open a practical path toward fault-tolerant quantum computation. △ Less

Submitted 30 July, 2026; originally announced July 2026.

Comments: 13 pages main text + 73 pages appendix; 13 figures

Can LLMs Really Understand Item Difficulty Levels? Implications for Automated Item Generation Using LLMs

Authors: Xinyi Wang, Hong Jiao, Ming Li, Sydney Peters, Hanna Choi, Tianyi Zhou, Qingshu Xu

Abstract: The estimation of item difficulty plays a key role in both formative assessment and large-scale high-stakes summative assessments. This study explores how large language models (LLMs) perform in predicting item difficulty levels using items from a large-scale Reading and Writing test. The study investigated various prompting strategies and parameter settings across multiple LLMs. LLM performance w… ▽ More The estimation of item difficulty plays a key role in both formative assessment and large-scale high-stakes summative assessments. This study explores how large language models (LLMs) perform in predicting item difficulty levels using items from a large-scale Reading and Writing test. The study investigated various prompting strategies and parameter settings across multiple LLMs. LLM performance was compared with encoder-only language models and feature-based supervised machine learning models. Zero-shot GPT-4.1 with a temperature of 0 yielded the highest item difficulty level prediction accuracy, with a quadratic weighted kappa (QWK) of 0.578. However, LLMs' prediction accuracy was lower than that of ConvBERT (QWK = 0.625), which outperformed the best feature-based supervised machine learning model. Further analysis showed that all LLMs struggled to label hard items; in particular, the current advanced GPT-5.4 tended to underestimate item difficulty levels. Dimension reduction of embeddings showed that item embeddings from different difficulty levels were mixed together, indicating that semantic information from items alone is likely insufficient for item difficulty level prediction. The findings suggest that if LLMs cannot understand item difficulty levels as evidenced by empirical data and tend to treat most items as easy when their own capabilities increase, caution should be exercised when using LLMs to generate items with targeted difficulty levels. △ Less

Submitted 17 May, 2026; originally announced July 2026.

Comments: 43 pages, 4 figures

Logical computation with canonical lifted product codes

Authors: Han Zheng, Guo Zheng, Liang Jiang, Qian Xu

Abstract: High-rate quantum low-density parity-check (qLDPC) codes encode many logical qubits with low physical-qubit overhead, but realizing efficient fault-tolerant computation on such dense encodings remains a major challenge. Generic, code-agnostic techniques such as code surgery and gate teleportation apply broadly, but are difficult to make modular, low-overhead, and fully certifiable on complex high-… ▽ More High-rate quantum low-density parity-check (qLDPC) codes encode many logical qubits with low physical-qubit overhead, but realizing efficient fault-tolerant computation on such dense encodings remains a major challenge. Generic, code-agnostic techniques such as code surgery and gate teleportation apply broadly, but are difficult to make modular, low-overhead, and fully certifiable on complex high-rate codes whose structure is left unexploited. Here we overcome these obstacles by co-designing the code together with its logical instruction set for a broad family of \emph{canonical} lifted-product (LP) codes with cyclic symmetry. We show that these codes admit a \emph{canonical logical basis}, in which conjugate logical operators are organized into rows and columns of cyclic orbits inherited directly from the underlying classical codes, analogous to the structure that makes hypergraph-product codes so tractable. This canonical basis unlocks a complete logical instruction set, including constant-depth automorphism and fold-transversal Clifford gates, modular graph code surgeries built from a constant number of reusable seed surgery gadgets or a compact canonical extractor, highly parallel logical Pauli-product measurements, and parallel magic-state injection. For example, a $[[1122,148,\leq\!20]]$ (resp. $[[4350,1224,\leq\!20]]$) LP code requires only two (resp. four) seed surgery gadgets, while arbitrary high-weight logical measurements can be implemented using a full extractor smaller than half of the data code block. These results advance the frontier of fault-tolerant quantum computation on ultra-high-rate quantum architectures. △ Less

Submitted 30 July, 2026; originally announced July 2026.

Comments: 4 Figures and 5 tables, 22 page + 40 page appendix

Dual Enhancement of Superconductivity in FeSe/SrTiO3 via Orbital and Correlation Synergy

Authors: Guihao Jia, Jingming Yan, Yucong Peng, Shendong Su, Pei Ouyang, Xiaopeng Hu, Qi-Kun Xue, Wei Li

Abstract: In iron-based superconductors, the dz2 orbital band typically resides far below the Fermi level and has not been considered to participate in Cooper pairing. Here, using monolayer FeSe/SrTiO3 as a model system, we demonstrate that tip-induced tensile strain controllably shifts the dz2 band toward the Fermi level, driving a two-stage enhancement of superconductivity. In-plane lattice expansion firs… ▽ More In iron-based superconductors, the dz2 orbital band typically resides far below the Fermi level and has not been considered to participate in Cooper pairing. Here, using monolayer FeSe/SrTiO3 as a model system, we demonstrate that tip-induced tensile strain controllably shifts the dz2 band toward the Fermi level, driving a two-stage enhancement of superconductivity. In-plane lattice expansion first enhances electronic correlation, amplifying superconductivity in the initial stage. As strain further increases, the upward-shifted dz2 band hybridizes with the dxy band, reconstructing the pairing-active d-orbital bands and inducing a secondary, stronger gap enhancement. Collectively, these two stages enlarge the superconducting gap from 17.8 to 23.6 meV. Throughout this process, invariant Fermi wave vectors confirm that the enhancement originates from band renormalization and reconstruction rather than carrier doping. Our work establishes a route to tailor superconducting states via strain-activated electronic correlations and band engineering, and reveals a previously unrecognized orbital-selective pairing mechanism with broad implications for correlated multiband superconductors. △ Less

Submitted 29 July, 2026; originally announced July 2026.

Comments: 17 pages, 4 figures

Journal ref: Proc. Natl. Acad. Sci. U.S.A. 123, e2602209123 (2026)

Multi-Asset Liquidation in Dark Pools with Adverse Selection

Authors: Guanxing Fu, Johannes Ruf, Xiaomin Shi, Zuo Quan Xu

Abstract: We study the optimal liquidation of a multi-asset portfolio using both a traditional exchange and dark pools in the presence of quadratic adverse-selection costs. The problem leads to a matrix-valued backward stochastic differential equation with jumps and a singular terminal condition. We establish existence and uniqueness of its solution and use it to characterize the value function and the opti… ▽ More We study the optimal liquidation of a multi-asset portfolio using both a traditional exchange and dark pools in the presence of quadratic adverse-selection costs. The problem leads to a matrix-valued backward stochastic differential equation with jumps and a singular terminal condition. We establish existence and uniqueness of its solution and use it to characterize the value function and the optimal liquidation strategy. The uniqueness result is the main mathematical contribution and strengthens the existing theory even in simpler special cases; the existence result is also new. For a two-asset model, we distinguish the roles of asset correlation, own-asset adverse selection, and cross-asset spillover in adverse-selection costs. Under diagonal temporary impact and in the absence of cross-asset spillover, an initially well-diversified portfolio remains well diversified during optimal liquidation and, for a fixed sign of the correlation, its liquidation cost is strictly decreasing in the magnitude of the correlation. By contrast, under the same diagonal-impact specification, under explicit conditions and sufficiently close to the liquidation horizon, cross-asset spillover makes a well-diversified portfolio more costly to liquidate than its poorly diversified sign-reversed counterpart and causes sufficiently unbalanced well-diversified portfolios to become poorly diversified with positive probability. Separately, without requiring diagonal temporary impact, we show that, in the absence of cross-asset spillover, own-asset adverse selection introduces an explicit shrinkage factor in the optimal dark-pool order relative to the order minimizing the post-execution continuation value. Finally, we derive an explicit condition under which a dark-pool execution transforms a poorly diversified portfolio into a well-diversified one. △ Less

Submitted 10 August, 2026; v1 submitted 29 July, 2026; originally announced July 2026.

Comments: 39 pages

Model-Free Q-Learning for Infinite-Horizon Stochastic Linear Quadratic Problems with Regime Switching

Authors: Xinyue Zhang, Na Li, Xun Li, Zuo Quan Xu

Abstract: This paper addresses infinite-horizon continuous-time stochastic linear quadratic optimal control problems with regime switching. We propose a paradigm shift from model-based design by adopting an adaptive dynamic programming approach, specifically developing on-policy and off-policy Q-learning algorithms that learn the optimal controller solely from online state trajectory data. The theoretical c… ▽ More This paper addresses infinite-horizon continuous-time stochastic linear quadratic optimal control problems with regime switching. We propose a paradigm shift from model-based design by adopting an adaptive dynamic programming approach, specifically developing on-policy and off-policy Q-learning algorithms that learn the optimal controller solely from online state trajectory data. The theoretical core of our work consists of a complete proof of the equivalence between the on- and off-policy architectures, alongside a rigorous analysis establishing the stability of the closed-loop system and the convergence of the algorithms to the optimal solution. For computational tractability, we implement these algorithms using vectorization and Kronecker product algebra. The theoretical results are corroborated by numerical case studies that clearly demonstrate the operational effectiveness and practical feasibility of the proposed model-free control strategy. △ Less

Submitted 29 July, 2026; originally announced July 2026.

Comments: 21 pages, 1 figure

Distilling Temporal Search and Reasoning: Evolving LLMs for Future Prediction via Harness-Assisted Efficient Data Synthesis

Authors: Wanxu Cai, Zhengyu Chen, Huaisheng Zhu, Wei Wang, Jingang Wang, Qiang Xu

Abstract: Future event prediction carries broad social impact yet remains challenging. SOTA approaches augment LLMs with external agent frameworks whose predictive capability vanishes once the harness is removed. While recent Tool-Integrated Reasoning (TIR) internalizes deep search for multi-hop retrieval of facts, forecasting further demands temporal search and reasoning over historical trends and dynamic… ▽ More Future event prediction carries broad social impact yet remains challenging. SOTA approaches augment LLMs with external agent frameworks whose predictive capability vanishes once the harness is removed. While recent Tool-Integrated Reasoning (TIR) internalizes deep search for multi-hop retrieval of facts, forecasting further demands temporal search and reasoning over historical trends and dynamic shifts. The key obstacle is data: historical queries induce temporal leakage that degrades forecasting into retrieval. Prior works either freeze information gathering with static observations, or rely on rejection sampling or unresolved fresh queries that discard vast amounts of data, degrading synthesis efficiency. We propose a time-truncation harness that enforces a temporal cut-off at every turn, enabling TIR-style sampling from historical events, reducing temporal leakage and reliance of rejection sampling or unsolved queries, increasing the sampling efficiency. We further build a large-scale corpus and a process-based metric and show that our harness naturally induces a broader temporal breadth of search and raises the proportion of high-quality data, further increasing the efficiency and reducing the reliance on complex rubrics. Distillation experiments show that students trained on harness-intervened data achieve the best performance, demonstrating harness-assisted model evolving that turns higher quality temporal search and reasoning data into a parametric advancement of the students. △ Less

Submitted 28 July, 2026; originally announced July 2026.

Tip-Tuned Renormalization-Group Spectroscopy Unmasks a False-positive Topological Superconducting Vortex

Authors: Zhenhua Zhu, Qun Zhu, Yong-Wei Wang, Gu Zhang, Jihai Zhang, Xu-Cun Ma, Qi-Kun Xue, Can-Li Song, Dong E. Liu

Abstract: Clean, nonsplit vortex zero-bias peaks (ZBPs) can be misinterpreted as Majorana zero modes (MZMs), making static scanning tunneling microscopy intrinsically ambiguous. Here we use the STM tip coupling to drive a local boundary-renormalization-group (boundary RG) flow, turning dynamical Coulomb blockade into a falsification test for Majorana-like ZBPs. Experimentally, in a $\mathrm{SrSn}_3$ thin fi… ▽ More Clean, nonsplit vortex zero-bias peaks (ZBPs) can be misinterpreted as Majorana zero modes (MZMs), making static scanning tunneling microscopy intrinsically ambiguous. Here we use the STM tip coupling to drive a local boundary-renormalization-group (boundary RG) flow, turning dynamical Coulomb blockade into a falsification test for Majorana-like ZBPs. Experimentally, in a $\mathrm{SrSn}_3$ thin film, normal-state spectra establish an Ohmic dissipative environment, and a common boundary-RG/thermodynamic-Bethe-ansatz analysis of the superconducting-gap and vortex-center spectra yields consistent dissipation strengths within the $r < 1/2$ Majorana-filter regime. Lowering the tip nevertheless drives a clean, non-split vortex-center ZBP into a zero-bias dip, opposite to the protected flow of an isolated MZM, unmasking the peak as a Majorana false positive produced by a conventional vortex-core state. The same flow selectively suppresses the strongly tip-coupled channel, resolving the two-gap superconductivity. Dissipative STM thus tests dynamical protection rather than spectral appearance. △ Less

Submitted 28 July, 2026; originally announced July 2026.

Comments: 13 pages, 6 figures

Organizing Principles for Moiré Quantum Matter

Authors: Qiaoling Xu, Yifan Gao, Tao Zhang, Ammon Fischer, Yi Jiang, Hanqi Pi, Zike Fan, Dongdong An, Kun Zhou, Yingjian Li, Yongqing Li, Yuhao Fu, Lei Wang, Lijun Zhang, B. Andrei Bernevig, Dante M. Kennes, Enge Wang, Angel Rubio, Lede Xian

Abstract: Moiré flat bands in van der Waals bilayers are usually discussed through a small set of mechanisms associated with the $Γ$ and $K$ valleys of hexagonal crystals, and more recently with $M$-valleys systems. Here we show that this view is incomplete. The momentum-space location and effective local orbital character of the monolayer's band edge, in conjunction with the moiré symmetry and the symmetry… ▽ More Moiré flat bands in van der Waals bilayers are usually discussed through a small set of mechanisms associated with the $Γ$ and $K$ valleys of hexagonal crystals, and more recently with $M$-valleys systems. Here we show that this view is incomplete. The momentum-space location and effective local orbital character of the monolayer's band edge, in conjunction with the moiré symmetry and the symmetry representations of the resulting bands, provide a general set of organizing variables for the emergent low-energy moiré Hamiltonian. Applying fully relaxed first-principles calculations, band unfolding and symmetry-representation analysis to more than 600 commensurate twisted bilayers spanning all 2D lattice classes, we identify several routes to moiré quantum matter beyond the conventional single-orbital paradigm. The resulting flat bands realize trigonal, honeycomb, square, checkerboard and kagome-like Hubbard models with single-orbital, multi-orbital and multi-site Hilbert spaces; spin-orbit-coupled multi-orbital flat bands exhibit symmetry-indicated topology beyond the conventional $K$-valley setting; and nonsymmorphic moiré symmetries enforce semimetallic flat-band connectivity. Analogous quasi-one-dimensional flat-band structures are found in $M$-valley hexagonal systems and $X$-valley square or rectangular systems resulting from emergent momentum-space nonsymmorphic symmetries. Separately, coupled multi-valley manifolds with kagome-like connectivity are identified in several systems whose parent band edges lie at non-high-symmetry points. These results establish a valley-orbital-symmetry framework for connecting parent-material electronic structure to emergent moiré Hamiltonians relevant to correlated, topological and symmetry-enforced moiré phases. △ Less

Submitted 27 July, 2026; originally announced July 2026.

Comments: 20 pages, 5 figures

Kimi K3: Open Frontier Intelligence

Authors: Kimi Team, Tongtong Bai, Yifan Bai, Yiping Bao, M. C., Jianfeng Cai, Xinyuan Cai, Peizhou Cao, Yuxuan Cao, Ziwei Chai, Y. Charles, H. S. Che, Guanduo Chen, Guangyu Chen, Guanzheng Chen, Huarong Chen, Jia Chen, Jianlong Chen, Jun Chen, Kexin Chen, Peng Chen, Ruijue Chen, Wentao Chen, Xin Chen, Yang Chen , et al. (377 additional authors not shown)

Abstract: We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is built on Kimi Delta Attention and Attention Residuals, which improve information flow across sequence length and model depth. Together with Stable LatentMoE, which effectively activates 16 of 896 routed experts per token… ▽ More We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is built on Kimi Delta Attention and Attention Residuals, which improve information flow across sequence length and model depth. Together with Stable LatentMoE, which effectively activates 16 of 896 routed experts per token, and refined training and data recipes, these advances yield an approximately 2.5x improvement in overall scaling efficiency over Kimi K2. Post-training highlights reinforcement learning across general, agentic, and coding domains and multiple reasoning-effort levels, enabling compositional generalization and robust long-horizon execution. At 2.8T scale, Kimi K3 is supported by infrastructure advances in multiple areas: algorithm-system co-design for KDA, perfectly balanced expert-parallel training with efficient memory management, million-token agentic RL with persistent rollout and sandbox states, and deployment innovations. Extensive evaluations show that Kimi K3 achieves frontier-level performance across long-horizon coding, agentic, knowledge, reasoning, and vision tasks. While its overall performance still trails the most powerful proprietary models, namely Claude Fable 5 and GPT-5.6 Sol, Kimi K3 consistently outperforms other open and proprietary models evaluated in our suite. We release the full Kimi K3 model weights to facilitate future research and accelerate the broader deployment and adoption of frontier intelligence. △ Less

Submitted 7 August, 2026; v1 submitted 27 July, 2026; originally announced July 2026.

Comments: K3 tech report

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

PathScale-R1: Cross-scale Reasoning for Pathological Image Analysis

Authors: Chi Phan, Tianyi Zhang, Yufeng Wu, Qiaochu Xue, Jiajie Zhang, Linghan Cai, Zeyu Liu, Sudong Wang, Yueming Jin, Dan Hu

Abstract: Pathological diagnosis is inherently multi-scale, requiring the integration of global tissue architecture at low magnification with cellular morphology at higher magnification. However, existing pathology benchmarks and vision-language models (VLMs) are still largely developed under single-scale settings, limiting their ability to learn clinically meaningful multi-magnification reasoning. Moreover… ▽ More Pathological diagnosis is inherently multi-scale, requiring the integration of global tissue architecture at low magnification with cellular morphology at higher magnification. However, existing pathology benchmarks and vision-language models (VLMs) are still largely developed under single-scale settings, limiting their ability to learn clinically meaningful multi-magnification reasoning. Moreover, naively constructed visual question answering (VQA) tasks may be susceptible to text-only or superficial visual shortcuts, leading to unreliable assessments of visual understanding. To address these limitations, we introduce a benchmark and training framework for shortcut-resistant cross-scale pathology reasoning. We design an Adversarial Text-only Screening strategy for semantic reasoning questions and a Structure-controlled Distractor Sampling strategy for visual grounding questions, encouraging models to rely on cross-scale visual evidence. Based on this pipeline, we construct PathScale-VQA, a high-quality cross-scale pathology VQA benchmark with 10,373 multiple-choice questions grounded in 1,368 diagnostic paths across multiple magnification levels. Building on the semantic reasoning set, PathScale-R1 is optimized through Difficulty-driven Reasoning Distillation supervised fine-tuning followed by reinforcement learning with a Scale-aware Reasoning Structure reward, which encourages the use of evidence across magnifications. Extensive experiments demonstrate state-of-the-art performance of PathScale-R1 on cross-scale reasoning tasks and effective transfer to conventional single-scale pathology VQA. Our code is available at https://github.com/iMVR-PL/PathScale-R1. △ Less

Submitted 26 July, 2026; originally announced July 2026.

Do Language Models Converge to Themselves? Recursive Self-Refinement as Textual Relaxation

Authors: Xuening Wu, Qianya Xu, Yanlan Kang, Zeping Chen, Yubin Liu, Shenqin Yin

Abstract: Large language models are increasingly used in recursive refinement workflows, where an initial draft is repeatedly revised by the same model. Despite their growing use, the long-term dynamics of such workflows remain poorly understood. Does repeated refinement continue to improve outputs indefinitely, or does it converge toward a stable textual form? We study recursive self-refinement as a dyna… ▽ More Large language models are increasingly used in recursive refinement workflows, where an initial draft is repeatedly revised by the same model. Despite their growing use, the long-term dynamics of such workflows remain poorly understood. Does repeated refinement continue to improve outputs indefinitely, or does it converge toward a stable textual form? We study recursive self-refinement as a dynamical process in which repeated LLM revision drives text toward a model-preferred soft fixed-point region. Using GPT-5.5, we generate 10-step refinement trajectories for 50 ICML 2025 abstracts under both default-temperature and deterministic decoding, and additionally evaluate 15 ICML 2020 abstracts. We analyze normalized edit distance, exact and approximate fixed points, word-count stability, exponential relaxation, and external LLM-as-a-judge evaluation. Across all settings, refinement trajectories rapidly saturate. Most edits occur within the first few iterations, after which trajectories enter a soft fixed-point region with only minor surface-level changes. Deterministic decoding reaches exact fixed points earlier and exhibits smaller residual fluctuations than default-temperature decoding, while both achieve universal approximate convergence. The average edit magnitude follows a consistent exponential relaxation pattern, suggesting convergence toward a model-preferred textual equilibrium rather than open-ended optimization. External evaluation indicates that converged abstracts improve clarity, conciseness, and scientific style while preserving technical meaning. These findings support a dynamical-systems view of LLM self-refinement and motivate practical stopping criteria based on edit-magnitude saturation. △ Less

Submitted 26 June, 2026; originally announced July 2026.

DRP-FLR: Data-Driven Assessment of Demand Response Potential for Flexible Load Regulation in Smart Grids

Authors: Yunhao Yao, Siyu Jing, Yang Yang, Qiang Xu, Changqi Weng, Xiang-Yang Li

Abstract: The rapid growth of AI workloads and renewable energy resources exacerbates supply-demand imbalance in power systems, making traditional load regulation designed for efficient allocation inadequate and motivating demand response (DR) mechanisms to enable load controllability in smart grids. However, existing DR-oriented approaches either focus on optimizing electricity cost or occupant comfort wit… ▽ More The rapid growth of AI workloads and renewable energy resources exacerbates supply-demand imbalance in power systems, making traditional load regulation designed for efficient allocation inadequate and motivating demand response (DR) mechanisms to enable load controllability in smart grids. However, existing DR-oriented approaches either focus on optimizing electricity cost or occupant comfort with limited benefit to system-level balance. Others overlook the diverse and dynamic consumption patterns of heterogeneous energy entities, leading to significant over- or under-regulation. Therefore, we propose DRP-FLR. First, DRP-FLR achieves accurate short-term load forecasting by embedding exogenous knowledge (e.g., entity information, prediction time) into historical load representations. Next, it constructs entity-specific load-pattern profiles by clustering historical load curves, and estimates DR potential by matching forecasted loads with pattern profiles. Finally, DRP-FLR formulates flexible load regulation as a mixed-integer optimization problem and solves it with an MILP solver to jointly optimize DR utilization, participant economic benefit, and renewable accommodation, while enforcing supply-demand balance and economic feasibility. Experiments on a regional grid and a campus microgrid show that DRP-FLR reduces regulation deviation by 36.63%-91.87% and improves participant benefit by 44.66% on average. △ Less

Submitted 10 June, 2026; originally announced July 2026.

Comments: 10 pages, 6 pages

ACM Class: I.2.1; I.5.3; G.1.6

Measurement of Born Cross Section for $e^+e^-\to K_S^0\barΞ^+Σ^-+\rm{c.c.}$ at $\sqrt{s} = 3.51-4.95$ GeV

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, 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, I. Boyko , et al. (737 additional authors not shown)

Abstract: Using $e^+e^-$ collision data collected with the BESIII detector at the BEPCII collider corresponding to a total integrated luminosity of 44~fb$^{-1}$, we present the first measurement of the Born cross sections for the process $e^+e^-\to K_S^0\barΞ^+Σ^-+\rm{c.c.}$ at 56 center-of-mass energies from 3.510 to 4.951~GeV. By fitting the dressed cross sections of $e^+e^-\to K_S^0\barΞ^+Σ^-+\rm{c.c.}$… ▽ More Using $e^+e^-$ collision data collected with the BESIII detector at the BEPCII collider corresponding to a total integrated luminosity of 44~fb$^{-1}$, we present the first measurement of the Born cross sections for the process $e^+e^-\to K_S^0\barΞ^+Σ^-+\rm{c.c.}$ at 56 center-of-mass energies from 3.510 to 4.951~GeV. By fitting the dressed cross sections of $e^+e^-\to K_S^0\barΞ^+Σ^-+\rm{c.c.}$ with the assumption of a power-law function plus a charmonium(-like) resonance, i.e. $ψ(3770)$, $ψ(4040)$, $ψ(4160)$, $Y(4230)$, $Y(4360)$, $ψ(4415)$, {\it Y}(4500), $Y(4660)$, and {\it Y}(4710), no significant signal of any charmonium(-like) state decaying into the $K_S^0\barΞ^+Σ^-+\rm{c.c.}$ is observed. Upper limits on the product of the electronic width and branching fraction at the 90\% confidence level are given for each resonance. Combining this result with the previous measurement of the isospin-symmetric process $e^+e^-\to K^{-} \barΞ^{+} Σ^{0} + \rm{c.c.}$, the ratio of the Born cross sections, $R=σ^{B}(e^+e^-\to K_S^0\barΞ^+Σ^-+\rm{c.c.})/$$σ^{B}(e^+e^-\to K^-\barΞ^+Σ^0+\rm{c.c.})$, is found to be approximately 1. △ Less

Submitted 24 July, 2026; originally announced July 2026.

Comments: 11 Pages, 3 Figures, 1 Appendix, etc

On structured cosine sums and applications

Authors: Qin Xue

Abstract: For a multiset $S$ on the cyclic group $\mathbb{Z}/N\mathbb{Z}$, we study finite sums of cosine functions of rational angles associated to $S$ by translating them as evaluations of elements in the group ring $\mathbb{Z}[\mathbb{Z}/N\mathbb{Z}]$. Using vanishing sums of roots of unity, especially the Lam-Leung theory, we obtain criteria for the vanishing of the cosine sums under some conditions, an… ▽ More For a multiset $S$ on the cyclic group $\mathbb{Z}/N\mathbb{Z}$, we study finite sums of cosine functions of rational angles associated to $S$ by translating them as evaluations of elements in the group ring $\mathbb{Z}[\mathbb{Z}/N\mathbb{Z}]$. Using vanishing sums of roots of unity, especially the Lam-Leung theory, we obtain criteria for the vanishing of the cosine sums under some conditions, and prove a small-weight Fourier rigidity. We then apply these algebraic results to cyclic Cayley graphs, deriving the zero-eigenvalue criteria, multiplicity bounds for nonzero eigenvalues in the small-support case, and a description of the square-free case where the generating set is a subgroup of the unit group. △ Less

Submitted 23 July, 2026; originally announced July 2026.

Comments: 32 pages

Probabilistic Residual Learning for Online Recommendations

Authors: Wenyuan Wang, Yusong Zhao, Zihao Xu, Hengyi Wang, Qi Xu, Zhigang Hua, Yan Xie, Yi Wang, Zihao Zhao, Bo Long, Chengzhi Mao, Shuang Yang, Hengguan Huang, Hao Wang

Abstract: Modern recommender systems are typically based on deep learning (DL) models, where a dense encoder learns representations of users and items. As a result, these systems often suffer from the black-box nature and computational complexity of the underlying models, making it difficult to systematically enhance their recommendation capabilities. To address this problem, we propose Probabilistic Residu… ▽ More Modern recommender systems are typically based on deep learning (DL) models, where a dense encoder learns representations of users and items. As a result, these systems often suffer from the black-box nature and computational complexity of the underlying models, making it difficult to systematically enhance their recommendation capabilities. To address this problem, we propose Probabilistic Residual Learning (PRL), a causal Bayesian recommendation model that models the residual between ground-truth and base predictions, enabling targeted refinement of existing systems. Specifically, PRL (1) probabilistically groups users for localized residual modeling, (2) models domain-level confounders that influence user and item representations, and (3) aggregates cluster-specific residual predictions over the confounders using do-calculus. Experiments demonstrate that our plug-and-play PRL is compatible with various base deep learning recommender systems, improving their performance while automatically discovering meaningful user clusters. △ Less

Submitted 22 July, 2026; originally announced July 2026.

Comments: Accepted at the 20th ACM Conference on Recommender Systems (RecSys 2026)

First Measurement of the Relative Phase between Proton Psionic Form Factors

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, Y. Bai, O. Bakina, Y. Ban, H. -R. Bao, X. L. Bao, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. B. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone, I. Boyko , et al. (732 additional authors not shown)

Abstract: The relative phase between the time-like form factors of the proton is a crucial observable for a complete understanding of its internal structure, yet it has remained unmeasured due to the formidable experimental challenge of determining the final-state polarization or having available polarized beams. With a novel technique that measures polarization via secondary scattering on spectrometer mate… ▽ More The relative phase between the time-like form factors of the proton is a crucial observable for a complete understanding of its internal structure, yet it has remained unmeasured due to the formidable experimental challenge of determining the final-state polarization or having available polarized beams. With a novel technique that measures polarization via secondary scattering on spectrometer material, we use $10.09\times10^{9}$ $J/ψ$ events collected at BESIII to analyze the reaction $e^+e^-\rightarrow J/ψ\rightarrow p\bar{p}$. This allows the first determination of the sine of the relative phase between the proton psionic form factors, $\sinΔΦ=-0.20\pm0.34_{\textrm{stat}}\pm0.11_{\textrm{syst}}$. This result provides the first direct insight into the complex dynamics of proton formation, and offers valuable new information to constrain theoretical models of nucleon structure. △ Less

Submitted 22 July, 2026; originally announced July 2026.

Comments: 4 pages, 6 figures

Proof of principle for nucleon polarization measurement at BESIII

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, Y. Bai, O. Bakina, Y. Ban, H. -R. Bao, X. L. Bao, V. Batozskaya, K. Begzsuren, N. Berger, M. Berlowski, M. B. Bertani, D. Bettoni, F. Bianchi, E. Bianco, A. Bortone, I. Boyko , et al. (732 additional authors not shown)

Abstract: A novel technique for measuring the spin polarization of final-state nucleons in a general-purpose spectrometer is validated. Using $10.09\times10^{9}$ $J/ψ$ events at BESIII, the asymmetry of polarized proton scattering on detector support material is measured, and is consistent with the expected value. This proves that a general-purpose spectrometer can be utilized as a large-acceptance polarime… ▽ More A novel technique for measuring the spin polarization of final-state nucleons in a general-purpose spectrometer is validated. Using $10.09\times10^{9}$ $J/ψ$ events at BESIII, the asymmetry of polarized proton scattering on detector support material is measured, and is consistent with the expected value. This proves that a general-purpose spectrometer can be utilized as a large-acceptance polarimeter, providing the spin polarization in addition to the conventional four-momentum information of the final-state particles. With this technique, physics capabilities are enhanced for existing and future facilities in particle and nuclear physics. △ Less

Submitted 22 July, 2026; originally announced July 2026.

Comments: 6 pages, 11 figures

PathAgentBench: Benchmarking Evidence-Seeking Vision-Language Models on Whole-Slide Pathology Image

Authors: Dankai Liao, Tianyi Zhang, Yufeng Wu, Xinyue Zhang, Qiaochu Xue, Zeyu Liu, Dachun Zhao, Linghan Cai, Yueming Jin

Abstract: Whole-slide image (WSI) diagnosis requires identifying diagnostically relevant regions, examining them across magnifications, and integrating multi-scale evidence. However, most existing pathology benchmarks evaluate models on pre-cropped patches or pre-extracted slide features, leaving their ability to acquire evidence directly from gigapixel WSIs largely untested. We introduce PathAgentBench, a… ▽ More Whole-slide image (WSI) diagnosis requires identifying diagnostically relevant regions, examining them across magnifications, and integrating multi-scale evidence. However, most existing pathology benchmarks evaluate models on pre-cropped patches or pre-extracted slide features, leaving their ability to acquire evidence directly from gigapixel WSIs largely untested. We introduce PathAgentBench, a benchmark for evaluating evidence-seeking vision-language models (VLMs) across four complementary capabilities: image-to-text matching for evidence interpretation, text-to-image retrieval for evidence verification, diagnostic-region localization for evidence acquisition, and multi-scale reasoning for evidence integration. The benchmark is organized as a diagnostic tree that links nested regions across magnifications with scale-specific findings and path-level diagnoses. It contains 1,822 TCGA WSIs and 17,135 diagnostic paths annotated by ten board-certified pathologists. An additional private cohort of 190 breast cancer WSIs with detailed annotations is used to evaluate autonomous whole-slide exploration. We evaluate 20 general-purpose, medical, and pathology-specialized models. Leading open-weight models achieve over 93% accuracy in multi-scale reasoning and over 50% accuracy in both cross-modal matching tasks. In contrast, diagnostic-region localization remains challenging: the best text-guided mean intersection-over-union is below 0.09, underperforming a simple center-based heuristic. During autonomous exploration, the unconditional hit rate decreases from 0.522 at low magnification to 0.185 at intermediate magnification and 0.020 at high magnification. These results reveal a pronounced gap between reasoning over curated evidence and acquiring that evidence directly from WSIs. PathAgentBench provides a unified framework for measuring and improving evidence-seeking pathology models. △ Less

Submitted 30 July, 2026; v1 submitted 21 July, 2026; originally announced July 2026.

(A)iSpy: Parasitic Trojans for Machine Learning Infrastructure

Authors: Habibur Rahaman, Qipan Xu, Zafaryab Haider, Prabuddha Chakraborty, Swarup Bhunia, Fnu Suya

Abstract: Modern machine learning (ML) pipelines depend heavily on third party libraries for graph compilation and hardware acceleration. While current practices audit data and model artifacts or rely on file integrity checks, the execution environment remains implicitly trusted. This blind spot enables active threats where a malicious runtime module interacts directly with live training and inference dynam… ▽ More Modern machine learning (ML) pipelines depend heavily on third party libraries for graph compilation and hardware acceleration. While current practices audit data and model artifacts or rely on file integrity checks, the execution environment remains implicitly trusted. This blind spot enables active threats where a malicious runtime module interacts directly with live training and inference dynamics: exploiting this interaction allows the Trojan to support complex objectives that are challenging for static code or binary modifications, achieving manipulations impossible for standard data and model level attacks. We expose this vulnerability by presenting (A)iSpy, a parasitic infrastructure Trojan that subverts ML systems through an active observe and execute paradigm. Operating within the computation graph, (A)iSpy monitors transient tensor states to perform targeted, stealthy manipulations with negligible overhead. To violate confidentiality, the Trojan identifies all critical training hyperparameters and covertly exfiltrates them via model weights or output logits. To break integrity, it acts as a gradient amplifier: by observing steganographic triggers, it transforms otherwise weak data poisoning into effective backdoor attacks, increasing success rates from near zero to 100%. We further demonstrate broad extensibility across the machine learning lifecycle by validating auxiliary attacks in the appendix, including subpopulation label flipping, availability disruptions, and inference stage manipulations. Importantly, the (A)iSpy module easily evades standard malware scanners, while the associated poisoned inputs and resulting compromised models bypass typical inspection tools. We demonstrate the practicality of this threat with an implementation in the ONNX Runtime training and inference engines. △ Less

Submitted 20 July, 2026; originally announced July 2026.

Endpoint Criteria for One-Dimensional Bilinear Rough Singular Integrals

Authors: Binwei Dan, Qingying Xue

Abstract: We prove endpoint theorems for one-dimensional bilinear rough singular integrals. Our starting point is a sharp structural characterization of the associated angular multiplier. For every mean-zero $Ω\in L^1(\mathbb{S}^1)$, the finite-part angular multiplier associated with $T_Ω$ has bounded variation if and only if the antipodal even part of $Ω$ belongs to $H^1(\mathbb{S}^1)$. This characterizati… ▽ More We prove endpoint theorems for one-dimensional bilinear rough singular integrals. Our starting point is a sharp structural characterization of the associated angular multiplier. For every mean-zero $Ω\in L^1(\mathbb{S}^1)$, the finite-part angular multiplier associated with $T_Ω$ has bounded variation if and only if the antipodal even part of $Ω$ belongs to $H^1(\mathbb{S}^1)$. This characterization identifies the precise rotational regularity required in the one-dimensional bilinear setting. It also yields a Stieltjes decomposition compatible with uniform estimates for the bilinear Hilbert transform. We then establish two boundedness criteria under critical kernel assumptions. First, if $Ω\in L\log L(\mathbb{S}^1)$, then $T_Ω$ is bounded from $ L^{p_1}(\mathbb{R})\times L^{p_2}(\mathbb{R})\text{to} L^p(\mathbb{R})$ whenever $1<p_1,p_2,p<\infty$ and $ \frac{1}{p}=\frac{1}{p_1}+\frac{1}{p_2}.$ Moreover, the logarithmic exponent $1$ is optimal within the scale $L(\log L)^A$. Second, at the critical directional index, the same boundedness holds for $Ω\in\mathcal{K}_{1/2,β}(\mathbb{S}^1)$, provided that $β>\frac{3}{2}\max\bigl\{p_1,p_1',p_2,p_2'\bigr\}-1.$The two critical kernel classes are incomparable. The $L\log L$ result is obtained by reducing the multiplier to a finite-part angular profile of bounded variation. The directional result follows from endpoint Fourier decay, product wavelet decompositions, and interpolation. △ Less

Submitted 19 July, 2026; originally announced July 2026.

Comments: 40 pages

MSC Class: 42B20