You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Sentinel-AI is a neuroscience-inspired transformer that dynamically prunes and regrows attention heads. Guided by controller feedback and entropy-based pruning, it self-optimizes through biologically informed cycles—compressing, adapting, and evolving its architecture over time.
Removing Attention Heads: Does the Energy Actually Drop or Do Remaining Heads Compensate? Dual-stream correlation of PyTorch timing hooks and epi-meter power traces on Pi 5 cluster.
Dropping MoE Experts and Measuring Energy Per Intelligence: Where Is the Efficient Operating Point? Expert pruning on Qwen3-30B-A3B measured by EPI on Pi 5 cluster.
Genetic algorithm framework for identifying strong lottery ticket networks in randomly initialized neural networks — features YAML-based configuration, works with any model architecture, and is easily extendable with new genetic operators.
<
10BC0
a href="/login?return_to=%2Fwish44165%2FOptimizing-Facial-Landmark-Estimation-for-Embedded-Systems" rel="nofollow" data-hydro-click="{"event_type":"authentication.click","payload":{"location_in_page":"star button","repository_id":752912136,"auth_type":"LOG_IN","originating_url":"https://github.com/topics/model-pruning?o=desc&s=updated","user_id":null}}" data-hydro-click-hmac="e3134e1be559e56bf19b828a6750ca4abf9bc8de37a0990b3b96e14ac74e8052" aria-label="You must be signed in to star a repository" data-view-component="true" class="tooltipped tooltipped-sw btn-sm btn color-bg-default">
Star
1
🔥 IEEE 2024 (Niagara Falls, Canada) - ICME Grand Challenges 🥈