Shanghai AI Laboratory
Shanghai AI Laboratory on Hugging Face Daily Papers: 16 papers, 3 in the top 3 of their day, 2 paper of the day.
- Real2Gym: Building Gyms from Videos, Bringing Skills to Robots 6 upvotes, #65 of 2026-09-30
- InfiniHand: Streaming World-Space Hand Motion Estimation from Egocentric Video 9 upvotes, #50 of 2026-09-29
- AV-GRPO: Modality-Anchored Decoupling Diffusion Reinforcement Learning for Joint Audio-Video Generation 12 upvotes, #19 of 2026-09-25
- Rethinking Critic Learning in PPO: Understanding and Mitigating Value Flattening 79 upvotes, #2 of 2026-09-17
- NCP-ArchPreview Technical Report: Moving towards Latent Space Language Models through Next Concept Prediction 319 upvotes, #1 of 2026-09-11
- SWE-Bench Pro Verified: A Reliable Benchmark for Software Engineering Agents 14 upvotes, #15 of 2026-09-10
- InternReviewer & InternAdvocate: Objective Reward and Evaluation for Agentic Reinforcement Learning in Peer Review and Rebuttal 9 upvotes, #18 of 2026-09-02
- Safin-1: Safety from Within through Memory-Native State Evolution 20 upvotes, #12 of 2026-09-02
- MegaParts: Scaling Part-Aware 3D Object Generation to 300 Parts via Token-Efficient Autoregressive Modeling 19 upvotes, #16 of 2026-08-18
- Understanding Cognition-Induced Risks in Agentic AI Systems 17 upvotes, #18 of 2026-08-18
- SimpleOPD: Simple Tokenizer-Agnostic On-Policy Distillation for Long-Context Reasoning 34 upvotes, #5 of 2026-08-17
- An End-to-End Agent Auditing Engine 13 upvotes, #19 of 2026-08-11
- Quo Vadis, World Modeling? 37 upvotes, #8 of 2026-08-05
- SKT: Skill-Use Training at Scale via Verified Synthetic Data Generation 31 upvotes, #12 of 2026-08-04
- DAPD: Dual-Anchored Policy Distillation 108 upvotes, #4 of 2026-08-04
- Accurate, Interdisciplinary and Transparent Structure-property Understanding with Deep Native Structural Reasoning 85 upvotes, #1 of 2026-07-09
Data: hysts-bot-data/daily-papers-stats and the Daily Papers API. Open data: tardellirs/paper-pulse-data. Sister project: Model Pulse, the download history of every model on the Hub.