Crafter: A Multi-Agent Harness for Editable Scientific Figure Generation from Diverse Inputs Paper • 2605.30611 • Published 15 days ago • 192
Representation Forcing for Bottleneck-Free Unified Multimodal Models Paper • 2605.31604 • Published 14 days ago • 59
Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players Paper • 2605.28816 • Published 16 days ago • 423
From Raw Experience to Skill Consumption: A Systematic Study of Model-Generated Agent Skills Paper • 2605.23899 • Published 21 days ago • 29
Diversed Model Discovery via Structured Table Discovery Paper • 2605.22766 • Published 22 days ago • 6
Pseudo-Unification: Entropy Probing Reveals Divergent Information Patterns in Unified Multimodal Models Paper • 2604.10949 • Published Apr 13 • 40
How Well Do Agentic Skills Work in the Wild: Benchmarking LLM Skill Usage in Realistic Settings Paper • 2604.04323 • Published Apr 6 • 41
GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning Paper • 2604.02721 • Published Apr 3 • 632
When Models Judge Themselves: Unsupervised Self-Evolution for Multimodal Reasoning Paper • 2603.21289 • Published Mar 22 • 35
Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models Paper • 2603.25716 • Published Mar 26 • 156
ShotStream: Streaming Multi-Shot Video Generation for Interactive Storytelling Paper • 2603.25746 • Published Mar 26 • 155
MinerU-Diffusion: Rethinking Document OCR as Inverse Rendering via Diffusion Decoding Paper • 2603.22458 • Published Mar 23 • 137
Generation Models Know Space: Unleashing Implicit 3D Priors for Scene Understanding Paper • 2603.19235 • Published Mar 19 • 95
InCoder-32B: Code Foundation Model for Industrial Scenarios Paper • 2603.16790 • Published Mar 17 • 312
Bootstrapping Exploration with Group-Level Natural Language Feedback in Reinforcement Learning Paper • 2603.04597 • Published Mar 4 • 211
Code2Math: Can Your Code Agent Effectively Evolve Math Problems Through Exploration? Paper • 2603.03202 • Published Mar 3 • 18
From Blind Spots to Gains: Diagnostic-Driven Iterative Training for Large Multimodal Models Paper • 2602.22859 • Published Feb 26 • 150