What Makes World Action Models Generalize? An Empirical Study of Test-Time Future Modeling Paper • 2609.34981 • Published 3 days ago • 116
Rethinking On-Policy Distillation of Large Language Models II: One Training Example Paper • 2609.04172 • Published 29 days ago • 104
Safin-1: Safety from Within through Memory-Native State Evolution Paper • 2609.00092 • Published Aug 31 • 21
Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering Paper • 2607.28568 • Published Jul 30 • 188
Qwen-AgentWorld: Language World Models for General Agents Paper • 2606.24597 • Published Jun 23 • 167
NatureBench: Can Coding Agents Match the Published SOTA of Nature-Family Papers? Paper • 2606.24530 • Published Jun 23 • 67
EnterpriseClawBench: Benchmarking Agents from Real Workplace Sessions Paper • 2606.23654 • Published Jun 22 • 81
Draft-OPD: On-Policy Distillation for Speculative Draft Models Paper • 2605.29343 • Published May 28 • 34
Post-Trained MoE Can Skip Half Experts via Self-Distillation Paper • 2605.18643 • Published May 18 • 31
Achieving Gold-Medal-Level Olympiad Reasoning via Simple and Unified Scaling Paper • 2605.13301 • Published May 13 • 166
Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe Paper • 2604.13016 • Published Apr 14 • 116
SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning Paper • 2509.09674 • Published Sep 11, 2025 • 82
Towards a Unified View of Large Language Model Post-Training Paper • 2509.04419 • Published Sep 4, 2025 • 77
The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models Paper • 2505.22617 • Published May 28, 2025 • 132
Technologies on Effectiveness and Efficiency: A Survey of State Spaces Models Paper • 2503.11224 • Published Mar 14, 2025 • 28