T1: Terminal Agent Reinforcement Learning for Long-Horizon Tasks Paper • 2609.11042 • Published 18 days ago • 63
Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering Paper • 2607.28568 • Published Jul 30 • 188
NatureBench: Can Coding Agents Match the Published SOTA of Nature-Family Papers? Paper • 2606.24530 • Published Jun 23 • 67
Qwen-AgentWorld: Language World Models for General Agents Paper • 2606.24597 • Published Jun 23 • 165
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
Rethinking On-Policy Distillation of Large Language Models: Phenomenology, Mechanism, and Recipe Paper • 2604.13016 • Published Apr 14 • 116
Think-at-Hard: Selective Latent Iterations to Improve Reasoning Language Models Paper • 2511.08577 • Published Nov 11, 2025 • 110
Scaling Latent Reasoning via Looped Language Models Paper • 2510.25741 • Published Oct 29, 2025 • 236
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
UltraIF: Advancing Instruction Following from the Wild Paper • 2502.04153 • Published Feb 6, 2025 • 23