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cs.AI2026
Self-Evaluating Recursive Agents
TianYi Lyu, Xiaozhe Li, Yang Li +7
Recursive language-model agents decompose tasks and delegate subtasks to child instances of the same policy, forming a tree of work. Training them, however, is hard: the final outc…
cs.AI2025
MorphoBench: A Benchmark with Difficulty Adaptive to Model Reasoning
Xukai Wang, Xuanbo Liu, Mingrui Chen +16
With the advancement of powerful large-scale reasoning models, effectively evaluating the reasoning capabilities of these models has become increasingly important. However, existin…
cs.AI2025
Learning What Reinforcement Learning Can't: Interleaved Online Fine-Tuning for Hardest Questions
Lu Ma, Hao Liang, Meiyi Qiang +9
Recent advances in large language model (LLM) reasoning have shown that sophisticated behaviors such as planning and self-reflection can emerge through reinforcement learning (RL).…