Large language model agents increasingly undertake long-horizon tasks in complex environments characterized by fragmented evidence, partially completed states, and dependencies across resources and artifacts, and Interlock, a framework for task synthesis that represents each task as a typed completion graph is proposed...
Lin-Ji Hao, Yan-Ji He, Zi-Han Wang et al.· 0 citations
The rapid advancement of Large Language Models (LLMs) has driven their deployment toward general-purpose harness environments, where LLM-based agents operate in sandbox workspaces and interact directly with file systems and shells. While numerous post-training pipelines exist for tool-use agents, their counterparts for...
Han-Si Yang, Lin-Ji Hao, Hong-Yan Hao et al.· 0 citations
COPC is introduced, an actor--critic method combining token-level ratio masking with two-sided clipped-ratio weighting of TD residuals for return and advantage estimation that achieves the highest reported performance on tool-integrated mathematical reasoning and search, outperforming the strongest reported asynchronou...
Zi-Cheng Hu, Zhi-Jian Zhou, Xuan Zhang et al.· 0 citations
RSTG (Recovering Learning Signals via Adaptive Teacher Guidance), which applies distillation selectively and precisely where it matters most, and substantially outperforms naive GRPO+OPD.
Zhuo-Wen Han, Jinwei Xiao, Zhengxi Lu et al.· 4 citations
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