4 papers · 1 filter
SAP: State-Guided Data Synthesis with Argument Provenance for Multi-Turn Tool Use
Zichen Tian, Jinpeng Chen, Cheng Gong +2
High-quality multi-turn tool-use data is essential for training agentic models, yet existing data synthesis methods often underrepresent the argument-level dependencies that are cr…
SoftSkill: Behavioral Compression for Contextual Adaptation
Xijia Tao, Yihua Teng, Xinyu Fu +6
Natural-language skills let agents reuse task knowledge, yet deploying a long Markdown document makes the model interpret that knowledge anew on every call. We ask whether the beha…
CoVe: Training Interactive Tool-Use Agents via Constraint-Guided Verification
Jinpeng Chen, Cheng Gong, Hanbo Li +9
Developing multi-turn interactive tool-use agents is challenging because real-world user needs are often complex and ambiguous, yet agents must execute deterministic actions to sat…
Efficient Reasoning via Reward Model
Yuhao Wang, Xiaopeng Li, Cheng Gong +4
Reinforcement learning with verifiable rewards (RLVR) has been shown to enhance the reasoning capabilities of large language models (LLMs), enabling the development of large reason…