19 papers
From Scoring to Acting: Outcome-Verified Comparative Self-Distillation for LLM Agents
Xu Xia, Jinghua Piao, Min Yang +3
The paper introduces Outcome-Verified Comparative Self-Distillation (OVCSD), a method that lets large language model agents internalize skills by supervising them with teachers who…
AgentSociety 2: An Integrated Research Environment for Executable Social Science
Jinghua Piao, Jun Zhang, Haoyu Huang +16
AI scientist systems are beginning to automate parts of scientific research, but social science poses a distinct challenge: its objects of inquiry are not merely datasets or labora…
MiniCache: Reusable Program Caching with Small Model Interfaces for Efficient LLM Inference
Jingquan Chen, Jinghua Piao, Jie Feng +2
Large language models (LLMs) are increasingly used for program-aided reasoning, agentic decision making, and structured task execution, but these applications often incur high infe…
DyCon: Dynamic Reasoning Control via Evolving Difficulty Modeling
Tengyao Tu, Yulin Li, Hui-Ling Zhen +6
Recent advances in Large Reasoning Models (LRMs) demonstrate remarkable performance improvements by iteratively reflecting, exploring, and executing complex tasks, yet suffer from…
Multi-LLM Systems Exhibit Robust Semantic Collapse
Weiyi Kong, Shiyang Lai, Jinghua Piao +1
Whether machines can originate novel content has been debated for nearly two centuries, from Lovelace's assertion that no engine can "originate anything" to Turing's question of wh…
SkillMaster: Toward Autonomous Skill Mastery in LLM Agents
Min Yang, Jinghua Piao, Xu Xia +4
Skills provide an effective mechanism for improving LLM agents on complex tasks, yet in existing agent frameworks, their creation, refinement, and selection are typically governed…