4 papers
From Experience to Strategy: Empowering LLM Agents with Trainable Graph Memory
Siyu Xia, Zekun Xu, Jiajun Chai +7
Large Language Models (LLMs) based agents have demonstrated remarkable potential in autonomous task-solving across complex, open-ended environments. A promising approach for improv…
MTIR-SQL: Multi-turn Tool-Integrated Reasoning Reinforcement Learning for Text-to-SQL
Zekun Xu, Siyu Xia, Chuhuai Yue +6
As large language models (LLMs) are increasingly used in Text-to-SQL tasks, Reinforcement Learning (RL) has become a common method for improving performance. Existing methods prima…
RLFactory: A Plug-and-Play Reinforcement Learning Post-Training Framework for LLM Multi-Turn Tool-Use
Jiajun Chai, Guojun Yin, Zekun Xu +9
Large language models excel at basic reasoning but struggle with tasks that require interaction with external tools. We present RLFactory, a plug-and-play reinforcement learning po…
Internal Chain-of-Thought: Empirical Evidence for Layer-wise Subtask Scheduling in LLMs
Zhipeng Yang, Junzhuo Li, Siyu Xia +1
We show that large language models (LLMs) exhibit an : they sequentially decompose and execute composite tasks layer-by-layer. Two claims ground…