2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2025★ 1 cited
Reasoning through Exploration: A Reinforcement Learning Framework for Robust Function Calling
Bingguang Hao, Zengzhuang Xu, Maolin Wang +9
The effective training of Large Language Models (LLMs) for function calling faces a critical challenge: balancing exploration of complex reasoning paths with stable policy optimiza…
cs.CL2024
What Affects the Stability of Tool Learning? An Empirical Study on the Robustness of Tool Learning Frameworks
Chengrui Huang, Zhengliang Shi, Yuntao Wen +4
Tool learning methods have enhanced the ability of large language models (LLMs) to interact with real-world applications. Many existing works fine-tune LLMs or design prompts to en…
cs.CL2024★ 2 cited
Simulating Financial Market via Large Language Model based Agents
Shen Gao, Yuntao Wen, Minghang Zhu +4
Most economic theories typically assume that financial market participants are fully rational individuals and use mathematical models to simulate human behavior in financial market…