11 citations · 33 across the 10 of their papers we have counts for
6 papers · 1 filter
Learning Evolving Tools for Large Language Models
Guoxin Chen, Zhong Zhang, Xin Cong +5
Tool learning enables large language models (LLMs) to interact with external tools and APIs, greatly expanding the application scope of LLMs. However, due to the dynamic nature of…
DiReCT: Diagnostic Reasoning for Clinical Notes via Large Language Models
Bowen Wang, Jiuyang Chang, Yiming Qian +6
Large language models (LLMs) have recently showcased remarkable capabilities, spanning a wide range of tasks and applications, including those in the medical domain. Models like GP…
Step-level Value Preference Optimization for Mathematical Reasoning
Guoxin Chen, Minpeng Liao, Chengxi Li +1
Direct Preference Optimization (DPO) using an implicit reward model has proven to be an effective alternative to reinforcement learning from human feedback (RLHF) for fine-tuning p…
AlphaMath Almost Zero: Process Supervision without Process
Guoxin Chen, Minpeng Liao, Chengxi Li +1
Although recent advancements in large language models (LLMs) have significantly improved their performance on various tasks, they still face challenges with complex and symbolic mu…
SEER: Facilitating Structured Reasoning and Explanation via Reinforcement Learning
Guoxin Chen, Kexin Tang, Chao Yang +3
Elucidating the reasoning process with structured explanations from question to answer is crucial, as it significantly enhances the interpretability, traceability, and trustworthin…
Skyline Community Search over Edge-Attributed Bipartite Graphs
Fangda Guo, Xuanpu Luo, Shiyuan Xu +4
Bipartite graphs, modeling relationships between two types of entities, are widely used in practical applications. Community search, a fundamental problem in bipartite graphs, has…