2 papers
cs.CL2025
Group Preference Alignment: Customized LLM Response Generation from In-Situ Conversations
Ishani Mondal, Jack W. Stokes, Sujay Kumar Jauhar +5
LLMs often fail to meet the specialized needs of distinct user groups due to their one-size-fits-all training paradigm \cite{lucy-etal-2024-one} and there is limited research on wh…
cs.CL2025
GenTool: Enhancing Tool Generalization in Language Models through Zero-to-One and Weak-to-Strong Simulation
Jie He, Jennifer Neville, Mengting Wan +6
Large Language Models (LLMs) can enhance their capabilities as AI assistants by integrating external tools, allowing them to access a wider range of information. While recent LLMs…