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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…
Conversational User-AI Intervention: A Study on Prompt Rewriting for Improved LLM Response Generation
Rupak Sarkar, Bahareh Sarrafzadeh, Nirupama Chandrasekaran +4
Human-LLM conversations are increasingly becoming more pervasive in peoples' professional and personal lives, yet many users still struggle to elicit helpful responses from LLM Cha…
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…