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cs.CL2025
Understand User Opinions of Large Language Models via LLM-Powered In-the-Moment User Experience Interviews
Mengqiao Liu, Tevin Wang, Cassandra A. Cohen +2
Which large language model (LLM) is better? Every evaluation tells a story, but what do users really think about current LLMs? This paper presents CLUE, an LLM-powered interviewer…
cs.CL2024
RAGViz: Diagnose and Visualize Retrieval-Augmented Generation
Tevin Wang, Jingyuan He, Chenyan Xiong
Retrieval-augmented generation (RAG) combines knowledge from domain-specific sources into large language models to ground answer generation. Current RAG systems lack customizable v…