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cs.CL2026
Found in Conversation: LLMs Teach Themselves to Close the Multi-Turn Gap
Tianlang Chen, Shirley Wu, Jure Leskovec
Large Language Model (LLM) interactions are typically underspecified, with users clarifying all necessary details across multiple conversational turns. Yet recent work shows that L…
cs.CL2026
Reflections and New Directions for Human-Centered Large Language Models
Caleb Ziems, Dora Zhao, Rose E. Wang +55
Large Language Models (LLMs) are increasingly shaping the private and professional lives of users, with numerous applications in business, education, finance, healthcare, law, and…
cs.CL2026
HumanLM: Simulating Users with State Alignment Beats Response Imitation
Shirley Wu, Evelyn Choi, Arpandeep Khatua +7
Large Language Models (LLMs) are increasingly used to simulate how specific users respond to a given context, enabling more user-centric applications that rely on user feedback. Ho…