11 papers
INSIDE the Student's Mind: Jointly Modeling Latent Reasoning and Action in LLM Student Simulators
Rose Niousha, Minwoo Kang, Narges Norouzi
Large Language Model (LLM)-based simulators often reproduce observable actions but fail to capture the underlying reasoning behind them. In education, where student simulation is i…
Speculative Interaction Agents: Building Real-Time Agents with Asynchronous I/O and Speculative Tool Calling
Coleman Hooper, Minwoo Kang, Suhong Moon +7
There is a growing demand for agentic AI technologies for a range of downstream applications like customer service and personal assistants. For applications where the agent needs t…
Quantifying the Utility of User Simulators for Building Collaborative LLM Assistants
Joseph Suh, Ayush Raj, Minwoo Kang +1
User simulators are increasingly leveraged to build interactive AI assistants, yet how to measure the quality of these simulators remains an open question. In this work, we show ho…
Virtual Personas for Language Models via an Anthology of Backstories
Suhong Moon, Marwa Abdulhai, Minwoo Kang +5
Large language models (LLMs) are trained from vast repositories of text authored by millions of distinct authors, reflecting an enormous diversity of human traits. While these mode…
Dynamic In-Group Persona Generation for Enhancing Human-AI Rapport
Yoonseok Oh, Inseo Jung, Jinkyu Kim +3
LLM-based chatbots are increasingly applied in interpersonal domains such as counseling and peer support, where establishing human-AI rapport is crucial yet remains challenging. In…
Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions
Joseph Suh, Erfan Jahanparast, Suhong Moon +2
Large language models (LLMs) present novel opportunities in public opinion research by predicting survey responses in advance during the early stages of survey design. Prior method…