2 citations · 2 across the 6 of their papers we have counts for
6 papers
Pretrained Persona Mixture Models and Tandem Models for Human Simulation
Minwoo Kang, Téa Wright, Seun Eisape +6
We argue here that the current dominant practice in LLM human simulation: prompting instruction-tuned assistant language models to role-play personas, is inaccurate and produces st…
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…
Identity, Cooperation and Framing Effects within Groups of Real and Simulated Humans
Suhong Moon, Minwoo Kang, Joseph Suh +2
Humans act via a nuanced process that depends both on rational deliberation and also on identity and contextual factors. In this work, we study how large language models (LLMs) can…
Graph-Based Alternatives to LLMs for Human Simulation
Joseph Suh, Suhong Moon, Serina Chang
Large language models (LLMs) have become a popular approach for simulating human behaviors, yet it remains unclear if LLMs are necessary for all simulation tasks. We study a broad…
DEMOTIC: A Differentiable Sampler for Multi-Level Digital Circuits
Arash Ardakani, Minwoo Kang, Kevin He +4
Efficient sampling of satisfying formulas for circuit satisfiability (CircuitSAT), a well-known NP-complete problem, is essential in modern front-end applications for thorough test…
Rediscovering the Latent Dimensions of Personality with Large Language Models as Trait Descriptors
Joseph Suh, Suhong Moon, Minwoo Kang +1
Assessing personality traits using large language models (LLMs) has emerged as an interesting and challenging area of research. While previous methods employ explicit questionnaire…