3 citations · 3 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…
Anamnesis: An Open-Source Platform for Large-Scale Backstory-Conditioned Survey Simulation
Song-Ze Yu, Joseph Suh, Serina Chang +1
We present Anamnesis, an interactive system for demographically controllable survey simulation using large language models. Open-source and designed for non-technical users/researc…
PitchBench: Measuring Pitch Hearing in Audio-Language Models
Milan Liessens Dujardin, Song-Ze Yu, Craver Corbyn Thomas-Smith +2
Audio-language models (ALMs) are increasingly used in real-world applications that require understanding music, from music tutoring and transcription to captioning, recommendation…
Deep Binding of Language Model Virtual Personas: a Study on Approximating Political Partisan Misperceptions
Minwoo Kang, Suhong Moon, Seung Hyeong Lee +4
Large language models (LLMs) are increasingly capable of simulating human behavior, offering cost-effective ways to estimate user responses to various surveys and polls. However, t…
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…
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…