activity
20222026
most citedPersonality Traits in Large Language Models

26 citations · 48 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

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…

cs.LG2025★ 2 cited

Sleepless Nights, Sugary Days: Creating Synthetic Users with Health Conditions for Realistic Coaching Agent Interactions

Taedong Yun, Eric Yang, Mustafa Safdari +13

We present an end-to-end framework for generating synthetic users for evaluating interactive agents designed to encourage positive behavior changes, such as in health and lifestyle…

cs.LG2023★ 16 cited

A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis

Izzeddin Gur, Hiroki Furuta, Austin Huang +4

Pre-trained large language models (LLMs) have recently achieved better generalization and sample efficiency in autonomous web automation. However, the performance on real-world web…

cs.CL2023★ 26 cited

Personality Traits in Large Language Models

Greg Serapio-García, Mustafa Safdari, Clément Crepy +6

The advent of large language models (LLMs) has revolutionized natural language processing, enabling the generation of coherent and contextually relevant human-like text. As LLMs in…

cs.LG2022★ 4 cited

Understanding HTML with Large Language Models

Izzeddin Gur, Ofir Nachum, Yingjie Miao +6

Large language models (LLMs) have shown exceptional performance on a variety of natural language tasks. Yet, their capabilities for HTML understanding -- i.e., parsing the raw HTML…