11 papers
Do AI Personas Grow? Analyzing and Benchmarking Personality Evolution in LLM Agents After Life Events
Ming Wang, Peidong Wang, Xiaocui Yang +4
Personality-conditioned LLM agents (PC-Agents) are increasingly used in emotional support, social simulation, and role-playing, motivating the development of lifelong agents that r…
MIThinker: A Plug-and-Play Policy-Optimized Thinker For Motivational Interviewing Counseling
Yizhe Yang, Palakorn Achananuparp, Heyan Huang +2
Reasoning large language models (LLMs) have recently made much progress in complex problem-solving, leveraging internal reasoning (or thought) to guide their solution generation. H…
VerifyMAS: Hypothesis Verification for Failure Attribution in LLM Multi-Agent Systems
Hezhe Qiao, Hanghang Tong, Ee-Peng Lim +2
Large language model-driven multi-agent systems (LLM-MAS) excel at complex tasks, yet unreliable agents remain a key bottleneck to system-level reliability. Automatic failure attri…
MHSafeEval: Role-Aware Interaction-Level Evaluation of Mental Health Safety in Large Language Models
Suhyun Lee, Palakorn Achananuparp, Neemesh Yadav +2
Large language models (LLMs) are increasingly explored as scalable tools for mental health counseling, yet evaluating their safety remains challenging due to the interactional and…
DialToM: A Theory of Mind Benchmark for Forecasting State-Driven Dialogue Trajectories
Neemesh Yadav, Palakorn Achananuparp, Jing Jiang +1
We introduce DialToM, an annotated Theory of Mind (ToM) benchmark built from naturalistic human-human dialogues using a multiple-choice evaluation framework. Concurrent with recent…
Leveraging Large Language Models for Career Mobility Analysis: A Study of Gender, Race, and Job Change Using U.S. Online Resume Profiles
Palakorn Achananuparp, Ye Xu, Yao Lu +2
We present a large-scale analysis of career mobility of college-educated U.S. workers using online resume profiles to investigate how gender, race, and job change options are assoc…
Effects of Theory of Mind and Prosocial Beliefs on Steering Human-Aligned Behaviors of LLMs in Ultimatum Games
Neemesh Yadav, Yihuai Lan, Shan Dong +4
Large Language Models (LLMs) have shown potential in simulating human behaviors and performing theory-of-mind (ToM) reasoning, crucial for complex social interactions. We investiga…
A Multi-Stage Framework with Taxonomy-Guided Reasoning for Occupation Classification Using Large Language Models
Palakorn Achananuparp, Ee-Peng Lim, Yao Lu
Automatically annotating job data with standardized occupations from taxonomies, known as occupation classification, is crucial for labor market analysis. However, this task is oft…
CAMI: A Counselor Agent Supporting Motivational Interviewing through State Inference and Topic Exploration
Yizhe Yang, Palakorn Achananuparp, Heyan Huang +5
Conversational counselor agents have become essential tools for addressing the rising demand for scalable and accessible mental health support. This paper introduces CAMI, a novel…
Consistent Client Simulation for Motivational Interviewing-based Counseling
Yizhe Yang, Palakorn Achananuparp, Heyan Huang +7
Simulating human clients in mental health counseling is crucial for training and evaluating counselors (both human or simulated) in a scalable manner. Nevertheless, past research o…
Speaker Verification in Agent-Generated Conversations
Yizhe Yang, Palakorn Achananuparp, Heyan Huang +2
The recent success of large language models (LLMs) has attracted widespread interest to develop role-playing conversational agents personalized to the characteristics and styles of…