10 papers · 1 filter
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…
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…
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…
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…