10 papers
Can MLLMs Decode the Creative Leap? Introducing C4 for Cross-Concept Understanding
Ming Wang, Yuqing Zhang, Tingna Xie +5
Creative capabilities of MLLMs matter in design, communication, education, and human--AI collaboration, yet remain difficult to evaluate because explicit targets and reward signals…
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…
Beyond Feeling Better: Capability-Sustaining Emotional Dialogue as a Longitudinal Research Paradigm
Ming Wang, Jiaqi Wu Young, Wenfang Wu +2
The paper introduces capability‑sustaining emotional dialogue (CSED) as a longitudinal research paradigm that aims to support users' emotional regulation, coping, and autonomy over…
GenPT: Beyond Self-Report for Reliable LLM Psychometrics via Generative Projective Testing
Ming Wang, Shuang Wu, Bixuan Wang +7
Self-report questionnaires remain the prevailing tool for probing the psychological states of persona-conditioned agents (PC-Agents). However, classical instruments inherit two wel…
A Systematic Analysis of the Impact of Persona Steering on LLM Capabilities
Jiaqi Chen, Ming Wang, Tingna Xie +2
Imbuing Large Language Models (LLMs) with specific personas is prevalent for tailoring interaction styles, yet the impact on underlying cognitive capabilities remains unexplored. W…
T-COL: Generating Counterfactual Explanations for General User Preferences on Variable Machine Learning Systems
Ming Wang, Daling Wang, Wenfang Wu +2
To address the interpretability challenge in machine learning (ML) systems, counterfactual explanations (CEs) have emerged as a promising solution. CEs are unique as they provide w…