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From the 1 of 11 linked papers with an AI index.

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20242026
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cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

cs.CL2025

AnnaAgent: Dynamic Evolution Agent System with Multi-Session Memory for Realistic Seeker Simulation

Ming Wang, Peidong Wang, Lin Wu +6

Constrained by the cost and ethical concerns of involving real seekers in AI-driven mental health, researchers develop LLM-based conversational agents (CAs) with tailored configura…

cs.CL2025

Language Models as Continuous Self-Evolving Data Engineers

Peidong Wang, Ming Wang, Zhiming Ma +5

Large Language Models (LLMs) have demonstrated remarkable capabilities on various tasks, while the further evolvement is limited to the lack of high-quality training data. In addit…

cs.CL2024

RoCar: A Relationship Network-based Evaluation Method for Large Language Models

Ming Wang, Wenfang Wu, Chongyun Gao +3

Large language models (LLMs) have received increasing attention. However, due to the complexity of its capabilities, how to rationally evaluate the capabilities of LLMs is still a…