collaborators

8 papers

cs.CL2026

MicroVerse: An Instrument for Measuring Self-Authored Identity Drift in Long-Horizon Multi-Agent Language-Model Simulations

Sky Ng, Brihi Joshi, Ishan Gupta +47

Long-horizon, multi-agent language model (LM) simulations are widely proposed for studying social behavior, yet instruments to measure whether persona-conditioned agents maintain i…

cs.HC2026

PersonaEval: Persona-Based User Simulation for Evaluating Interactive Applications

Yifan Simon Liu, Qianfeng Wen, Yilan Fan +40

Real user studies are important for understanding how people interact with systems under test or already deployed. In practice, however, they are often costly, time-consuming, and…

cs.AI2026

MatrAIx: Simulating the World with 8.3 Billion Persona Agents

Xiaomin Li, Yuexing Hao, Jianheng Hou +90

Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract away human diversity and inter…

cs.CR2026

ASPI: Seeking Ambiguity Clarification Amplifies Prompt Injection Vulnerability in LLM Agents

Udari Madhushani Sehwag, Zhengyang Shan, Heming Liu +3

Clarification-seeking behavior is widely regarded as a desirable property of LLM agents, enabling them to resolve ambiguity before acting on underspecified tasks. However, the secu…

cs.AI2026

Do Self-Evolving Agents Forget? Capability Degradation and Preservation in Lifelong LLM Agent Adaptation

Ye Yu, Xiaopeng Yuan, Haibo Jin +3

Recent advances in LLM agents enable systems that autonomously refine workflows, accumulate reusable skills, self-train their underlying models, and maintain persistent memory. How…

cs.AI2026

Learning to Communicate: Toward End-to-End Optimization of Multi-Agent Language Systems

Ye Yu, Heming Liu, Haibo Jin +3

Multi-agent systems built on large language models have shown strong performance on complex reasoning tasks, yet most work focuses on agent roles and orchestration while treating i…

cs.CV2026

Entropy-Aware Structural Alignment for Zero-Shot Handwritten Chinese Character Recognition

Qiuming Luo, Tao Zeng, Feng Li +3

Zero-shot Handwritten Chinese Character Recognition (HCCR) aims to recognize unseen characters by leveraging radical-based semantic compositions. However, existing approaches often…

math.ST2024

Spectral Recovery in the Labeled SBM

Julia Gaudio, Heming Liu

We consider the problem of exact community recovery in the Labeled Stochastic Block Model (LSBM) with communities, where each pair of vertices is associated with a label from t…