5 papers
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…
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…
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…
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…
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…