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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.AI2026

Automating SKILL.md Generation for Computer-Using Agents via Interaction Trajectory Mining

Yuexing Hao, Xiaomin Li

Explicit skill libraries make computer-using agents easier to inspect, but it remains unclear whether such libraries can be mined from interaction data in a way that improves downs…

cs.AI2026

DataDignity: Training Data Attribution for Large Language Models

Xiaomin Li, Andrzej Banburski-Fahey, Jaron Lanier

Auditing language-model outputs often requires more than judging correctness: an auditor may need to identify which source document most likely supports the knowledge expressed in…

cs.AI2026

Chain of Risk: Safety Failures in Large Reasoning Models and Mitigation via Adaptive Multi-Principle Steering

Xiaomin Li, Jianheng Hou, Zheyuan Deng +6

Large reasoning models (LRMs) increasingly expose chain-of-thought-like reasoning for transparency, verification, and deliberate problem solving. This creates a safety blind spot:…

cs.AI2026

Multiplayer Nash Preference Optimization

Fang Wu, Xu Huang, Weihao Xuan +8

Reinforcement learning from human feedback (RLHF) has emerged as the standard paradigm for aligning large language models with human preferences. However, reward-based methods grou…