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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
DSGym: A Holistic Framework for Evaluating and Training Data Science Agents
Fan Nie, Junlin Wang, Harper Hua +6
Data science agents promise to accelerate discovery and insight-generation by turning data into executable analyses and findings. Yet existing data science benchmarks fall short du…
cs.AI2025
Weak-for-Strong: Training Weak Meta-Agent to Harness Strong Executors
Fan Nie, Lan Feng, Haotian Ye +5
Efficiently leveraging of the capabilities of contemporary large language models (LLMs) is increasingly challenging, particularly when direct fine-tuning is expensive and often imp…