2 papers
cs.AI2026
LAP: An Agent-to-Instrument Protocol for Autonomous Science
Linwu Zhu, Liqiang Gao, Yan Chen +2
Autonomous science is moving from demonstration to infrastructure. Large language model agents now plan experiments, and self-driving laboratories execute them. Yet every such syst…
cs.CL2025
Training LLMs Beyond Next Token Prediction -- Filling the Mutual Information Gap
Chun-Hao Yang, Bo-Han Feng, Tzu-Yuan Lai +3
Optimizing training performance in large language models (LLMs) remains an essential challenge, particularly in improving model performance while maintaining computational costs. T…