3 papers
cs.CL2026
Lexical Perturbations Disrupt LLM Reasoning: An Empirical Study of Attention Diversion
Jiaqian Zhu, Yang Zhang, Junhua Ding +1
Large Language Models (LLMs) achieve strong reasoning performance, but their robustness to realistic lexical corruption remains poorly understood. We evaluate four open-weight inst…
cs.AI2026
MetaGAI: A Large-Scale and High-Quality Benchmark for Generative AI Model and Data Card Generation
Haoxuan Zhang, Ruochi Li, Yang Zhang +4
The rapid proliferation of Generative AI necessitates rigorous documentation standards for transparency and governance. However, manual creation of Model and Data Cards is not scal…
cs.CL2024
Efficient Fine-Tuning of Large Language Models for Automated Medical Documentation
Hui Yi Leong, Yi Fan Gao, Ji Shuai +2
Scientific research indicates that for every hour spent in direct patient care, physicians spend nearly two additional hours on administrative tasks, particularly on electronic hea…