1 citations · 1 across the 1 of their papers we have counts for
8 papers
ClinicalBench: Can LLMs Beat Traditional ML Models in Clinical Prediction?
Canyu Chen, Jian Yu, Shan Chen +8
Large Language Models (LLMs) hold great promise to revolutionize current clinical systems for their superior capacities on medical text processing tasks and medical licensing exams…
Authorship Attribution in the Era of LLMs: Problems, Methodologies, and Challenges
Baixiang Huang, Canyu Chen, Kai Shu
Accurate attribution of authorship is crucial for maintaining the integrity of digital content, improving forensic investigations, and mitigating the risks of misinformation and pl…
SafeMind: A Risk-Aware Differentiable Control Framework for Adaptive and Safe Quadruped Locomotion
Zukun Zhang, Kai Shu, Mingqiao Mo
Learning-based quadruped controllers achieve impressive agility but typically lack formal safety guarantees under model uncertainty, perception noise, and unstructured contact cond…
Online GPU Energy Optimization with Switching-Aware Bandits
Xiongxiao Xu, Solomon Abera Bekele, Brice Videau +1
Energy consumption has become a bottleneck for future computing architectures, from wearable devices to leadership-class supercomputers. Existing energy management techniques large…
Can Editing LLMs Inject Harm?
Canyu Chen, Baixiang Huang, Zekun Li +12
Large Language Models (LLMs) have emerged as a new information channel. Meanwhile, one critical but under-explored question is: Is it possible to bypass the safety alignment and in…
Can Knowledge Editing Really Correct Hallucinations?
Baixiang Huang, Canyu Chen, Xiongxiao Xu +2
Large Language Models (LLMs) suffer from hallucinations, referring to the non-factual information in generated content, despite their superior capacities across tasks. Meanwhile, k…