16 papers
Towards Certified Unlearning for Deep Neural Networks
Binchi Zhang, Yushun Dong, Tianhao Wang +1
In the field of machine unlearning, certified unlearning has been extensively studied in convex machine learning models due to its high efficiency and strong theoretical guarantees…
Machine-State Embeddings as an Operational Coordinate System for Accelerator Operation
Chris Tennant, Jundong Li, Song Wang
We demonstrate that graph neural network (GNN) embeddings of injector configurations provide a practical operational coordinate system for the Continuous Electron Beam Accelerator…
Reforming the Mechanism: Editing Reasoning Patterns in LLMs with Circuit Reshaping
Zhenyu Lei, Qiong Wu, Jianxiong Dong +4
Large language models (LLMs) often exhibit flawed reasoning ability that undermines reliability. Existing approaches to improving reasoning typically treat it as a general and mono…
BrainTAP: Brain Disorder Prediction with Adaptive Distill and Selective Prior Integration
Zhenyu Lei, Aiying Zhang, Song Wang +2
Predicting clinical outcomes from brain networks in large-scale neuroimaging cohorts such as the Adolescent Brain Cognitive Development (ABCD) study requires effectively integratin…
Interpretable Neuropsychiatric Diagnosis via Concept-Guided Graph Neural Networks
Song Wang, Zhenyu Lei, Zhen Tan +4
Nearly one in five adolescents currently live with a diagnosed mental or behavioral health condition, such as anxiety, depression, or conduct disorder, underscoring the urgency of…
Harnessing Large Language Models for Disaster Management: A Survey
Zhenyu Lei, Yushun Dong, Weiyu Li +3
Large language models (LLMs) have revolutionized scientific research with their exceptional capabilities and transformed various fields. Among their practical applications, LLMs ha…