128 citations · 350 across the 37 of their papers we have counts for
6 papers · 1 filter
MolEdit: Knowledge Editing for Multimodal Molecule Language Models
Zhenyu Lei, Patrick Soga, Yaochen Zhu +3
Understanding and continuously refining multimodal molecular knowledge is crucial for advancing biomedicine, chemistry, and materials science. Molecule language models (MoLMs) have…
Learning from Diverse Reasoning Paths with Routing and Collaboration
Zhenyu Lei, Zhen Tan, Song Wang +4
Advances in large language models (LLMs) significantly enhance reasoning capabilities but their deployment is restricted in resource-constrained scenarios. Knowledge distillation a…
FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs
Zihan Chen, Xingbo Fu, Yushun Dong +2
Federated Graph Learning (FGL) empowers clients to collaboratively train Graph neural networks (GNNs) in a distributed manner while preserving data privacy. However, FGL methods us…
BrainMAP: Learning Multiple Activation Pathways in Brain Networks
Song Wang, Zhenyu Lei, Zhen Tan +8
Functional Magnetic Resonance Image (fMRI) is commonly employed to study human brain activity, since it offers insight into the relationship between functional fluctuations and hum…
KG-CF: Knowledge Graph Completion with Context Filtering under the Guidance of Large Language Models
Zaiyi Zheng, Yushun Dong, Song Wang +3
Large Language Models (LLMs) have shown impressive performance in various tasks, including knowledge graph completion (KGC). However, current studies mostly apply LLMs to classific…
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…