Shichang (Ray) Zhang

Conference Publications

  1. FUSE: Measure-Theoretic Compact Fuzzy Set Representation for Taxonomy Expansion (ACL 2024 Findings)
    Fred Xu, Song Jiang, Zijie Huang, Xiao Luo, Shichang Zhang, Yuanzhou Chen, Yizhou Sun [PDF][Code]

  2. Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks (ICML 2024)
    Haoyu Li*, Shichang Zhang*, Longwen Tang, Mathieu Bauchy, Yizhou Sun (*equal contribution) [PDF]

  3. SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models (ICML 2024)
    Xiaoxuan Wang*, Ziniu Hu*, Pan Lu*, Yanqiao Zhu*, Jieyu Zhang, Satyen Subramaniam, Arjun R Loomba, Shichang Zhang, Yizhou Sun, Wei Wang (*equal contribution) [PDF] [code]

  4. Laplacian Score Benefit Adaptive Filter Selection for Graph Neural Networks (SDM 2024)
    Yewen Wang, Shichang Zhang, Junghoo Cho, Yizhou Sun [PDF]

  5. Linkless Link Prediction via Relational Distillation (ICML 2023)
    Zhichun Guo, William Shiao, Shichang Zhang, Yozen Liu, Nitesh Chawla, Neil Shah, Tong Zhao [PDF][code]

  6. PaGE-Link: Graph Neural Network Explanation for Heterogeneous Link Prediction (WWW 2023)
    Shichang Zhang, Jiani Zhang, Xiang Song, Soji Adeshina, Da Zheng, Christos Faloutsos, Yizhou Sun. [PDF][code]

  7. GStarX: Explaining Graph Neural Networks with Structure-Aware Cooperative Games (NeurIPS 2022)
    Shichang Zhang, Neil Shah, Yozen Liu, Yizhou Sun [PDF] [code]

  8. Graph-less Neural Networks, Teach Old MLPs New Tricks via Distillation (ICLR 2022)
    Shichang Zhang, Yozen Liu, Yizhou Sun, Neil Shah [PDF] [code]

  9. Graph Condensation for Graph Neural Networks (ICLR 2022)
    Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, Neil Shah [PDF] [code]

Journal Publications

  1. An Explainable AI Approach using Graph Learning to Predict ICU Length of Stay (ISR Oct. 2024)
    Tianjian Guo, Indranil Bardhan, Ying Ding, Shichang Zhang [PDF]

  2. Motif-driven Contrastive Learning of Graph Representations (TKDE Feb. 2024)
    Shichang Zhang*, Ziniu Hu*, Arjun Subramonian, Yizhou Sun (*equal contribution) [PDF]

Workshop Papers and Pre-prints

  1. Generalized Group Data Attribution (ATTRIB@NeurIPS 2024)
    Dan Ley, Suraj Srinivas, Shichang Zhang, Gili Rusak, Himabindu Lakkaraju [PDF]

  2. Hierarchical Compression of Text-Rich Graphs via Large Language Models (pre-print)
    Shichang Zhang, Da Zheng, Jiani Zhang, Qi Zhu, Xiang Song, Soji Adeshina, Christos Faloutsos, George Karypis, Yizhou Sun. [PDF]

  3. Self-Control of LLM Behaviors by Compressing Suffix Gradient into Prefix Controller (MI@ICML 2024)
    Min Cai, Yuchen Zhang, Shichang Zhang, Fan Yin, Difan Zou, Yisong Yue, Ziniu Hu [PDF] [Code] [Website]

  4. Efficient Ensembles Improve Training Data Attribution (DMLR@ICML 2024)
    Junwei Deng, Ting-Wei Li, Shichang Zhang, Jiaqi Ma [PDF]

  5. Automated Molecular Concept Generation and Labeling with Large Language Models (XAI4Sci@AAAI 2024)
    Shichang Zhang*, Botao Xia*, Zimin Zhang*, Qianli Wu*, Fang Sun, Ziniu Hu, Yizhou Sun (*equal contribution) [PDF]

  6. Parameter-Efficient Tuning Large Language Models for Graph Representation Learning (pre-print)
    Qi Zhu, Da Zheng, Xiang Song, Shichang Zhang, Bowen Jin, Yizhou Sun, George Karypis [PDF]

  7. A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware (pre-print)
    Shichang Zhang, Atefeh Sohrabizadeh, Cheng Wan, Zijie Huang, Ziniu Hu, Yewen Wang, Yingyan (Celine) Lin, Jason Cong, Yizhou Sun [PDF]