Shichang (Ray) Zhang

Conference Publications

1. Automated Molecular Concept Generation and Labeling with Large Language Models
   Zimin Zhang*, Qianli Wu*, Botao Xia*, Fang Sun, Ziniu Hu, Yizhou Sun, Shichang Zhang (*equal contribution)
   COLING 2025 [PDF] [Code]
   

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

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

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

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

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

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

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

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

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

Journal Publications

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

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

Workshop Papers and Pre-prints

1. Building Bridges, Not Walls - Advancing Interpretability by Unifying Feature, Data and Model Component Attribution
   Shichang Zhang, Tessa Han, Usha Bhalla, Himabindu Lakkaraju
   Pre-print [PDF]
   

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

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

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

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

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

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