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2020 – today
- 2024
[j1]Guibin Zhang
, Yiqiao Chen, Shiyu Wang, Kun Wang, Junfeng Fang:
Fortune favors the invariant: Enhancing GNNs' generalizability with Invariant Graph Learning. Knowl. Based Syst. 292: 111620 (2024)- [c11]Junfeng Fang, Shuai Zhang, Chang Wu, Zhengyi Yang, Zhiyuan Liu, Sihang Li, Kun Wang, Wenjie Du, Xiang Wang:
MolTC: Towards Molecular Relational Modeling In Language Models. ACL (Findings) 2024: 1943-1958 - [c10]Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen:
Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness. ICML 2024 - [c9]Wenjie Du, Shuai Zhang, Di Wu, Jun Xia, Ziyuan Zhao, Junfeng Fang, Yang Wang:
MMGNN: A Molecular Merged Graph Neural Network for Explainable Solvation Free Energy Prediction. IJCAI 2024: 5808-5816 - [c8]Kun Wang, Guohao Li, Shilong Wang, Guibin Zhang, Kai Wang, Yang You, Junfeng Fang, Xiaojiang Peng, Yuxuan Liang, Yang Wang:
The Snowflake Hypothesis: Training and Powering GNN with One Node One Receptive Field. KDD 2024: 3152-3163 - [c7]Kun Wang, Guibin Zhang, Xinnan Zhang, Junfeng Fang, Xun Wu, Guohao Li, Shirui Pan, Wei Huang, Yuxuan Liang:
The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs. KDD 2024: 3164-3175 - [c6]Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He:
EXGC: Bridging Efficiency and Explainability in Graph Condensation. WWW 2024: 721-732 - [c5]Yongduo Sui, Caizhi Tang, Zhixuan Chu, Junfeng Fang, Yuan Gao, Qing Cui, Longfei Li, Jun Zhou, Xiang Wang:
Invariant Graph Learning for Causal Effect Estimation. WWW 2024: 2552-2562 - [c4]Yuan Gao, Junfeng Fang, Yongduo Sui, Yangyang Li, Xiang Wang, Huamin Feng, Yongdong Zhang:
Graph Anomaly Detection with Bi-level Optimization. WWW 2024: 4383-4394 - [i13]Guibin Zhang, Yanwei Yue, Kun Wang, Junfeng Fang, Yongduo Sui, Kai Wang, Yuxuan Liang, Dawei Cheng, Shirui Pan, Tianlong Chen:
Two Heads Are Better Than One: Boosting Graph Sparse Training via Semantic and Topological Awareness. CoRR abs/2402.01242 (2024) - [i12]Junfeng Fang, Shuai Zhang, Chang Wu, Zhengyi Yang, Zhiyuan Liu, Sihang Li, Kun Wang, Wenjie Du, Xiang Wang:
MolTC: Towards Molecular Relational Modeling In Language Models. CoRR abs/2402.03781 (2024) - [i11]Junfeng Fang, Xinglin Li, Yongduo Sui, Yuan Gao, Guibin Zhang, Kun Wang, Xiang Wang, Xiangnan He:
EXGC: Bridging Efficiency and Explainability in Graph Condensation. CoRR abs/2402.05962 (2024) - [i10]Kun Wang, Hao Wu, Guibin Zhang, Junfeng Fang, Yuxuan Liang, Yuankai Wu, Roger Zimmermann, Yang Wang:
Modeling Spatio-temporal Dynamical Systems with Neural Discrete Learning and Levels-of-Experts. CoRR abs/2402.05970 (2024) - [i9]Kun Wang, Guibin Zhang, Xinnan Zhang, Junfeng Fang, Xun Wu, Guohao Li, Shirui Pan, Wei Huang, Yuxuan Liang:
The Heterophilic Snowflake Hypothesis: Training and Empowering GNNs for Heterophilic Graphs. CoRR abs/2406.12539 (2024) - [i8]Baolong Bi, Shenghua Liu, Yiwei Wang, Lingrui Mei, Hongcheng Gao, Junfeng Fang, Xueqi Cheng:
StruEdit: Structured Outputs Enable the Fast and Accurate Knowledge Editing for Large Language Models. CoRR abs/2409.10132 (2024) - [i7]Miao Yu, Junyuan Mao, Guibin Zhang, Jingheng Ye, Junfeng Fang, Aoxiao Zhong, Yang Liu, Yuxuan Liang, Kun Wang, Qingsong Wen:
Mind Scramble: Unveiling Large Language Model Psychology Via Typoglycemia. CoRR abs/2410.01677 (2024) - [i6]Junfeng Fang, Houcheng Jiang, Kun Wang, Yunshan Ma, Xiang Wang, Xiangnan He, Tat-Seng Chua:
AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models. CoRR abs/2410.02355 (2024) - [i5]Yanchen Luo, Junfeng Fang, Sihang Li, Zhiyuan Liu, Jiancan Wu, An Zhang, Wenjie Du, Xiang Wang:
Text-guided Diffusion Model for 3D Molecule Generation. CoRR abs/2410.03803 (2024) - [i4]Houcheng Jiang, Junfeng Fang, Tianyu Zhang, An Zhang, Ruipeng Wang, Tao Liang, Xiang Wang:
Neuron-Level Sequential Editing for Large Language Models. CoRR abs/2410.04045 (2024) - [i3]Jinghan Li, Yuan Gao, Jinda Lu, Junfeng Fang, Congcong Wen, Hui Lin, Xiang Wang:
DiffGAD: A Diffusion-based Unsupervised Graph Anomaly Detector. CoRR abs/2410.06549 (2024) - [i2]Guibin Zhang, Yanwei Yue, Xiangguo Sun, Guancheng Wan, Miao Yu, Junfeng Fang, Kun Wang, Dawei Cheng:
G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks. CoRR abs/2410.11782 (2024) - [i1]Zhenhong Zhou, Haiyang Yu, Xinghua Zhang, Rongwu Xu, Fei Huang, Kun Wang, Yang Liu, Junfeng Fang, Yongbin Li:
On the Role of Attention Heads in Large Language Model Safety. CoRR abs/2410.13708 (2024) - 2023
- [c3]Kun Wang, Yuxuan Liang, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang:
Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective. ICLR 2023 - [c2]Junfeng Fang, Wei Liu, Yuan Gao, Zemin Liu, An Zhang, Xiang Wang, Xiangnan He:
Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis. NeurIPS 2023 - [c1]Junfeng Fang, Xiang Wang, An Zhang, Zemin Liu, Xiangnan He, Tat-Seng Chua:
Cooperative Explanations of Graph Neural Networks. WSDM 2023: 616-624
Coauthor Index
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