Zhou, Kaixiong

33 publications

ICLR 2025 DAMO: Decoding by Accumulating Activations Momentum for Mitigating Hallucinations in Vision-Language Models Kaishen Wang, Hengrui Gu, Meijun Gao, Kaixiong Zhou

CVPR 2025 Flexible Group Count Enables Hassle-Free Structured Pruning Jiamu Zhang, Shaochen Zhong, Andrew Ye, Zirui Liu, Sebastian Zhao, Kaixiong Zhou, Li Li, Soo-Hyun Choi, Rui Chen, Xia Hu, Shuai Xu, Vipin Chaudhary

ICLR 2025 MQuAKE-Remastered: Multi-Hop Knowledge Editing Can Only Be Advanced with Reliable Evaluations Shaochen Zhong, Yifan Lu, Lize Shao, Bhargav Bhushanam, Xiaocong Du, Yixin Wan, Yucheng Shi, Daochen Zha, Yiwei Wang, Ninghao Liu, Kaixiong Zhou, Shuai Xu, Kai-Wei Chang, Louis Feng, Vipin Chaudhary, Xia Hu

ICML 2025 Retrieval Augmented Zero-Shot Enzyme Generation for Specified Substrate Jiahe Du, Kaixiong Zhou, Xinyu Hong, Zhaozhuo Xu, Jinbo Xu, Xiao Huang

CPAL 2025 Sparse MoE as a New Treatment: Addressing Forgetting, Fitting, Learning Issues in Multi-Modal Multi-Task Learning Jie Peng, Sukwon Yun, Kaixiong Zhou, Ruida Zhou, Thomas Hartvigsen, Yanyong Zhang, Zhangyang Wang, Tianlong Chen

CPAL 2025 You Only Debias Once: Towards Flexible Accuracy-Fairness Trade-Offs at Inference Time Xiaotian Han, Tianlong Chen, Kaixiong Zhou, Zhimeng Jiang, Zhangyang Wang, Xia Hu

ICLR 2024 Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang, Xin Wang

ICML 2024 GNNs Also Deserve Editing, and They Need It More than Once Shaochen Zhong, Duy Le, Zirui Liu, Zhimeng Jiang, Andrew Ye, Jiamu Zhang, Jiayi Yuan, Kaixiong Zhou, Zhaozhuo Xu, Jing Ma, Shuai Xu, Vipin Chaudhary, Xia Hu

NeurIPS 2024 Gradient Rewiring for Editable Graph Neural Network Training Zhimeng Jiang, Zirui Liu, Xiaotian Han, Qizhang Feng, Hongye Jin, Qiaoyu Tan, Kaixiong Zhou, Na Zou, Xia Hu

ICML 2024 Knowledge Graphs Can Be Learned with Just Intersection Features Duy Le, Shaochen Zhong, Zirui Liu, Shuai Xu, Vipin Chaudhary, Kaixiong Zhou, Zhaozhuo Xu

CVPR 2024 Molecular Data Programming: Towards Molecule Pseudo-Labeling with Systematic Weak Supervision Xin Juan, Kaixiong Zhou, Ninghao Liu, Tianlong Chen, Xin Wang

ICLRW 2024 Privacy-Preserving Fine-Tuning of Large Language Models Through Flatness Tiejin Chen, Longchao Da, Huixue Zhou, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei

ICML 2024 Rethinking Independent Cross-Entropy Loss for Graph-Structured Data Rui Miao, Kaixiong Zhou, Yili Wang, Ninghao Liu, Ying Wang, Xin Wang

ICML 2024 Soft Prompt Recovers Compressed LLMs, Transferably Zhaozhuo Xu, Zirui Liu, Beidi Chen, Shaochen Zhong, Yuxin Tang, Jue Wang, Kaixiong Zhou, Xia Hu, Anshumali Shrivastava

ICML 2024 TVE: Learning Meta-Attribution for Transferable Vision Explainer Guanchu Wang, Yu-Neng Chuang, Fan Yang, Mengnan Du, Chia-Yuan Chang, Shaochen Zhong, Zirui Liu, Zhaozhuo Xu, Kaixiong Zhou, Xuanting Cai, Xia Hu

TMLR 2023 DSpar: An Embarrassingly Simple Strategy for Efficient GNN Training and Inference via Degree-Based Sparsification Zirui Liu, Kaixiong Zhou, Zhimeng Jiang, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu

ECML-PKDD 2023 ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning Yucheng Shi, Kaixiong Zhou, Ninghao Liu

NeurIPSW 2023 LeanFlex-GKP: Advancing Hassle-Free Structured Pruning with Simple Flexible Group Count Jiamu Zhang, Shaochen Zhong, Andrew Ye, Zirui Liu, Kaixiong Zhou, Xia Hu, Shuai Xu, Vipin Chaudhary

IJCAI 2023 Probabilistic Masked Attention Networks for Explainable Sequential Recommendation Huiyuan Chen, Kaixiong Zhou, Zhimeng Jiang, Chin-Chia Michael Yeh, Xiaoting Li, Menghai Pan, Yan Zheng, Xia Hu, Hao Yang

ICML 2023 RSC: Accelerate Graph Neural Networks Training via Randomized Sparse Computations Zirui Liu, Chen Shengyuan, Kaixiong Zhou, Daochen Zha, Xiao Huang, Xia Hu

NeurIPS 2023 Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model Zirui Liu, Guanchu Wang, Shaochen Zhong, Zhaozhuo Xu, Daochen Zha, Ruixiang Tang, Zhimeng Jiang, Kaixiong Zhou, Vipin Chaudhary, Shuai Xu, Xia Hu

NeurIPS 2022 A Comprehensive Study on Large-Scale Graph Training: Benchmarking and Rethinking Keyu Duan, Zirui Liu, Peihao Wang, Wenqing Zheng, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang

ICLR 2022 An Information Fusion Approach to Learning with Instance-Dependent Label Noise Zhimeng Jiang, Kaixiong Zhou, Zirui Liu, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu

AutoML 2022 AutoCoG: A Unified Data-Model Co-Search Framework for Graph Neural Networks Duc N.M Hoang, Kaixiong Zhou, Tianlong Chen, Xia Hu, Zhangyang Wang

ICLR 2022 EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression Zirui Liu, Kaixiong Zhou, Fan Yang, Li Li, Rui Chen, Xia Hu

AAAI 2022 Orthogonal Graph Neural Networks Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang

IJCAI 2022 Table2Graph: Transforming Tabular Data to Unified Weighted Graph Kaixiong Zhou, Zirui Liu, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu

NeurIPS 2021 Dirichlet Energy Constrained Learning for Deep Graph Neural Networks Kaixiong Zhou, Xiao Huang, Daochen Zha, Rui Chen, Li Li, Soo-Hyun Choi, Xia Hu

ICCV 2021 DivAug: Plug-in Automated Data Augmentation with Explicit Diversity Maximization Zirui Liu, Haifeng Jin, Ting-Hsiang Wang, Kaixiong Zhou, Xia Hu

NeurIPS 2020 Detecting Interactions from Neural Networks via Topological Analysis Zirui Liu, Qingquan Song, Kaixiong Zhou, Ting-Hsiang Wang, Ying Shan, Xia Hu

IJCAI 2020 Multi-Channel Graph Neural Networks Kaixiong Zhou, Qingquan Song, Xiao Huang, Daochen Zha, Na Zou, Xia Hu

NeurIPS 2020 Towards Deeper Graph Neural Networks with Differentiable Group Normalization Kaixiong Zhou, Xiao Huang, Yuening Li, Daochen Zha, Rui Chen, Xia Hu

IJCAI 2019 Experience Replay Optimization Daochen Zha, Kwei-Herng Lai, Kaixiong Zhou, Xia Hu