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Kaize Ding

Publication record assembled from the DBLP archive of ranked conferences.

Papers indexed

73

Venues

19

Active years

2019–2026

Best venue rank

A*

Where they publish

Papers

73 indexed papers, newest first.

YearVenueTitleAuthors
2026AAAITowards Acyclic Preference Evaluation of Language Models via Multiple Evaluators.Zhengyu Hu, Jieyu Zhang, Zhihan Xiong, Alexander Ratner, Kaize Ding, Ranjay Krishna
2026ACLAddressing Overthinking in Large Vision-Language Models via Gated Perception-Reasoning Optimization.Xingjian Diao, Zheyuan Liu, Chunhui Zhang, Weiyi Wu, Keyi Kong, Lin Shi, Kaize Ding, Soroush Vosoughi, Jiang Gui
2026ACLExplainable and Fine-Grained Safeguarding of LLM Multi-Agent Systems via Bi-Level Graph Anomaly Detection.Junjun Pan, Yixin Liu, Rui Miao, Kaize Ding, Yu Zheng, Quoc Viet Hung Nguyen, Alan Wee-Chung Liew, Shirui Pan
2026ACLMolMem: Memory-Augmented Agentic Reinforcement Learning for Sample-Efficient Molecular Optimization.Ziqing Wang, Yibo Wen, Abhishek Pandey, Han Liu, Kaize Ding
2026ACLA Survey of Large Language Models for Text-Guided Molecular Discovery: From Molecule Generation to Optimization.Ziqing Wang, Kexin Zhang, Zihan Zhao, Yibo Wen, Abhishek Pandey, Han Liu, Kaize Ding
2026ACLCoAct: Co-Active LLM Preference Learning with Human-AI Synergy.Ruiyao Xu, Mihir Parmar, Tiankai Yang, Zhengyu Hu, Yue Zhao, Kaize Ding
2026PAKDDGlassMol: Interpretable Molecular Property Prediction with Concept Bottleneck Models.Oscar Rivera, Ziqing Wang, Matthieu Dagommer, Abhishek Pandey, Kaize Ding
2026WSDMRigorizing Retrieval-augmented Generation with Structured Knowledge Intelligence (6 Hrs).Zhisheng Qi, Yongjia Lei, Haoyu Han, Harry Shomer, Kaize Ding, Yu Zhang, Ryan A. Rossi, Hui Liu, Yu Wang
2025ACLAD-LLM: Benchmarking Large Language Models for Anomaly Detection.Tiankai Yang, Yi Nian, Li Li, Ruiyao Xu, Yuangang Li, Jiaqi Li, Zhuo Xiao, Xiyang Hu, Ryan A. Rossi, Kaize Ding, Xia Hu, Yue Zhao
2025CIKMFact or Facsimile? Evaluating the Factual Robustness of Modern Retrievers.Haoyu Wu, Qingcheng Zeng, Kaize Ding
2025CIKMUncertainty Quantification for Multiple-Choice Questions is Just One-Token Deep.Qingcheng Zeng, Mingyu Jin, Qinkai Yu, Zhenting Wang, Wenyue Hua, Guangyan Sun, Yanda Meng, Shiqing Ma, Qifan Wang, Felix Juefei-Xu, Fan Yang, Kaize Ding, Ruixiang Tang, Yongfeng Zhang
2025COLINGExploring Concept Depth: How Large Language Models Acquire Knowledge and Concept at Different Layers?Mingyu Jin, Qinkai Yu, Jingyuan Huang, Qingcheng Zeng, Zhenting Wang, Wenyue Hua, Haiyan Zhao, Kai Mei, Yanda Meng, Kaize Ding, Fan Yang, Mengnan Du, Yongfeng Zhang
2025EMNLPExplaining Length Bias in LLM-Based Preference Evaluations.Zhengyu Hu, Linxin Song, Jieyu Zhang, Zheyuan Xiao, Tianfu Wang, Zhengyu Chen, Nicholas Jing Yuan, Jianxun Lian, Kaize Ding, Hui Xiong
2025EMNLPAMANDA: Agentic Medical Knowledge Augmentation for Data-Efficient Medical Visual Question Answering.Ziqing Wang, Chengsheng Mao, Xiaole Wen, Yuan Luo, Kaize Ding
2025ICASSPUncertainty-Aware Robust Learning on Noisy Graphs.Shuyi Chen, Kaize Ding, Shixiang Zhu
2025ICLRUnifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark.Yili Wang, Yixin Liu, Xu Shen, Chenyu Li, Rui Miao, Kaize Ding, Ying Wang, Shirui Pan, Xin Wang
2025ICLROn Large Language Model Continual Unlearning.Chongyang Gao, Lixu Wang, Kaize Ding, Chenkai Weng, Xiao Wang, Qi Zhu
2025KDDRelKD 2025: The Third International Workshop on Resource-Efficient Learning for Knowledge Discovery.Chuxu Zhang, Kaize Ding, Jundong Li, Dongkuan Xu, Haoyu Wang, Derek Zhiyuan Cheng, Huan Liu
2025KDDA Survey on Model Extraction Attacks and Defenses for Large Language Models.Kaixiang Zhao, Lincan Li, Kaize Ding, Neil Zhenqiang Gong, Yue Zhao, Yushun Dong
2025NAACLAvoiding Copyright Infringement via Large Language Model Unlearning.Guangyao Dou, Zheyuan Liu, Qing Lyu, Kaize Ding, Eric Wong
2025NAACLALERT: An LLM-powered Benchmark for Automatic Evaluation of Recommendation Explanations.Yichuan Li, Xinyang Zhang, Chenwei Zhang, Mao Li, Tianyi Liu, Pei Chen, Yifan Gao, Kyumin Lee, Kaize Ding, Zhengyang Wang, Zhihan Zhang, Jingbo Shang, Xian Li, Trishul Chilimbi
2025NAACLLarge Language Models for Anomaly and Out-of-Distribution Detection: A Survey.Ruiyao Xu, Kaize Ding
2025WWWResource-Efficient Learning for the Web.Chuxu Zhang, Kaize Ding, Jundong Li, Dongkuan Xu, Haoyu Wang, Derek Zhiyuan Cheng, Huan Liu
2025WWWRelWeb 2025: The International Workshop on Resource-Efficient Learning for the Web.Chuxu Zhang, Kaize Ding, Jundong Li, Dongkuan Xu, Haoyu Wang, Derek Zhiyuan Cheng, Huan Liu
2025WSDMFusion Matters: Learning Fusion in Deep Click-through Rate Prediction Models.Kexin Zhang, Fuyuan Lyu, Xing Tang, Dugang Liu, Chen Ma, Kaize Ding, Xiuqiang He, Xue Liu
2024AAAIData-Efficient Graph Learning.Kaize Ding
2024AAAISterling: Synergistic Representation Learning on Bipartite Graphs.Baoyu Jing, Yuchen Yan, Kaize Ding, Chanyoung Park, Yada Zhu, Huan Liu, Hanghang Tong
2024ACLEmpowering Large Language Models for Textual Data Augmentation.Yichuan Li, Kaize Ding, Jianling Wang, Kyumin Lee
2024CIKMData Quality-aware Graph Machine Learning.Yu Wang, Kaize Ding, Xiaorui Liu, Jian Kang, Ryan A. Rossi, Tyler Derr
2024DSAAMetaGAD: Meta Representation Adaptation for Few-Shot Graph Anomaly Detection.Xiongxiao Xu, Kaize Ding, Canyu Chen, Kai Shu
2024EMNLPOn Fake News Detection with LLM Enhanced Semantics Mining.Xiaoxiao Ma, Yuchen Zhang, Kaize Ding, Jian Yang, Jia Wu, Hao Fan
2024EMNLPLet's Ask GNN: Empowering Large Language Model for Graph In-Context Learning.Zhengyu Hu, Yichuan Li, Zhengyu Chen, Jingang Wang, Han Liu, Kyumin Lee, Kaize Ding
2024KDDGraph Anomaly Detection with Few Labels: A Data-Centric Approach.Xiaoxiao Ma, Ruikun Li, Fanzhen Liu, Kaize Ding, Jian Yang, Jia Wu
2024KDDDivide and Denoise: Empowering Simple Models for Robust Semi-Supervised Node Classification against Label Noise.Kaize Ding, Xiaoxiao Ma, Yixin Liu, Shirui Pan
2024KDDMastering Long-Tail Complexity on Graphs: Characterization, Learning, and Generalization.Haohui Wang, Baoyu Jing, Kaize Ding, Yada Zhu, Wei Cheng, Si Zhang, Yonghui Fan, Liqing Zhang, Dawei Zhou
2024KDDRelKD 2024: The Second International Workshop on Resource-Efficient Learning for Knowledge Discovery.Chuxu Zhang, Dongkuan Xu, Kaize Ding, Jundong Li, Mojan Javaheripi, Subhabrata Mukherjee, Nitesh V. Chawla, Huan Liu
2024WACVMGM-AE: Self-Supervised Learning on 3D Shape Using Mesh Graph Masked Autoencoders.Zhangsihao Yang, Kaize Ding, Huan Liu, Yalin Wang
2024WSDMThe 5th International Workshop on Machine Learning on Graphs (MLoG).Tyler Derr, Yao Ma, Kaize Ding, Tong Zhao, Nesreen K. Ahmed
2023AAAIEliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning.Kaize Ding, Yancheng Wang, Yingzhen Yang, Huan Liu
2023CIKMSTREAMS: Towards Spatio-Temporal Causal Discovery with Reinforcement Learning for Streamflow Rate Prediction.Paras Sheth, Ahmadreza Mosallanezhad, Kaize Ding, Reepal Shah, John Sabo, Huan Liu, K. Seluk Candan
2023CIKMLearning Node Abnormality with Weak Supervision.Qinghai Zhou, Kaize Ding, Huan Liu, Hanghang Tong
2023EMNLPGRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed Graphs.Yichuan Li, Kaize Ding, Kyumin Lee
2023KDDLearning Strong Graph Neural Networks with Weak Information.Yixin Liu, Kaize Ding, Jianling Wang, Vincent C. S. Lee, Huan Liu, Shirui Pan
2023KDDVirtual Node Tuning for Few-shot Node Classification.Zhen Tan, Ruocheng Guo, Kaize Ding, Huan Liu
2023KDDFederated Few-shot Learning.Song Wang, Xingbo Fu, Kaize Ding, Chen Chen, Huiyuan Chen, Jundong Li
2023SIGIRHyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer.Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng
2023WSDMGOOD-D: On Unsupervised Graph Out-Of-Distribution Detection.Yixin Liu, Kaize Ding, Huan Liu, Shirui Pan
2023WSDMFew-shot Node Classification with Extremely Weak Supervision.Song Wang, Yushun Dong, Kaize Ding, Chen Chen, Jundong Li
2022AAAIMeta Propagation Networks for Graph Few-shot Semi-supervised Learning.Kaize Ding, Jianling Wang, James Caverlee, Huan Liu
2022ICDMGeneralized Few-Shot Node Classification.Zhe Xu, Kaize Ding, Yu-Xiong Wang, Huan Liu, Hanghang Tong
2022IJCAIFew-Shot Learning on Graphs.Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu
2022KDDToward Graph Minimally-Supervised Learning.Kaize Ding, Chuxu Zhang, Jie Tang, Nitesh V. Chawla, Huan Liu
2022KDDTask-Adaptive Few-shot Node Classification.Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen, Jundong Li
2022WSDMGraph Minimally-supervised Learning.Kaize Ding, Jundong Li, Nitesh V. Chawla, Huan Liu
2022WSDMGraph Few-shot Class-incremental Learning.Zhen Tan, Kaize Ding, Ruocheng Guo, Huan Liu
2022SISAPCausal Disentanglement with Network Information for Debiased Recommendations.Paras Sheth, Ruocheng Guo, Kaize Ding, Lu Cheng, K. Seluk Candan, Huan Liu
2021AAAIFact-Enhanced Synthetic News Generation.Kai Shu, Yichuan Li, Kaize Ding, Huan Liu
2021CIKMTowards Anomaly-resistant Graph Neural Networks via Reinforcement Learning.Kaize Ding, Xuan Shan, Huan Liu
2021CIKMAdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter.Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, Jundong Li
2021EMNLPLearning to Selectively Learn for Weakly-supervised Paraphrase Generation.Kaize Ding, Dingcheng Li, Alexander Hanbo Li, Xing Fan, Chenlei Guo, Yang Liu, Huan Liu
2021WWWFew-shot Network Anomaly Detection via Cross-network Meta-learning.Kaize Ding, Qinghai Zhou, Hanghang Tong, Huan Liu
2021SIGIRSequential Recommendation for Cold-start Users with Meta Transitional Learning.Jianling Wang, Kaize Ding, James Caverlee
2021SDMSession-based Recommendation with Hypergraph Attention Networks.Jianling Wang, Kaize Ding, Ziwei Zhu, James Caverlee
2020CIKMChallenges in Combating COVID-19 Infodemic - Data, Tools, and Ethics.Kaize Ding, Kai Shu, Yichuan Li, Amrita Bhattacharjee, Huan Liu
2020CIKMGraph Prototypical Networks for Few-shot Learning on Attributed Networks.Kaize Ding, Jianling Wang, Jundong Li, Kai Shu, Chenghao Liu, Huan Liu
2020CIKMGraph Few-shot Learning with Attribute Matching.Ning Wang, Minnan Luo, Kaize Ding, Lingling Zhang, Jundong Li, Qinghua Zheng
2020EMNLPBe More with Less: Hypergraph Attention Networks for Inductive Text Classification.Kaize Ding, Jianling Wang, Jundong Li, Dingcheng Li, Huan Liu
2020IJCAIInductive Anomaly Detection on Attributed Networks.Kaize Ding, Jundong Li, Nitin Agarwal, Huan Liu
2020SIGIRNext-item Recommendation with Sequential Hypergraphs.Jianling Wang, Kaize Ding, Liangjie Hong, Huan Liu, James Caverlee
2020WSDMKey Opinion Leaders in Recommendation Systems: Opinion Elicitation and Diffusion.Jianling Wang, Kaize Ding, Ziwei Zhu, Yin Zhang, James Caverlee
2019IJCAIInterSpot: Interactive Spammer Detection in Social Media.Kaize Ding, Jundong Li, Shivam Dhar, Shreyash Devan, Huan Liu
2019WSDMInteractive Anomaly Detection on Attributed Networks.Kaize Ding, Jundong Li, Huan Liu
2019SDMDeep Anomaly Detection on Attributed Networks.Kaize Ding, Jundong Li, Rohit Bhanushali, Huan Liu