Li, Jundong

61 publications

ICLR 2026 Energy-Based Transformers Are Scalable Learners and Thinkers Alexi Gladstone, Ganesh Nanduru, Md Mofijul Islam, Peixuan Han, Hyeonjeong Ha, Aman Chadha, Yilun Du, Heng Ji, Jundong Li, Tariq Iqbal

TMLR 2026 Explainable Graph Learning for Particle Accelerator Operations Song Wang, Chris Tennant, Jundong Li

ICLR 2026 Probing to Refine: Reinforcement Distillation of LLM Reasoners via Explanatory Inversion Zhen Tan, Chengshuai Zhao, Song Wang, Jundong Li, Tianlong Chen, Huan Liu

ICLR 2026 Rank-GRPO: Training LLM-Based Conversational Recommender Systems with Reinforcement Learning Yaochen Zhu, Harald Steck, Dawen Liang, Yinhan He, Vito Claudio Ostuni, Jundong Li, Nathan Kallus

ICLR 2026 Reforming the Mechanism: Editing Reasoning Patterns in LLMs with Circuit Reshaping Zhenyu Lei, Qiong Wu, Jianxiong Dong, Yinhan He, Emily Dodwell, Yushun Dong, Jundong Li

ICML 2025 Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion Binchi Zhang, Zaiyi Zheng, Zhengzhang Chen, Jundong Li

AAAI 2025 BrainMAP: Learning Multiple Activation Pathways in Brain Networks Song Wang, Zhenyu Lei, Zhen Tan, Jiaqi Ding, Xinyu Zhao, Yushun Dong, Guorong Wu, Tianlong Chen, Chen Chen, Aiying Zhang, Jundong Li

ICLR 2025 CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models Song Wang, Peng Wang, Tong Zhou, Yushun Dong, Zhen Tan, Jundong Li

ICLR 2025 Causal Effect Estimation with Mixed Latent Confounders and Post-Treatment Variables Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li

ICLR 2025 Edge Prompt Tuning for Graph Neural Networks Xingbo Fu, Yinhan He, Jundong Li

TMLR 2025 FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Zihan Chen, Xingbo Fu, Yushun Dong, Jundong Li, Cong Shen

TMLR 2025 Generative Risk Minimization for Out-of-Distribution Generalization on Graphs Song Wang, Zhen Tan, Yaochen Zhu, Chuxu Zhang, Jundong Li

TMLR 2025 Global Graph Counterfactual Explanation: A Subgraph Mapping Approach Yinhan He, Wendy Zheng, Yaochen Zhu, Jing Ma, Saumitra Mishra, Natraj Raman, Ninghao Liu, Jundong Li

ICLR 2025 Graph Neural Networks Are More than Filters: Revisiting and Benchmarking from a Spectral Perspective Yushun Dong, Patrick Soga, Yinhan He, Song Wang, Jundong Li

NeurIPS 2025 GraphTOP: Graph Topology-Oriented Prompting for Graph Neural Networks Xingbo Fu, Zhenyu Lei, Zihan Chen, Binchi Zhang, Chuxu Zhang, Jundong Li

NeurIPS 2025 Hierarchical Demonstration Order Optimization for Many-Shot In-Context Learning Yinhan He, Wendy Zheng, Song Wang, Zaiyi Zheng, Yushun Dong, Yaochen Zhu, Jundong Li

TMLR 2025 Instance-Aware Graph Prompt Learning Jiazheng Li, Jundong Li, Chuxu Zhang

IJCAI 2025 Interpreting Pretrained Language Models via Concept Bottlenecks (Extended Abstract) Zhen Tan, Lu Cheng, Song Wang, Bo Yuan, Jundong Li, Huan Liu

WACV 2025 Invariant Shape Representation Learning for Image Classification Tonmoy Hossain, Jing Ma, Jundong Li, Miaomiao Zhang

ICML 2025 MAPLE: Many-Shot Adaptive Pseudo-Labeling for In-Context Learning Zihan Chen, Song Wang, Zhen Tan, Jundong Li, Cong Shen

ICLR 2025 Reasoning of Large Language Models over Knowledge Graphs with Super-Relations Song Wang, Junhong Lin, Xiaojie Guo, Julian Shun, Jundong Li, Yada Zhu

AAAI 2025 ST-FiT: Inductive Spatial-Temporal Forecasting with Limited Training Data Zhenyu Lei, Yushun Dong, Jundong Li, Chen Chen

NeurIPS 2025 SemCoT: Accelerating Chain-of-Thought Reasoning Through Semantically-Aligned Implicit Tokens Yinhan He, Wendy Zheng, Yaochen Zhu, Zaiyi Zheng, Lin Su, Sriram Vasudevan, Qi Guo, Liangjie Hong, Jundong Li

ICML 2025 Towards Global-Level Mechanistic Interpretability: A Perspective of Modular Circuits of Large Language Models Yinhan He, Wendy Zheng, Yushun Dong, Yaochen Zhu, Chen Chen, Jundong Li

AAAI 2025 Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning Xingbo Fu, Zihan Chen, Yinhan He, Song Wang, Binchi Zhang, Chen Chen, Jundong Li

ICLR 2024 Adversarial Attacks on Fairness of Graph Neural Networks Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li

NeurIPSW 2024 CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models Song Wang, Peng Wang, Tong Zhou, Yushun Dong, Zhen Tan, Jundong Li

NeurIPSW 2024 Deep Interactions for Multimodal Molecular Property Prediction Patrick Soga, Zhenyu Lei, Camille L. Bilodeau, Jundong Li

NeurIPS 2024 Efficient Prompt Optimization Through the Lens of Best Arm Identification Chengshuai Shi, Kun Yang, Zihan Chen, Jundong Li, Jing Yang, Cong Shen

TMLR 2024 Federated Graph Learning with Graphless Clients Xingbo Fu, Song Wang, Yushun Dong, Binchi Zhang, Chen Chen, Jundong Li

NeurIPS 2024 Mixture of Demonstrations for In-Context Learning Song Wang, Zihan Chen, Chengshuai Shi, Cong Shen, Jundong Li

NeurIPSW 2024 On Demonstration Selection for Improving Fairness in Language Models Song Wang, Peng Wang, Yushun Dong, Tong Zhou, Lu Cheng, Yangfeng Ji, Jundong Li

ICML 2024 Towards Certified Unlearning for Deep Neural Networks Binchi Zhang, Yushun Dong, Tianhao Wang, Jundong Li

ICML 2024 Verification of Machine Unlearning Is Fragile Binchi Zhang, Zihan Chen, Cong Shen, Jundong Li

AAAI 2023 Interpreting Unfairness in Graph Neural Networks via Training Node Attribution Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li

IJCAI 2023 Learning Causal Effects on Hypergraphs (Extended Abstract) Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent J. Hecht, Jaime Teevan

TMLR 2023 Mind the Gap: Mitigating the Distribution Gap in Graph Few-Shot Learning Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang

NeurIPS 2022 BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H Chen, Zhihao Jia, Philip S Yu

NeurIPS 2022 CLEAR: Generative Counterfactual Explanations on Graphs Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li

NeurIPSW 2022 Contrastive Graph Few-Shot Learning Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang

IJCAI 2022 FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li

IJCAI 2022 Few-Shot Learning on Graphs Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu

NeurIPS 2022 Graph Few-Shot Learning with Task-Specific Structures Song Wang, Chen Chen, Jundong Li

ECML-PKDD 2022 SemiITE: Semi-Supervised Individual Treatment Effect Estimation via Disagreement-Based Co-Training Qiang Huang, Jing Ma, Jundong Li, Huiyan Sun, Yi Chang

LoG 2022 Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification Zhen Tan, Song Wang, Kaize Ding, Jundong Li, Huan Liu

NeurIPS 2022 TwiBot-22: Towards Graph-Based Twitter Bot Detection Shangbin Feng, Zhaoxuan Tan, Herun Wan, Ningnan Wang, Zilong Chen, Binchi Zhang, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo

IJCAI 2021 Multi-Cause Effect Estimation with Disentangled Confounder Representation Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li

IJCAI 2020 IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data Ruocheng Guo, Jundong Li, Yichuan Li, K. Selçuk Candan, Adrienne Raglin, Huan Liu

IJCAI 2020 Inductive Anomaly Detection on Attributed Networks Kaize Ding, Jundong Li, Nitin Agarwal, Huan Liu

AAAI 2020 Tracking Disaster Footprints with Social Streaming Data Lu Cheng, Jundong Li, K. Selçuk Candan, Huan Liu

IJCAI 2019 InterSpot: Interactive Spammer Detection in Social Media Kaize Ding, Jundong Li, Shivam Dhar, Shreyash Devan, Huan Liu

IJCAI 2019 PI-Bully: Personalized Cyberbullying Detection with Peer Influence Lu Cheng, Jundong Li, Yasin N. Silva, Deborah L. Hall, Huan Liu

IJCAI 2018 ANOMALOUS: A Joint Modeling Approach for Anomaly Detection on Attributed Networks Zhen Peng, Minnan Luo, Jundong Li, Huan Liu, Qinghua Zheng

IJCAI 2018 INITIATOR: Noise-Contrastive Estimation for Marked Temporal Point Process Ruocheng Guo, Jundong Li, Huan Liu

AAAI 2018 Personalized Privacy-Preserving Social Recommendation Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, Yujun Zhang

AAAI 2018 Unsupervised Personalized Feature Selection Jundong Li, Liang Wu, Harsh Dani, Huan Liu

IJCAI 2017 Radar: Residual Analysis for Anomaly Detection in Attributed Networks Jundong Li, Harsh Dani, Xia Hu, Huan Liu

IJCAI 2017 Reconstruction-Based Unsupervised Feature Selection: An Embedded Approach Jundong Li, Jiliang Tang, Huan Liu

ECML-PKDD 2017 Sentiment Informed Cyberbullying Detection in Social Media Harsh Dani, Jundong Li, Huan Liu

AAAI 2017 Unsupervised Sentiment Analysis with Signed Social Networks Kewei Cheng, Jundong Li, Jiliang Tang, Huan Liu

IJCAI 2016 Multi-Label Informed Feature Selection Ling Jian, Jundong Li, Kai Shu, Huan Liu