Accelerating Spectrum Sharing Algorithms for Cognitive Radio Transmitters in a Momentum Q-Learning Approach. - Lianghui Zhu; Zhanke Zhou; Zhaochuan Peng; Xiaojun Hei (SimuTools (1), 2020)

Enhancing WiFi Multiple Access Performance with Federated Deep Reinforcement Learning. - Lyutianyang Zhang; Hao Yin; Zhanke Zhou; Sumit Roy 001; Yaping Sun (VTC Fall, 2020)

AutoSF+: Towards Automatic Scoring Function Design for Knowledge Graph Embedding. - Yongqi Zhang; Zhanke Zhou; Quanming Yao (CoRR, 2021)

Efficient Hyper-parameter Search for Knowledge Graph Embedding. - Yongqi Zhang; Zhanke Zhou; Quanming Yao; Yong Li 008 (ACL (1), 2022)

KGTuner: Efficient Hyper-parameter Search for Knowledge Graph Learning. - Yongqi Zhang; Zhanke Zhou; Quanming Yao; Yong Li 008 (CoRR, 2022)

Learning Adaptive Propagation for Knowledge Graph Reasoning. - Yongqi Zhang; Zhanke Zhou; Quanming Yao; Xiaowen Chu 001; Bo Han 003 (CoRR, 2022)

On Strengthening and Defending Graph Reconstruction Attack with Markov Chain Approximation. - Zhanke Zhou; Chenyu Zhou; Xuan Li 005; Jiangchao Yao; Quanming Yao; Bo Han 003 (ICML, 2023)

AdaProp: Learning Adaptive Propagation for Graph Neural Network based Knowledge Graph Reasoning. - Yongqi Zhang; Zhanke Zhou; Quanming Yao; Xiaowen Chu 001; Bo Han 003 (KDD, 2023)

Combating Bilateral Edge Noise for Robust Link Prediction. - Zhanke Zhou; Jiangchao Yao; Jiaxu Liu; Xiawei Guo; Quanming Yao; Li He; Liang Wang 001; Bo Zheng 007; Bo Han 003 (NeurIPS, 2023)

Long-Range Neural Atom Learning for Molecular Graphs. - Xuan Li 005; Zhanke Zhou; Jiangchao Yao; Yu Rong 001; Lu Zhang 060; Bo Han 003 (CoRR, 2023)

DeepInception: Hypnotize Large Language Model to Be Jailbreaker. - Xuan Li 005; Zhanke Zhou; Jianing Zhu; Jiangchao Yao; Tongliang Liu; Bo Han 003 (CoRR, 2023)

Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel. - Xuan Li 005; Zhanke Zhou; Jiangchao Yao; Yu Rong 001; Lu Zhang 060; Bo Han 003 (ICLR, 2024)

Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs. - Zhanke Zhou; Yongqi Zhang; Jiangchao Yao; Quanming Yao; Bo Han 003 (ICLR, 2024)

Envisioning Outlier Exposure by Large Language Models for Out-of-Distribution Detection. - Chentao Cao; Zhun Zhong; Zhanke Zhou; Yang Liu 018; Tongliang Liu; Bo Han 003 (ICML, 2024)

Mind the Gap Between Prototypes and Images in Cross-domain Finetuning. - Hongduan Tian; Feng Liu 003; Zhanke Zhou; Tongliang Liu; Chengqi Zhang; Bo Han 003 (NeurIPS, 2024)

Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales? - Zhanke Zhou; Rong Tao; Jianing Zhu; Yiwen Luo; Zengmao Wang; Bo Han 003 (NeurIPS, 2024)

Model Inversion Attacks: A Survey of Approaches and Countermeasures. - Zhanke Zhou; Jianing Zhu; Fengfei Yu; Xuan Li 005; Xiong Peng; Tongliang Liu; Bo Han 003 (CoRR, 2024)

Understanding Fairness Surrogate Functions in Algorithmic Fairness. - Wei Yao 017; Zhanke Zhou; Zhicong Li; Bo Han 003; Yong Liu (Trans. Mach. Learn. Res., 2024)

Eliciting Causal Abilities in Large Language Models for Reasoning Tasks. - Yajing Wang; Zongwei Luo; Jingzhe Wang; Zhanke Zhou; Yongqiang Chen; Bo Han (AAAI, 2025)

Physics Reasoner: Knowledge-Augmented Reasoning for Solving Physics Problems with Large Language Models. - Xinyu Pang; Ruixin Hong; Zhanke Zhou; Fangrui Lv; Xinwei Yang; Zhilong Liang; Bo Han 003; Changshui Zhang (COLING, 2025)

Noisy Test-Time Adaptation in Vision-Language Models. - Chentao Cao; Zhun Zhong; Zhanke Zhou; Tongliang Liu; Yang Liu 018; Kun Zhang 001; Bo Han 003 (ICLR, 2025)

Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond. - Qizhou Wang; Jin Peng Zhou; Zhanke Zhou; Saebyeol Shin; Bo Han 003; Kilian Q. Weinberger (ICLR, 2025)

Landscape of Thoughts: Visualizing the Reasoning Process of Large Language Models. - Zhanke Zhou; Zhaocheng Zhu; Xuan Li 005; Mikhail Galkin 001; Xiao Feng 003; Sanmi Koyejo; Jian Tang 005; Bo Han 003 (CoRR, 2025)

SATBench: Benchmarking LLMs' Logical Reasoning via Automated Puzzle Generation from SAT Formulas. - Anjiang Wei; Yuheng Wu; Yingjia Wan; Tarun Suresh; Huanmi Tan; Zhanke Zhou; Sanmi Koyejo; Ke Wang; Alex Aiken (CoRR, 2025)

From Debate to Equilibrium: Belief-Driven Multi-Agent LLM Reasoning via Bayesian Nash Equilibrium. - Xie Yi; Zhanke Zhou; Chentao Cao; Qiyu Niu; Tongliang Liu; Bo Han 003 (CoRR, 2025)

From Passive to Active Reasoning: Can Large Language Models Ask the Right Questions under Incomplete Information? - Zhanke Zhou; Xiao Feng 003; Zhaocheng Zhu; Jiangchao Yao; Sanmi Koyejo; Bo Han 003 (CoRR, 2025)

Co-Reward: Self-supervised Reinforcement Learning for Large Language Model Reasoning via Contrastive Agreement. - Zizhuo Zhang; Jianing Zhu; Xinmu Ge; Zihua Zhao; Zhanke Zhou; Xuan Li 005; Xiao Feng 003; Jiangchao Yao; Bo Han 003 (CoRR, 2025)