Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats. - Hongwei Jin; Zishun Yu; Xinhua Zhang (NeurIPS, 2022)

Orthogonal Gromov-Wasserstein discrepancy with efficient lower bound. - Hongwei Jin; Zishun Yu; Xinhua Zhang (UAI, 2022)

Slowly Changing Adversarial Bandit Algorithms are Provably Efficient for Discounted MDPs. - Ian A. Kash; Lev Reyzin; Zishun Yu (CoRR, 2022)

Deep Reinforcement Learning With Graph Representation for Vehicle Repositioning. - Zishun Yu; Mengqi Hu (IEEE Trans. Intell. Transp. Syst., 2022)

Actor-Critic Alignment for Offline-to-Online Reinforcement Learning. - Zishun Yu; Xinhua Zhang (ICML, 2023)

B-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis. - Zishun Yu; Yunzhe Tao; Liyu Chen; Tao Sun 008; Hongxia Yang (CoRR, 2023)

Slowly Changing Adversarial Bandit Algorithms are Efficient for Discounted MDPs. - Ian A. Kash; Lev Reyzin; Zishun Yu (ALT, 2024)

B-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis. - Zishun Yu; Yunzhe Tao; Liyu Chen; Tao Sun; Hongxia Yang (ICLR, 2024)

Offline Reward Perturbation Boosts Distributional Shift in Online RL. - Zishun Yu; Siteng Kang; Xinhua Zhang (UAI, 2024)

Towards Efficient Collaboration via Graph Modeling in Reinforcement Learning. - Wenzhe Fan; Zishun Yu; Chengdong Ma; Changye Li 003; Yaodong Yang 001; Xinhua Zhang (AAAI, 2025)

Think Smarter not Harder: Adaptive Reasoning with Inference Aware Optimization. - Zishun Yu; Tengyu Xu; Di Jin; Karthik Abinav Sankararaman; Yun He; Wenxuan Zhou; Zhouhao Zeng; Eryk Helenowski; Chen Zhu; Sinong Wang; Hao Ma; Han Fang (CoRR, 2025)

Language Model Distillation: A Temporal Difference Imitation Learning Perspective. - Zishun Yu; Shangzhe Li; Xinhua Zhang (CoRR, 2025)

Boosting LLM Reasoning via Spontaneous Self-Correction. - Xutong Zhao; Tengyu Xu; Xuewei Wang; Zhengxing Chen; Di Jin; Liang Tan; Yen-Ting; Zishun Yu; Zhuokai Zhao; Yun He; Sinong Wang; Han Fang; et al. (CoRR, 2025)