| 2025 | ICLR | How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension. | Xinnan Dai, Haohao Qu, Yifei Shen, Bohang Zhang, Qihao Wen, Wenqi Fan, Dongsheng Li, Jiliang Tang, Caihua Shan |
| 2025 | ICLR | Homomorphism Expressivity of Spectral Invariant Graph Neural Networks. | Jingchu Gai, Yiheng Du, Bohang Zhang, Haggai Maron, Liwei Wang |
| 2025 | ICML | Beyond Atoms: Enhancing Molecular Pretrained Representations with 3D Space Modeling. | Shuqi Lu, Xiaohong Ji, Bohang Zhang, Lin Yao, Siyuan Liu, Zhifeng Gao, Linfeng Zhang, Guolin Ke |
| 2024 | ICLR | Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness. | Bohang Zhang, Jingchu Gai, Yiheng Du, Qiwei Ye, Di He, Liwei Wang |
| 2024 | ICML | Do Efficient Transformers Really Save Computation? | Kai Yang, Jan Ackermann, Zhenyu He, Guhao Feng, Bohang Zhang, Yunzhen Feng, Qiwei Ye, Di He, Liwei Wang |
| 2024 | ICML | On the Expressive Power of Spectral Invariant Graph Neural Networks. | Bohang Zhang, Lingxiao Zhao, Haggai Maron |
| 2023 | ICLR | Rethinking the Expressive Power of GNNs via Graph Biconnectivity. | Bohang Zhang, Shengjie Luo, Liwei Wang, Di He |
| 2023 | ICML | Finding Generalization Measures by Contrasting Signal and Noise. | Jiaye Teng, Bohang Zhang, Ruichen Li, Haowei He, Yequan Wang, Yan Tian, Yang Yuan |
| 2023 | ICML | A Complete Expressiveness Hierarchy for Subgraph GNNs via Subgraph Weisfeiler-Lehman Tests. | Bohang Zhang, Guhao Feng, Yiheng Du, Di He, Liwei Wang |
| 2023 | IWCMC | Enhanced Sliding Window Superposition Coding for Industrial Automation. | Bohang Zhang, Zhaojun Nan, Sheng Zhou, Zhisheng Niu |
| 2022 | ICLR | Boosting the Certified Robustness of L-infinity Distance Nets. | Bohang Zhang, Du Jiang, Di He, Liwei Wang |
| 2021 | ICML | Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons. | Bohang Zhang, Tianle Cai, Zhou Lu, Di He, Liwei Wang |