@inproceedings{guo2026adaptive,
  title     = {Adaptive Code Watermarking Through Reinforcement Learning},
  author    = {Guo, Zhimeng and Zhu, Huaisheng and Xu, Siyuan and Zhang, Hangfan and Xiao, Teng and Cheng, Minhao},
  booktitle = {Forty-third International Conference on Machine Learning},
  year      = {2026}
}

@inproceedings{guo2025practical,
  title     = {Practical and Effective Code Watermarking for Large Language Models},
  author    = {Guo, Zhimeng and Cheng, Minhao},
  booktitle = {The Thirty-ninth Annual Conference on Neural Information Processing Systems},
  year      = {2025},
  url       = {https://openreview.net/forum?id=RpE4HeuX69}
}

@inproceedings{zhang2024jailbreak,
  title     = {Jailbreak open-sourced large language models via enforced decoding},
  author    = {Zhang, Hangfan and Guo, Zhimeng and Zhu, Huaisheng and Cao, Bochuan and Lin, Lu and Jia, Jinyuan and Chen, Jinghui and Wu, Dinghao},
  booktitle = {Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
  pages     = {5475--5493},
  year      = {2024}
}

@inproceedings{qian2024addressing,
  title     = {Addressing shortcomings in fair graph learning datasets: Towards a new benchmark},
  author    = {Qian, Xiaowei and Guo, Zhimeng and Li, Jialiang and Mao, Haitao and Li, Bingheng and Wang, Suhang and Ma, Yao},
  booktitle = {Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  pages     = {5602--5612},
  year      = {2024}
}

@inproceedings{xiao2024efficient,
  title     = {Efficient contrastive learning for fast and accurate inference on graphs},
  author    = {Xiao, Teng and Zhu, Huaisheng and Zhang, Zhiwei and Guo, Zhimeng and Aggarwal, Charu C. and Wang, Suhang and Honavar, Vasant G.},
  booktitle = {Forty-first International Conference on Machine Learning},
  year      = {2024}
}

@article{guo2023towards,
  title   = {Towards Fair Graph Neural Networks via Graph Counterfactual},
  author  = {Guo, Zhimeng and Li, Jialiang and Xiao, Teng and Ma, Yao and Wang, Suhang},
  journal = {arXiv preprint arXiv:2307.04937},
  year    = {2023}
}

@misc{guo2023counterfactual,
  title         = {Counterfactual Learning on Graphs: A Survey},
  author        = {Guo, Zhimeng and Xiao, Teng and Aggarwal, Charu and Liu, Hui and Wang, Suhang},
  year          = {2023},
  eprint        = {2304.01391},
  archivePrefix = {arXiv},
  primaryClass  = {cs.LG}
}

@article{zhu2023fairnessaware,
  title   = {Fairness-aware Message Passing for Graph Neural Networks},
  author  = {Zhu, Huaisheng and Fu, Guoji and Guo, Zhimeng and Zhang, Zhiwei and Xiao, Teng and Wang, Suhang},
  journal = {arXiv},
  year    = {2023},
  volume  = {abs/2306.11132}
}

@inproceedings{xiao2022decoupled,
  title     = {Decoupled Self-supervised Learning for Graphs},
  author    = {Xiao, Teng and Chen, Zhengyu and Guo, Zhimeng and Zhuang, Zeyang and Wang, Suhang},
  booktitle = {Conference on Neural Information Processing Systems (NeurIPS)},
  pages     = {620--634},
  volume    = {35},
  year      = {2022}
}