Yang Li (郦洋)

@article{li2024fastt2t,
  title = {Fast T2T: Optimization Consistency Speeds Up Diffusion-Based Training-to-Testing Solving for Combinatorial Optimization},
  author = {Li*, Yang and Guo*, Jinpei and Wang, Runzhong and Zha, Hongyuan and Yan, Junchi},
  journal = {Advances in Neural Information Processing Systems},
  year = {2024}
}

@article{zheng2024learning,
  title = {Learning Plaintext-Ciphertext Cryptographic Problems via ANF-based SAT Instance Representation},
  author = {Zheng, Xinhao and Li, Yang and Fan, Cunxin and Wu, Huaijin and Song, Xinhao and Yan, Junchi},
  journal = {Advances in Neural Information Processing Systems},
  year = {2024}
}

@article{geng2024rethinking,
  title = {There is No Silver Bullet: Benchmarking Methods in Predictive Combinatorial Optimization},
  author = {Geng, Haoyu and Ruan, Hang and Wang, Runzhong and Li, Yang and Wang, Yang and Chen, Lei and Yan, Junchi},
  journal = {Advances in Neural Information Processing Systems},
  year = {2024}
}

@article{wang2024learning,
  title = {Learning to Solve Combinatorial Optimization under Positive Linear Constraints via Non-Autoregressive Neural Networks},
  author = {Wang, Runzhong and Li, Yang and Yan, Junchi and Yang, Xiaokang},
  journal = {SCIENTIA SINICA Informationis 2024},
  year = {2024}
}

@inproceedings{guo2024acm,
  title = {ACM-MILP: Adaptive Constraint Modification via Grouping and Selection for Hardness-Preserving MILP Instance Generation},
  author = {Guo, Ziao and Li, Yang and Liu, Chang and Ouyang, Wenli and Yan, Junchi},
  booktitle = {The Forty-first International Conference on Machine Learning},
  year = {2024},
}

@inproceedings{chen2024mixsat,
  title = {MixSATGEN: Learning Graph Mixing for SAT Instance Generation},
  author = {Chen*, Xinyan and Li*, Yang and Wang, Runzhong and Yan, Junchi},
  booktitle = {The Twelfth International Conference on Learning Representations},
  year = {2024},
}

@article{li2024machine,
  title = {Machine Learning Insides OptVerse AI Solver: Design Principles and Applications},
  author = {Li, Xijun and Zhu, Fangzhou and Zhen, Hui-Ling and Luo, Weilin and Lu, Meng and Huang, Yimin and Fan, Zhenan and Zhou, Zirui and Kuang, Yufei and Wang, Zhihai and Geng, Zijie and Li, Yang and Liu, Haoyang and An, Zhiwu and Yang, Muming and Li, Jianshu and Wang, Jie and Yan, Junchi and Sun, Defeng and Zhong, Tao and Zhang, Yong and Zeng, Jia and Yuan, Mingxuan and Hao, Jianye and Yao, Jun and Mao, Kun},
  year = {2024},
  journal = {arXiv preprint},
}

@article{yang2024molecule,
  title = {Molecule Generation for Drug Design: a Graph Learning Perspective},
  author = {Yang, Nianzu and Wu, Huaijin and Zeng, Kaipeng and Li, Yang and Yan, Junchi},
  year = {2024},
  journal = {arXiv preprint},
}

@inproceedings{li2023t2tco,
  title = {T2T: From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization},
  author = {Li, Yang and Guo, Jinpei and Wang, Runzhong and Yan, Junchi},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2023}
}

@inproceedings{li2023hardsatgen,
  title = {HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline},
  author = {Li, Yang and Chen, Xinyan and Guo, Wenxuan and Li, Xijun and Luo, Wanqian and Huang, Junhua and Zhen, Hui-Ling and Yuan, Mingxuan and Yan, Junchi},
  booktitle = {Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
  year = {2023}
}

@inproceedings{iid2023li,
  author = {Li*, Yang and Shi*, Liangliang and Yan, Junchi},
  booktitle = {Proceedings of the 32nd International Joint Conference on Artificial Intelligence},
  title = {IID-GAN: an IID Sampling Perspective for Regularizing Mode Collapse},
  year = {2023}
}

@inproceedings{li2022improving,
  author = {Li, Yang and Mo, Yichuan and Shi, Liangliang and Yan, Junchi},
  booktitle = {Advances in Neural Information Processing Systems},
  editor = {Koyejo, S. and Mohamed, S. and Agarwal, A. and Belgrave, D. and Cho, K. and Oh, A.},
  pages = {8868--8881},
  publisher = {Curran Associates, Inc.},
  title = {Improving Generative Adversarial Networks via Adversarial Learning in Latent Space},
  volume = {35},
  year = {2022}
}

@inproceedings{NEURIPS2022_a8b8c1ad,
  author = {Cheng, Ruoyu and Lyu, Xianglong and Li, Yang and Ye, Junjie and Hao, Jianye and Yan, Junchi},
  booktitle = {Advances in Neural Information Processing Systems},
  editor = {Koyejo, S. and Mohamed, S. and Agarwal, A. and Belgrave, D. and Cho, K. and Oh, A.},
  pages = {26350--26362},
  publisher = {Curran Associates, Inc.},
  title = {The Policy-gradient Placement and Generative Routing Neural Networks for Chip Design},
  volume = {35},
  year = {2022}
}

@article{li2022kissat,
  title = {Kissat Adaptive Restart, Kissat Cfexp: Adaptive Restart Policy and Variable Scoring Improvement},
  author = {Li, Yang and Jia, Yuqi and Luo, Wanqian and Zhen, Hui-Ling and Li, Xijun and Yuan, Mingxuan and Yan, Junchi},
  journal = {Proceedings of SAT Competition},
  year = {2022}
}

@article{li2022sat,
  title = {The SAT Encoding for Graph Isomorphism},
  author = {Li, Yang and Jia, Yuqi and Luo, Wanqian and Zhen, Hui-Ling and Li, Xijun and Yuan, Mingxuan and Yan, Junchi},
  journal = {Proceedings of SAT Competition},
  year = {2022}
}