Yang Li (郦洋)

@inproceedings{li2025gensco,
  title = {Generation as Search Operator for Test-Time Scaling of Diffusion-based Combinatorial Optimization},
  author = {Li, Yang and Chen, Lvda and Wang, Haonan and Wang, Runzhong and Yan, Junchi},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2025}
}

@inproceedings{wang2025strudico,
  title = {StruDiCO: Structured Denoising Diffusion with Gradient-free Inference-stage Boosting for Memory and Time Efficient Combinatorial Optimization},
  author = {Wang, Yu and Li, Yang and Yan, Junchi and Chang, Yi},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2025}
}

@inproceedings{ma2025mlcobench,
  title = {ML4CO-Bench-101: Benchmark Machine Learning for Classic Combinatorial Problems on Graphs},
  author = {Ma, Jiale and Pan, Wenzheng and Li, Yang and Yan, Junchi},
  booktitle = {The Thirty-ninth Annual Conference on Neural Information Processing Systems Datasets and Benchmarks Track},
  year = {2025},
}

@inproceedings{li2025pcl,
  title = {Generative Modeling Reinvents Supervised Learning: Label Repurposing with Predictive Consistency Learning},
  author = {Li, Yang and Ma, Jiale and Yang, Yebin and Wu, Qitian and Zha, Hongyuan and Yan, Junchi},
  booktitle = {International Conference on Machine Learning},
  year = {2025}
}

@inproceedings{ma2025coexpander,
  title = {COExpander: Adaptive Solution Expansion for Combinatorial Optimization},
  author = {Ma, Jiale and Pan, Wenzheng and Li, Yang and Yan, Junchi},
  booktitle = {International Conference on Machine Learning},
  year = {2025}
}

@inproceedings{li2025ml4tsp,
  title = {Unify ML4TSP: Drawing Methodological Principles for TSP and Beyond from Streamlined Design Space of Learning and Search},
  author = {Li, Yang and Ma, Jiale and Pan, Wenzheng and Wang, Runzhong and Geng, Haoyu and Yang, Nianzu and Yan, Junchi},
  booktitle = {International Conference on Learning Representations},
  year = {2025}
}

@inproceedings{pan2025unico,
  author = {Pan, Wenzheng and Xiong, Hao and Ma, Jiale and Zhao, Wentao and Li, Yang and Yan, Junchi},
  booktitle = {International Conference on Learning Representations},
  year = {2025}
}

@inproceedings{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},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2024}
}

@inproceedings{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},
  booktitle = {Advances in Neural Information Processing Systems},
  year = {2024}
}

@inproceedings{geng2024rethinking,
  title = {Benchmarking PtO and PnO Methods in the Predictive Combinatorial Optimization Regime},
  author = {Geng, Haoyu and Ruan, Hang and Wang, Runzhong and Li, Yang and Wang, Yang and Chen, Lei and Yan, Junchi},
  booktitle = {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},
}

@inproceedings{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},
  booktitle = {Fundamental Research},
}

@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{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}
}