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Xi Lin (林熙) Xi Lin is an incoming full professor in the School of Mathematics and Statistics at Xi'an Jiaotong University. He was a postdoctoral research fellow in the Department of Computer Science at City University of Hong Kong, working with Prof. Qingfu Zhang. He received the B.Sc. degree from South China University of Technology, the M.A. degree from Columbia University, and the Ph.D. degree from City University of Hong Kong under the supervision of Prof. Qingfu Zhang and Prof. Sam Kwong. His research interests include multi-objective optimization, learning-based optimization, multi-task learning, and evolutionary computation. His work has been published in top-tier machine learning conferences such as ICML, NeurIPS, and ICLR. He serves as an Area Chair for NeurIPS and ICLR, and as an Action Editor for the Transactions on Machine Learning Research (TMLR). He regularly reviews for numerous machine learning and evolutionary computation conferences and journals, and has received several outstanding reviewer awards from ICML, ICLR and TMLR. |
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Selected Publications(*: equal contribution, __: student first author I co-mentor, full list: Google Scholar) |
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CoEvo: Continual Evolution of Symbolic Solutions Using Large Language Models
Ping Guo, Qingfu Zhang, Xi Lin Annual AAAI Conference on Artificial Intelligence (AAAI) , 2026 pdf / arXiv |
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Robust Causal Discovery under Imperfect Structural Constraints
Zidong Wang, Xi Lin, Chuchao He, Xiaoguang Gao Annual AAAI Conference on Artificial Intelligence (AAAI) , 2026 (Oral Presentation) Coming Soon |
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Neural Evolution Strategy for Black-box Pareto Set Learning
Chengyu Lu, Zhenhua Li, Xi Lin, Ji Cheng, Qingfu Zhang Advances in Neural Information Processing Systems (NeurIPS) , 2025 pdf / openreview |
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Learning to Insert for Constructive Neural Vehicle Routing Solver
Fu Luo, Xi Lin, Mengyuan Zhong, Fei Liu, Zhenkun Wang, Jianyong Sun, Qingfu Zhang Advances in Neural Information Processing Systems (NeurIPS) , 2025 pdf / arXiv / openreview |
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TS-MOF: Two-Stage Multi-Objective Fine-tuning for Long-Tailed Recognition
Zhe Zhao, Zhiheng Gong, Pengkun Wang, HaiBin Wen, Cankun Guo, Bo Xue, Xi Lin, Zhenkun Wang, Qingfu Zhang, Yang Wang Advances in Neural Information Processing Systems (NeurIPS) , 2025 pdf / openreview |
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Gradient-Guided Epsilon Constraint Method for Online Continual Learning
Song Lai, Changyi Ma, Fei Zhu, Zhe Zhao, Xi Lin, Gaofeng Meng, Qingfu Zhang Advances in Neural Information Processing Systems (NeurIPS) , 2025 pdf / openreview |
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MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework
Ping Guo, Cheng Gong, Fei Liu, Xi Lin, Zhichao Lu, Qingfu Zhang, Zhenkun Wang IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2025 pdf / arXiv |
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Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization
Xi Lin, Yilu Liu, Xiaoyuan Zhang, Fei Liu, Zhenkun Wang, Qingfu Zhang International Conference on Learning Representations (ICLR) , 2025 pdf / arXiv / openreview |
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Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems
Fu Luo, Xi Lin, Yaoxin Wu, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang International Conference on Learning Representations (ICLR) , 2025 pdf / openreview |
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Dealing with Structure Constraints in Evolutionary Pareto Set Learning
Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Qingfu Zhang IEEE Transactions on Evolutionary Computation (TEVC) , 2025 pdf / arXiv |
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Multi-Objective Evolution of Heuristic Using Large Language Model
Shunyu Yao*, Fei Liu*, Xi Lin, Zhichao Lu, Zhenkun Wang, Qingfu Zhang Annual AAAI Conference on Artificial Intelligence (AAAI) , 2025 (Oral Presentation, Top 4.62% among All Submissions) pdf / arXiv |
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Multiple Trade-offs: An Improved Approach for Lexicographic Linear Bandits
Bo Xue, Xi Lin, Xiaoyuan Zhang, Qingfu Zhang Annual AAAI Conference on Artificial Intelligence (AAAI) , 2025 (Oral Presentation, Top 4.62% among All Submissions) archives |
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Pareto Continual Learning: Preference-Conditioned Learning and Adaption for Dynamic Stability-Plasticity Trade-off
Song Lai, Zhe Zhao, Fei Zhu, Xi Lin, Qingfu Zhang, Gaofeng Meng Annual AAAI Conference on Artificial Intelligence (AAAI) , 2025 pdf / arXiv / code |
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Gliding over the Pareto Front with Uniform Designs
Xiaoyuan Zhang, Genghui Li, Xi Lin, Yichi Zhang, Yifan Chen, Qingfu Zhang Advances in Neural Information Processing Systems (NeurIPS) , 2024 pdf / openreview |
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Smooth Tchebycheff Scalarization for Multi-Objective Optimization
Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Fei Liu, Zhenkun Wang, Qingfu Zhang International Conference on Machine Learning (ICML), 2024 pdf / arXiv / openreview / code |
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Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model
Fei Liu, Xialiang Tong, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, Qingfu Zhang International Conference on Machine Learning (ICML), 2024 (Oral Presentation, Top 1.49% among All Submissions) pdf / arXiv / openreview / code |
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Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization
Fei Liu, Xi Lin, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024 pdf / arXiv / code |
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Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization
Fu Luo*, Xi Lin*, Fei Liu, Qingfu Zhang, Zhenkun Wang Advances in Neural Information Processing Systems (NeurIPS) , 2023 pdf / arXiv / openreview / code |
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Hypervolume Maximization: A Geometric View of Pareto Set Learning
Xiaoyuan Zhang, Xi Lin, Bo Xue, Yifan Chen, Qingfu Zhang Advances in Neural Information Processing Systems (NeurIPS) , 2023 pdf / openreview |
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Continuation Path Learning for Homotopy Optimization
Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang International Conference on Machine Learning (ICML), 2023 (Oral Presentation, Top 2.37% among All Submissions) pdf / arXiv / openreview / code |
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Pareto Set Learning for Expensive Multi-Objective Optimization
Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang Advances in Neural Information Processing Systems (NeurIPS) , 2022 pdf / arXiv / openreview / code |
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Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization
Xi Lin, Zhiyuan Yang, Qingfu Zhang International Conference on Learning Representations (ICLR) , 2022 pdf / arXiv / openreview / code |
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Controllable Pareto Multi-Task Learning
Xi Lin, Zhiyuan Yang, Qingfu Zhang, Sam Kwong Technical Report, 2020 pdf / arXiv |
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Pareto Multi-Task Learning
Xi Lin, Hui-Ling Zhen, Zhenhua Li, Qingfu Zhang, Sam Kwong Advances in Neural Information Processing Systems (NeurIPS) , 2019 pdf / arXiv / proceedings / code |
Surveys |
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Gradient-Based Multi-Objective Deep Learning: Algorithms, Theories, Applications, and Beyond
Weiyu Chen*, Xiaoyuan Zhang*, Baijiong Lin*, Xi Lin, Han Zhao, Qingfu Zhang, James T. Kwok pdf / arXiv |
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A Systematic Survey on Large Language Models for Algorithm Design
Fei Liu, Yiming Yao, Ping Guo, Zhiyuan Yang, Xi Lin, Xialiang Tong, Mingxuan Yuan, Zhichao Lu, Zhenkun Wang, Qingfu Zhang pdf / arXiv |
Packages(Please also refer to the codes above for each work.) |
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LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch
Xiaoyuan Zhang*, Liang Zhao*, Yingying Yu*, Xi Lin, Zhenkun Wang, Han Zhao, Qingfu Zhang Advances in Neural Information Processing Systems (NeurIPS) , 2024 pdf / arXiv / code |
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LLM4AD: A Platform for Algorithm Design with Large Language Model
Fei Liu*, Rui Zhang*, Zhuoliang Xie, Rui Sun, Kai Li, Xi Lin, Zhenkun Wang, Zhichao Lu, Qingfu Zhang pdf / arXiv / code |
Academic Service |
| Area Chair: NeurIPS, ICLR |
| Action Editor (aka Associate Editor): Transactions on Machine Learning Research (TMLR) |
| Conference Reviewer: ICML, ICLR, NeurIPS, AISTATS, IJCAI, GECCO, CEC, SSCI |
| Journal Reviewer: JMLR, TMLR, TEVC, TCYB, TNNLS, TAI, TETCI, NN, SWEVO, COR |
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Awards:
Notable Reviewer, ICLR 2025 Expert Reviewer, TMLR 2023 Outstanding Reviewer, ICML 2021, ICML 2022 Highlighted Reviewer, ICLR 2022 |
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This website's source code is adapted from Jon Barron's public academic website. |