Xi Lin

According to our database, Xi Lin authored at least 75 papers between 2016 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

A Systematic Survey on Large Language Models for Algorithm Design.

Fei Liu, Yiming Yao, Ping Guo, Zhiyuan Yang, Xi Lin, Zhe Zhao, Xialiang Tong, Kun Mao, Zhichao Lu, Zhenkun Wang, Mingxuan Yuan, Qingfu Zhang

ACM Comput. Surv., June, 2026

PMGDA: A Preference-Based Multiple Gradient Descent Algorithm.

Xiaoyuan Zhang, Xi Lin, Qingfu Zhang

IEEE Trans. Emerg. Top. Comput. Intell., April, 2026

Leader-Follower Disagreement Minimization in Social Networks.

Yilu Liu, Xi Lin, Qingfu Zhang

IEEE Trans. Evol. Comput., April, 2026

Few-for-Many Personalized Federated Learning.

Ping Guo, Tiantian Zhang, Xi Lin, Xiang Li, Zhi-Ri Tang, Qingfu Zhang

CoRR, March, 2026

Survey on Neural Routing Solvers.

Yunpeng Ba, Xi Lin, Changliang Zhou, Ruihao Zheng, Zhenkun Wang, Xinyan Liang, Zhichao Lu, Jianyong Sun, Yuhua Qian, Qingfu Zhang

CoRR, February, 2026

Quality-Diversity Optimization as Multi-Objective Optimization.

Xi Lin, Ping Guo, Yilu Liu, Qingfu Zhang, Jianyong Sun

CoRR, February, 2026

Timing-driven Detailed Placement via TimingMask-guided Path-level Optimization.

Ruo-Tong Chen, Chengrui Gao, Siyuan Xu, Ke Xue, Yunqi Shi, Xi Lin, Mingxuan Yuan, Chao Qian, Zhi-Hua Zhou

Proceedings of the Design, Automation & Test in Europe Conference, 2026

CoEvo: Continual Evolution of Symbolic Solutions Using Large Language Models.

Ping Guo, Qingfu Zhang, Xi Lin

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Rethinking Supervised Learning-Based Neural Combinatorial Optimization for Routing Problem.

Shunyu Yao, Xi Lin, Jiashu Wang, Qingfu Zhang, Zhenkun Wang

ACM Trans. Evol. Learn. Optim., December, 2025

Re²MaP: Macro Placement by Recursively Prototyping and Packing Tree-based Relocating

Yunqi Shi, Xi Lin, Zhiang Wang, Siyuan Xu, Shixiong Kai, Yao Lai, Chengrui Gao, Ke Xue, Mingxuan Yuan, Chao Qian, Zhi-Hua Zhou

CoRR, November, 2025

BBOPlace-Bench: Benchmarking Black-Box Optimization for Chip Placement.

Ke Xue, Ruo-Tong Chen, Rong-Xi Tan, Xi Lin, Yunqi Shi, Siyuan Xu, Mingxuan Yuan, Chao Qian

CoRR, October, 2025

EvoEngineer: Mastering Automated CUDA Kernel Code Evolution with Large Language Models.

Ping Guo, Chenyu Zhu, Siyuan Chen, Fei Liu, Xi Lin, Zhichao Lu, Qingfu Zhang

CoRR, October, 2025

URS: A Unified Neural Routing Solver for Cross-Problem Zero-Shot Generalization.

Changliang Zhou, Canhong Yu, Shunyu Yao, Xi Lin, Zhenkun Wang, Yu Zhou, Qingfu Zhang

CoRR, September, 2025

FoMEMO: Towards Foundation Models for Expensive Multi-objective Optimization.

Yiming Yao, Fei Liu, Liang Zhao, Xi Lin, Qingfu Zhang

CoRR, September, 2025

Fine-tuning Large Language Model for Automated Algorithm Design.

Fei Liu, Rui Zhang, Xi Lin, Zhichao Lu, Qingfu Zhang

CoRR, July, 2025

Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training.

Song Lai, Haohan Zhao, Rong Feng, Changyi Ma, Wenzhuo Liu, Hongbo Zhao, Xi Lin, Dong Yi, Min Xie, Qingfu Zhang, Hongbin Liu, Gaofeng Meng, Fei Zhu

CoRR, July, 2025

Dealing With Structure Constraints in Evolutionary Pareto Set Learning.

Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Qingfu Zhang

IEEE Trans. Evol. Comput., June, 2025

Exploring the Adversarial Frontier: Quantifying Robustness via Adversarial Hypervolume.

Ping Guo, Cheng Gong, Xi Lin, Zhiyuan Yang, Qingfu Zhang

IEEE Trans. Emerg. Top. Comput. Intell., April, 2025

From Understanding to Excelling: Template-Free Algorithm Design through Structural-Functional Co-Evolution.

Zhe Zhao, Haibin Wen, Pengkun Wang, Ye Wei, Zaixi Zhang, Xi Lin, Fei Liu, Bo An, Hui Xiong, Yang Wang, Qingfu Zhang

CoRR, March, 2025

L2R: Learning to Reduce Search Space for Generalizable Neural Routing Solver.

Changliang Zhou, Xi Lin, Zhenkun Wang, Qingfu Zhang

CoRR, March, 2025

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

CoRR, January, 2025

A Distributed Multi-Objective Detection Method for Multi-Sensor Systems With Unknown Local SNR.

Chang Gao, Qingfu Zhang, Pramod K. Varshney, Xi Lin, Hongwei Liu

IEEE Trans. Signal Process., 2025

Learning to Insert for Constructive Neural Vehicle Routing Solver.

Fu Luo, Xi Lin, Mengyuan Zhong, Fei Liu, Zhenkun Wang, Jianyong Sun, Qingfu Zhang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Neural Evolution Strategy for Black-box Pareto Set Learning.

Chengyu Lu, Zhenhua Li, Xi Lin, Ji Cheng, Qingfu Zhang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Gradient-Guided Epsilon Constraint Method for Online Continual Learning.

Song Lai, Changyi Ma, Fei Zhu, Zhe Zhao, Xi Lin, Gaofeng Meng, Qingfu Zhang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Problem-dependent Regret for Lexicographic Multi-Armed Bandits with Adversarial Corruptions.

Bo Xue, Xi Lin, Yuanyu Wan, Qingfu Zhang

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence, 2025

Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems.

Fu Luo, Xi Lin, Yaoxin Wu, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Few for Many: Tchebycheff Set Scalarization for Many-Objective Optimization.

Xi Lin, Yilu Liu, Xiaoyuan Zhang, Fei Liu, Zhenkun Wang, Qingfu Zhang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Large Language Model for Multiobjective Evolutionary Optimization.

Fei Liu, Xi Lin, Shunyu Yao, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang

Proceedings of the Evolutionary Multi-Criterion Optimization, 2025

Timing-Driven Global Placement by Efficient Critical Path Extraction.

Yunqi Shi, Siyuan Xu, Shixiong Kai, Xi Lin, Ke Xue, Mingxuan Yuan, Chao Qian

Proceedings of the Design, Automation & Test in Europe Conference, 2025

ReMaP: Macro Placement by Recursively Prototyping and Periphery-Guided Relocating.

Yunqi Shi, Xi Lin, Siyuan Xu, Shixiong Kai, Ke Xue, Mingxuan Yuan, Chao Qian, Zhi-Hua Zhou

Proceedings of the 62nd ACM/IEEE Design Automation Conference, 2025

MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework.

Ping Guo, Cheng Gong, Xi Lin, Fei Liu, Zhichao Lu, Qingfu Zhang, Zhenkun Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Multi-Objective Evolution of Heuristic Using Large Language Model.

Shunyu Yao, Fei Liu, Xi Lin, Zhichao Lu, Zhenkun Wang, Qingfu Zhang

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

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

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

Multiple Trade-offs: An Improved Approach for Lexicographic Linear Bandits.

Bo Xue, Xi Lin, Xiaoyuan Zhang, Qingfu Zhang

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Decomposition gradient descent method for bi-objective optimisation.

Jingjing Chen, Genghui Li, Xi Lin

Int. J. Bio Inspired Comput., 2024

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, Qinyu Zhang

CoRR, 2024

A Systematic Survey on Large Language Models for Algorithm Design.

Fei Liu, Yiming Yao, Ping Guo, Zhiyuan Yang, Zhe Zhao, Xi Lin, Xialiang Tong, Mingxuan Yuan, Zhichao Lu, Zhenkun Wang, Qingfu Zhang

CoRR, 2024

LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch.

Xiaoyuan Zhang, Liang Zhao, Yingying Yu, Xi Lin, Zhenkun Wang, Han Zhao, Qingfu Zhang

CoRR, 2024

Instance-Conditioned Adaptation for Large-scale Generalization of Neural Combinatorial Optimization.

Changliang Zhou, Xi Lin, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang

CoRR, 2024

Self-Improved Learning for Scalable Neural Combinatorial Optimization.

Fu Luo, Xi Lin, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang

CoRR, 2024

Exploring the Adversarial Frontier: Quantifying Robustness via Adversarial Hypervolume.

Ping Guo, Cheng Gong, Xi Lin, Zhiyuan Yang, Qingfu Zhang

CoRR, 2024

Escaping Local Optima in Global Placement.

Ke Xue, Xi Lin, Yunqi Shi, Shixiong Kai, Siyuan Xu, Chao Qian

CoRR, 2024

Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization.

Fei Liu, Xi Lin, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan

CoRR, 2024

UMOEA/D: A Multiobjective Evolutionary Algorithm for Uniform Pareto Objectives based on Decomposition.

Xiaoyuan Zhang, Xi Lin, Yichi Zhang, Yifan Chen, Qingfu Zhang

CoRR, 2024

L-AutoDA: Leveraging Large Language Models for Automated Decision-based Adversarial Attacks.

Ping Guo, Fei Liu, Xi Lin, Qingchuan Zhao, Qingfu Zhang

CoRR, 2024

PuriDefense: Randomized Local Implicit Adversarial Purification for Defending Black-box Query-based Attacks.

Ping Guo, Zhiyuan Yang, Xi Lin, Qingchuan Zhao, Qingfu Zhang

CoRR, 2024

An Example of Evolutionary Computation + Large Language Model Beating Human: Design of Efficient Guided Local Search.

Fei Liu, Xialiang Tong, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, Qingfu Zhang

CoRR, 2024

Understanding the Importance of Evolutionary Search in Automated Heuristic Design with Large Language Models.

Rui Zhang, Fei Liu, Xi Lin, Zhenkun Wang, Zhichao Lu, Qingfu Zhang

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

Many-Objective Cover Problem: Discovering Few Solutions to Cover Many Objectives.

Yilu Liu, Chengyu Lu, Xi Lin, Qingfu Zhang

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch.

Xiaoyuan Zhang, Liang Zhao, Yingying Yu, Xi Lin, Yifan Chen, Han Zhao, Qingfu Zhang

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Gliding over the Pareto Front with Uniform Designs.

Xiaoyuan Zhang, Genghui Li, Xi Lin, Yichi Zhang, Yifan Chen, Qingfu Zhang

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Reinforcement Learning Policy as Macro Regulator Rather than Macro Placer.

Ke Xue, Ruo-Tong Chen, Xi Lin, Yunqi Shi, Shixiong Kai, Siyuan Xu, Chao Qian

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Multi-Task Learning for Routing Problem with Cross-Problem Zero-Shot Generalization.

Fei Liu, Xi Lin, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Prompt Learning for Generalized Vehicle Routing.

Fei Liu, Xi Lin, Weiduo Liao, Zhenkun Wang, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

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

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Smooth Tchebycheff Scalarization for Multi-Objective Optimization.

Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Fei Liu, Zhenkun Wang, Qingfu Zhang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

L-AutoDA: Large Language Models for Automatically Evolving Decision-based Adversarial Attacks.

Ping Guo, Fei Liu, Xi Lin, Qingchuan Zhao, Qingfu Zhang

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

2023

Evolutionary Pareto Set Learning with Structure Constraints.

Xi Lin, Xiaoyuan Zhang, Zhiyuan Yang, Qingfu Zhang

CoRR, 2023

Large Language Model for Multi-objective Evolutionary Optimization.

Fei Liu, Xi Lin, Zhenkun Wang, Shunyu Yao, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang

CoRR, 2023

Hypervolume Maximization: A Geometric View of Pareto Set Learning.

Xiaoyuan Zhang, Xi Lin, Bo Xue, Yifan Chen, Qingfu Zhang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization.

Fu Luo, Xi Lin, Fei Liu, Qingfu Zhang, Zhenkun Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Continuation Path Learning for Homotopy Optimization.

Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang

Proceedings of the International Conference on Machine Learning, 2023

Approximation of a Pareto Set Segment Using a Linear Model with Sharing Variables.

Ping Guo, Qingfu Zhang, Xi Lin

Proceedings of the Evolutionary Multi-Criterion Optimization, 2023

2022

Pareto Set Learning for Expensive Multi-Objective Optimization.

Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization.

Xi Lin, Zhiyuan Yang, Qingfu Zhang

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Template NeRF: Towards Modeling Dense Shape Correspondences from Category-Specific Object Images.

Jianfei Guo, Zhiyuan Yang, Xi Lin, Qingfu Zhang

CoRR, 2021

2020

Fast Covariance Matrix Adaptation for Large-Scale Black-Box Optimization.

Zhenhua Li, Qingfu Zhang, Xi Lin, Hui-Ling Zhen

IEEE Trans. Cybern., 2020

Evolution strategies for continuous optimization: A survey of the state-of-the-art.

Zhenhua Li, Xi Lin, Qingfu Zhang, Hai-Lin Liu

Swarm Evol. Comput., 2020

Controllable Pareto Multi-Task Learning.

Xi Lin, Zhiyuan Yang, Qingfu Zhang, Sam Kwong

CoRR, 2020

2019

Pareto Multi-Task Learning.

Xi Lin, Hui-Ling Zhen, Zhenhua Li, Qingfu Zhang, Sam Kwong

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

A Batched Scalable Multi-Objective Bayesian Optimization Algorithm.

Xi Lin, Hui-Ling Zhen, Zhenhua Li, Qingfu Zhang, Sam Kwong

CoRR, 2018

Nonlinear Collaborative Scheme for Deep Neural Networks.

Hui-Ling Zhen, Xi Lin, Alan Z. Tang, Zhenhua Li, Qingfu Zhang, Sam Kwong

CoRR, 2018

2017

An efficient batch expensive multi-objective evolutionary algorithm based on Decomposition.

Xi Lin, Qingfu Zhang, Sam Kwong

Proceedings of the 2017 IEEE Congress on Evolutionary Computation, 2017

2016

A decomposition based multiobjective evolutionary algorithm with classification.

Xi Lin, Qingfu Zhang, Sam Kwong

Proceedings of the IEEE Congress on Evolutionary Computation, 2016