Xi Lin

Affiliations

City University of Hong Kong

papers

568

total citations

papers (15)

Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model

ICML 2024arXiv

196

citations

Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization

NEURIPS 2023arXiv

150

citations

Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems

ICLR 2025

citations

What Makes Good Collaborative Views? Contrastive Mutual Information Maximization for Multi-Agent Perception

AAAI 2024arXiv

citations

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

ICLR 2025arXiv

citations

Rethinking Pseudo-Label Guided Learning for Weakly Supervised Temporal Action Localization from the Perspective of Noise Correction

AAAI 2025arXiv

citations

Pareto Continual Learning: Preference-Conditioned Learning and Adaption for Dynamic Stability-Plasticity Trade-off

AAAI 2025arXiv

citations

Learning to Insert for Constructive Neural Vehicle Routing Solver

NEURIPS 2025arXiv

citations

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

AAAI 2025

citations

Seeing Beyond Noise: Joint Graph Structure Evaluation and Denoising for Multimodal Recommendation

AAAI 2025

citations

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

CVPR 2025arXiv

citations

Hypervolume Maximization: A Geometric View of Pareto Set Learning

NEURIPS 2023

citations

Xi Lin

Affiliations

papers (15)

Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model

Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization

Pareto Set Learning for Expensive Multi-Objective Optimization

Multi-Objective Evolution of Heuristic Using Large Language Model

Smooth Tchebycheff Scalarization for Multi-Objective Optimization

Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems

What Makes Good Collaborative Views? Contrastive Mutual Information Maximization for Multi-Agent Perception

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

Rethinking Pseudo-Label Guided Learning for Weakly Supervised Temporal Action Localization from the Perspective of Noise Correction

Pareto Continual Learning: Preference-Conditioned Learning and Adaption for Dynamic Stability-Plasticity Trade-off

Learning to Insert for Constructive Neural Vehicle Routing Solver

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

Seeing Beyond Noise: Joint Graph Structure Evaluation and Denoising for Multimodal Recommendation

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

Hypervolume Maximization: A Geometric View of Pareto Set Learning

papers (15)

Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model

Neural Combinatorial Optimization with Heavy Decoder: Toward Large Scale Generalization

Pareto Set Learning for Expensive Multi-Objective Optimization

Multi-Objective Evolution of Heuristic Using Large Language Model

Smooth Tchebycheff Scalarization for Multi-Objective Optimization

Boosting Neural Combinatorial Optimization for Large-Scale Vehicle Routing Problems

What Makes Good Collaborative Views? Contrastive Mutual Information Maximization for Multi-Agent Perception

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

Rethinking Pseudo-Label Guided Learning for Weakly Supervised Temporal Action Localization from the Perspective of Noise Correction

Pareto Continual Learning: Preference-Conditioned Learning and Adaption for Dynamic Stability-Plasticity Trade-off

Learning to Insert for Constructive Neural Vehicle Routing Solver

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

Seeing Beyond Noise: Joint Graph Structure Evaluation and Denoising for Multimodal Recommendation

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

Hypervolume Maximization: A Geometric View of Pareto Set Learning