Zhiguang Cao
45 papers · 2020–2026 · 6 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (6) 🏃 Academic Marathon (5) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐝 Cross-Pollinator (10)
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Keyword Pioneer
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Conference Polyglot
(6)
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Dynamic Duo
(18)
👑
Triple Crown
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Grand Slam
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(13)
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Keyword Champion
(7)
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Century Club
(42)
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Prolific Year
(8)
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Unstoppable
(6)
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Keyword Collector
(111)
Conferences
NIPS (15)
AAAI (9)
ICLR (7)
ICML (6)
IJCAI (6)
UAI (2)
Top co-authors
Research topics
Keywords
vehicle routing problem
(11)
combinatorial optimization
(8)
graph neural network
(7)
traveling salesman problem
(7)
deep reinforcement learning
(7)
vehicle routing
(4)
reinforcement learning
(4)
evolutionary algorithm
(3)
black-box optimization
(3)
neural combinatorial optimization
(3)
domain generalization
(3)
attention mechanism
(3)
instance generation
(2)
ensemble learning
(2)
route optimization
(2)
distribution shift
(2)
integer programming
(2)
transformer architecture
(2)
multi-objective optimization
(2)
neural solver
(2)
Papers
Scale-Net: A Hierarchical U-Net Framework for Cross-Scale Generalization in Multi-Task Vehicle Routing
AAAI 2026
Instance Generation for Meta-Black-Box Optimization Through Latent Space Reverse Engineering
AAAI 2026
Bridging Synthetic and Real Routing Problems via LLM-Guided Instance Generation and Progressive Adaptation
AAAI 2026
DualOpt: A Dual Divide-and-Optimize Algorithm for the Large-scale Traveling Salesman Problem
AAAI 2025
Rethinking Neural Multi-Objective Combinatorial Optimization via Neat Weight Embedding
ICLR 2025
Preference-based Deep Reinforcement Learning for Historical Route Estimation
IJCAI 2025
EFormer: An Effective Edge-based Transformer for Vehicle Routing Problems
IJCAI 2025
Coupling Category Alignment for Graph Domain Adaptation
IJCAI 2025
Meta-Black-Box-Optimization through Offline Q-function Learning
ICML 2025
A Mixed-Curvature based Pre-training Paradigm for Multi-Task Vehicle Routing Solver
ICML 2025
SHIELD: Multi-task Multi-distribution Vehicle Routing Solver with Sparsity and Hierarchy
ICML 2025
Rethinking Light Decoder-based Solvers for Vehicle Routing Problems
ICLR 2025
Graph Assisted Offline-Online Deep Reinforcement Learning for Dynamic Workflow Scheduling
ICLR 2025
Neural Multi-Objective Combinatorial Optimization via Graph-Image Multimodal Fusion
ICLR 2025
Adversarial Generative Flow Network for Solving Vehicle Routing Problems
ICLR 2025
DGL: Dynamic Global-Local Information Aggregation for Scalable VRP Generalization with Self-Improvement Learning
IJCAI 2025
ConfigX: Modular Configuration for Evolutionary Algorithms via Multitask Reinforcement Learning
AAAI 2025
Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling
ICLR 2024
ReEvo: Large Language Models as Hyper-Heuristics with Reflective Evolution
NIPS 2024
Learning to Handle Complex Constraints for Vehicle Routing Problems
NIPS 2024
Collaboration! Towards Robust Neural Methods for Routing Problems
NIPS 2024
GLOP: Learning Global Partition and Local Construction for Solving Large-Scale Routing Problems in Real-Time
AAAI 2024
Adaptive Stabilization Based on Machine Learning for Column Generation
ICML 2024
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts
ICML 2024
Cross-Problem Learning for Solving Vehicle Routing Problems
IJCAI 2024
Learning Topological Representations with Bidirectional Graph Attention Network for Solving Job Shop Scheduling Problem
UAI 2024
Multi-view graph contrastive learning for solving vehicle routing problems
UAI 2023
Efficient Meta Neural Heuristic for Multi-Objective Combinatorial Optimization
NIPS 2023
Neural Multi-Objective Combinatorial Optimization with Diversity Enhancement
NIPS 2023
MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning
NIPS 2023
Towards Omni-generalizable Neural Methods for Vehicle Routing Problems
ICML 2023
Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift
NIPS 2023
Learning to Search Feasible and Infeasible Regions of Routing Problems with Flexible Neural k-Opt
NIPS 2023
DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization
NIPS 2023
Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation
NIPS 2022
Learning to Solve Routing Problems via Distributionally Robust Optimization
AAAI 2022
Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs
ICLR 2022
Efficient Neural Neighborhood Search for Pickup and Delivery Problems
IJCAI 2022
Graph Learning Assisted Multi-Objective Integer Programming
NIPS 2022
Multi-Decoder Attention Model with Embedding Glimpse for Solving Vehicle Routing Problems
AAAI 2021
NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem
NIPS 2021
Learning Large Neighborhood Search Policy for Integer Programming
NIPS 2021
Learning to Iteratively Solve Routing Problems with Dual-Aspect Collaborative Transformer
NIPS 2021
Learning to Dispatch for Job Shop Scheduling via Deep Reinforcement Learning
NIPS 2020
AATEAM: Achieving the Ad Hoc Teamwork by Employing the Attention Mechanism
AAAI 2020