Haoyang Liu

According to our database, Haoyang Liu authored at least 16 papers between 2023 and 2026.

Collaborative distances:

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

2026

Opt-Verifier: Unleashing the Power of LLMs for Optimization Modeling via Dual-Side Verification.

Haoyang Liu, Jie Wang, Boxuan Niu, Xiongwei Han, Yian Xu, Mingxuan Ye, Zijie Geng, Fangzhou Zhu, Tao Zhong, Mingxuan Yuan, Jianye Hao

CoRR, May, 2026

Collaborative Multi-Agent Optimization for Personalized Memory System.

Wenyu Mao, Haoyang Liu, Zhao Liu, Haosong Tan, Yaorui Shi, Jiancan Wu, An Zhang, Xiang Wang

CoRR, March, 2026

Invariant graph learning meets information bottleneck for out-of-distribution generalization.

Wenyu Mao, Jiancan Wu, Haoyang Liu, Yongduo Sui, Xiang Wang

Frontiers Comput. Sci., January, 2026

Bi-Mem: Bidirectional Construction of Hierarchical Memory for Personalized LLMs via Inductive-Reflective Agents.

Wenyu Mao, Haosong Tan, Shuchang Liu, Haoyang Liu, Yifan Xu, Huaxiang Ji, Xiang Wang

CoRR, January, 2026

CoCo-MILP: Inter-Variable Contrastive and Intra-Constraint Competitive MILP Solution Prediction.

Tianle Pu, Jianing Li, Yingying Gao, Shixuan Liu, Zijie Geng, Haoyang Liu, Chao Chen, Changjun Fan

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

RoME: Domain-Robust Mixture-of-Experts for MILP Solution Prediction across Domains.

Tianle Pu, Zijie Geng, Haoyang Liu, Shixuan Liu, Jie Wang, Li Zeng, Chao Chen, Changjun Fan

CoRR, November, 2025

Distinguished Quantized Guidance for Diffusion-based Sequence Recommendation.

Wenyu Mao, Shuchang Liu, Haoyang Liu, Haozhe Liu, Xiang Li, Lanatao Hu

CoRR, January, 2025

Distinguished Quantized Guidance for Diffusion-based Sequence Recommendation.

Wenyu Mao, Shuchang Liu, Haoyang Liu, Haozhe Liu, Xiang Li, Lantao Hu

Proceedings of the ACM on Web Conference 2025, 2025

OptiTree: Hierarchical Thoughts Generation with Tree Search for LLM Optimization Modeling.

Haoyang Liu, Jie Wang, Yuyang Cai, Xiongwei Han, Yufei Kuang, Jianye Hao

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

Apollo-MILP: An Alternating Prediction-Correction Neural Solving Framework for Mixed-Integer Linear Programming.

Haoyang Liu, Jie Wang, Zijie Geng, Xijun Li, Yuxuan Zong, Fangzhou Zhu, Jianye Hao, Feng Wu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Machine Learning Insides OptVerse AI Solver: Design Principles and Applications.

Xijun Li, Fangzhou Zhu, Hui-Ling Zhen, Weilin Luo, Meng Lu, Yimin Huang, Zhenan Fan, Zirui Zhou, Yufei Kuang, Zhihai Wang, Zijie Geng, Yang Li, Haoyang Liu, Zhiwu An, Muming Yang, Jianshu Li, Jie Wang, Junchi Yan, Defeng Sun, Tao Zhong, Yong Zhang, Jia Zeng, Mingxuan Yuan, Jianye Hao, Jun Yao, Kun Mao

CoRR, 2024

MILP-StuDio: MILP Instance Generation via Block Structure Decomposition.

Haoyang Liu, Jie Wang, Wanbo Zhang, Zijie Geng, Yufei Kuang, Xijun Li, Bin Li, Yongdong Zhang, Feng Wu

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

Accelerating PDE Data Generation via Differential Operator Action in Solution Space.

Huanshuo Dong, Hong Wang, Haoyang Liu, Jian Luo, Jie Wang

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

Rethinking Branching on Exact Combinatorial Optimization Solver: The First Deep Symbolic Discovery Framework.

Yufei Kuang, Jie Wang, Haoyang Liu, Fangzhou Zhu, Xijun Li, Jia Zeng, Jianye Hao, Bin Li, Feng Wu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Deep Symbolic Optimization for Combinatorial Optimization: Accelerating Node Selection by Discovering Potential Heuristics.

Hongyu Liu, Haoyang Liu, Yufei Kuang, Jie Wang, Bin Li

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

2023

Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation.

Haoyang Liu, Yufei Kuang, Jie Wang, Xijun Li, Yongdong Zhang, Feng Wu

CoRR, 2023