研究论文

Weizhe Lin, Xing Li, Zhiyuan Yang, Xiaojin Fu, Hui-Ling Zhen, Yaoyuan Wang, Xianzhi Yu, Wulong Liu, Xiaosong Li, Mingxuan Yuan (2025). TrimR: Verifier-based Training-Free Thinking Compression for Efficient Test-Time Scaling. arXiv preprint arXiv:2505.17155.

Hong Yankun, Li Xing, Zhen Hui-Ling, Yu Xianzhi, Liu Wulong, Yuan Mingxuan (2025). SVDq: 1.25-bit and 410x Key Cache Compression for LLM Attention. arXiv preprint arXiv:2502.15304.

Zehua Pei, Ying Zhang, Hui-Ling Zhen, Xianzhi Yu, Wulong Liu, Sinno Jialin Pan, Mingxuan Yuan, Bei Yu (2025). PreMoe: Lightening MoEs on Constrained Memory by Expert Pruning and Retrieval. arXiv preprint arXiv:2505.17639.

Bowei He, Lihao Yin, Hui-Ling Zhen, Xiaokun Zhang, Mingxuan Yuan, Chen Ma (2025). PASER: Post-Training Data Selection for Efficient Pruned Large Language Model Recovery. arXiv preprint arXiv:2502.12594.

Hanting Chen, Jiarui Qin, Jialong Guo, Tao Yuan, Yichun Yin, Huiling Zhen, Yasheng Wang, Jinpeng Li, Xiaojun Meng, Meng Zhang, Others (2025). Pangu Light: Weight Re-Initialization for Pruning and Accelerating LLMs. arXiv preprint arXiv:2505.20155.

Chen BAI, Peng Xu, Lihao Yin, Xianzhi Yu, Hui-Ling Zhen, Mingxuan Yuan, Tsung-Yi Ho, Bei Yu Hongduo Liu (2025). LLMShare: Optimizing LLM Inference Serving with Hardware Architecture Exploration. ACM/IEEE Design Automation Conference (DAC).

Fei Liu, Xi Lin, Shunyu Yao, Zhenkun Wang, Xialiang Tong, Mingxuan Yuan, Qingfu Zhang (2025). Large language model for multiobjective evolutionary optimization. International Conference on Evolutionary Multi-Criterion Optimization.

Xing Li, Zeyu Xing, Yiming Li, Linping Qu, Hui-Ling Zhen, Wulong Liu, Yiwu Yao, Sinno Jialin Pan, Mingxuan Yuan (2025). KVTuner: Sensitivity-Aware Layer-wise Mixed Precision KV Cache Quantization for Efficient and Nearly Lossless LLM Inference. ICML2025.

Runquan Gui, Zhihai Wang, Jie Wang, Chi Ma, Huiling Zhen, Mingxuan Yuan, Jianye Hao, Defu Lian, Enhong Chen, Feng Wu (2025). HyperTree Planning: Enhancing LLM Reasoning via Hierarchical Thinking. ICML2025.

Qingyu Song, Peiyu Liao, Wenqian Zhao, Yiwen Wang, Shoubo Hu, Hui-Ling Zhen, Ning Jiang, Mingxuan Yuan (2025). Harnessing Large Language Models Locally: Empirical Results and Implications for AI PC. arXiv preprint arXiv:2505.15030.

Fei Liu, Qingfu Zhang, Xialiang Tong, Mingxuan Yuan, Kun Mao (2025). Fitness Landscape of Large Language Model-Assisted Automated Algorithm Search. arXiv preprint arXiv:2504.19636.

Zijie Geng, Jie Wang, Xijun Li, Fangzhou Zhu, Jianye Hao, Bin Li, Feng Wu (2025). Differentiable integer linear programming. The Thirteenth International Conference on Learning Representations.

Zehua Pei, Lancheng Zou, Hui-Ling Zhen, Xianzhi Yu, Wulong Liu, Sinno Jialin Pan, Mingxuan Yuan, Bei Yu (2025). CMoE: Fast Carving of Mixture-of-Experts for Efficient LLM Inference. arXiv preprint arXiv:2502.04416.

Bowei He, Lihao Yin, Hui-Ling Zhen, Jianping Zhang, Lanqing Hong, Mingxuan Yuan, Chen Ma (2025). Certifying Language Model Robustness with Fuzzed Randomized Smoothing: An Efficient Defense Against Backdoor Attacks. ICLR2025.

Kai Li, Fei Liu, Zhenkun Wang, Xialiang Tong, Xiongwei Han, Mingxuan Yuan, Qingfu Zhang (2025). ARS: Automatic Routing Solver with Large Language Models. arXiv preprint arXiv:2502.15359.

Haoyang Liu, Jie Wang, Zijie Geng, Xijun Li, Yuxuan Zong, Fangzhou Zhu, Jianye Hao, Feng Wu (2025). Apollo-MILP: An alternating prediction-correction neural solving framework for mixed-integer linear programming. arXiv preprint arXiv:2503.01129.

Zhihai Wang, Jie Wang, Jilai Pan, Xilin Xia, Huiling Zhen, Mingxuan Yuan, Jianye Hao, Feng Wu (2025). Accelerating Large Language Model Reasoning via Speculative Search. ICML2025.

Yufei Kuang, Xijun Li, Jie Wang, Fangzhou Zhu, Meng Lu, Zhihai Wang, Jia Zeng, Houqiang Li, Yongdong Zhang, Feng Wu (2025). Accelerate presolve in large-scale linear programming via reinforcement learning. IEEE Transactions on Pattern Analysis and Machine Intelligence.

Yufei Kuang, Jie Wang, Yuyan Zhou, Xijun Li, Fangzhou Zhu, Jianye Hao, Feng Wu (2024). Towards general algorithm discovery for combinatorial optimization: Learning symbolic branching policy from bipartite graph. Forty-first International Conference on Machine Learning.

Reza Moravej, Saurabh Bodhe, Zhanguang Zhang, Didier Chetelat, Dimitrios Tsaras, Yingxue Zhang, Hui-Ling Zhen, Jianye Hao, Mingxuan Yuan (2024). The Graph's Apprentice: Teaching an LLM Low Level Knowledge for Circuit Quality Estimation. arXiv preprint arXiv:2411.00843.

Yufei Kuang, Jie Wang, Haoyang Liu, Fangzhou Zhu, Xijun Li, Jia Zeng, Jianye Hao, Bin Li, Feng Wu (2024). Rethinking branching on exact combinatorial optimization solver: The first deep symbolic discovery framework. The Twelfth International Conference on Learning Representations.

Hongduo Liu, Peiyu Liao, Junhua Huang, Hui-Ling Zhen, Mingxuan Yuan, Tsung-Yi Ho, Bei Yu (2024). Parallel gröbner basis rewriting and memory optimization for efficient multiplier verification. 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE).

Hongduo Liu, Peng Xu, Yuan Pu, Lihao Yin, Hui-Ling Zhen, Mingxuan Yuan, Tsung-Yi Ho, Bei Yu (2024). Neuroselect: Learning to select clauses in sat solvers. Proceedings of the 61st ACM/IEEE Design Automation Conference.

Haoyang Liu, Jie Wang, Wanbo Zhang, Zijie Geng, Yufei Kuang, Xijun Li, Bin Li, Yongdong Zhang, Feng Wu (2024). MILP-StuDio: MILP Instance Generation via Block Structure Decomposition. arXiv preprint arXiv:2410.22806.

Jie Wang, Zhihai Wang, Xijun Li, Yufei Kuang, Zhihao Shi, Fangzhou Zhu, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu (2024). Learning to cut via hierarchical sequence/set model for efficient mixed-integer programming. IEEE Transactions on Pattern Analysis and Machine Intelligence.

Hongduo Liu, Peiyu Liao, Mengchuan Zou, Bowen Pang, Xijun Li, Mingxuan Yuan, Tsung-Yi Ho, Bei Yu (2024). Layout decomposition via boolean satisfiability. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

Lei Chen, Yiqi Chen, Zhufei Chu, Wenji Fang, Tsung-Yi Ho, Ru Huang, Yu Huang, Sadaf Khan, Min Li, Xingquan Li, Others (2024). Large circuit models: opportunities and challenges. Science China Information Sciences.

Tsz Ho Chan, Wenyi Xiao, Junhua Huang, Huiling Zhen, Guangji Tian, Mingxuan Yuan (2024). IB-Net: Initial Branch Network for Variable Decision in Boolean Satisfiability. arXiv preprint arXiv:2403.03517.

Joseph Cotnareanu, Zhanguang Zhang, Hui-Ling Zhen, Yingxue Zhang, Mark Coates (2024). HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation. Advances in Neural Information Processing Systems.

Zhanguang Zhang, Didier Chételat, Joseph Cotnareanu, Amur Ghose, Wenyi Xiao, Hui-Ling Zhen, Yingxue Zhang, Jianye Hao, Mark Coates, Mingxuan Yuan (2024). Grass: Combining graph neural networks with expert knowledge for sat solver selection. Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

Zehua Pei, Hui-Ling Zhen, Xianzhi Yu, Sinno Jialin Pan, Mingxuan Yuan, Bei Yu (2024). FuseGPT: Learnable Layers Fusion of Generative Pre-trained Transformers. arXiv preprint arXiv:2411.14507.

Yu Zhang, Hui-Ling Zhen, Mingxuan Yuan, Bei Yu (2024). DiffSAT: Differential MaxSAT Layer for SAT Solving. Proceedings of the 43rd IEEE/ACM International Conference on Computer-Aided Design.

PEI Zehua, Huiling Zhen, Mingxuan Yuan, Yu Huang, Bei Yu (2024). Betterv: Controlled verilog generation with discriminative guidance. Forty-first International Conference on Machine Learning.

Fei Liu, Yiming Yao, Ping Guo, Zhiyuan Yang, Zhe Zhao, Xi Lin, Xialiang Tong, Mingxuan Yuan, Zhichao Lu, Zhenkun Wang, Others (2024). A systematic survey on large language models for algorithm design. arXiv preprint arXiv:2410.14716.

Zhengyuan Shi, Min Li, Yi Liu, Sadaf Khan, Junhua Huang, Hui-Ling Zhen, Mingxuan Yuan, Qiang Xu (2023). Satformer: transformer-based unsat core learning. 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD).

Wenxuan Guo, Hui-Ling Zhen, Xijun Li, Wanqian Luo, Mingxuan Yuan, Yaohui Jin, Junchi Yan (2023). Machine learning methods in solving the boolean satisfiability problem. Machine Intelligence Research.

Ruizhe Zhong, Xingbo Du, Shixiong Kai, Zhentao Tang, Siyuan Xu, Hui-Ling Zhen, Jianye Hao, Qiang Xu, Mingxuan Yuan, Junchi Yan (2023). Llm4eda: Emerging progress in large language models for electronic design automation. arXiv preprint arXiv:2401.12224.

Zhihai Wang, Xijun Li, Jie Wang, Yufei Kuang, Mingxuan Yuan, Jia Zeng, Yongdong Zhang, Feng Wu (2023). Learning cut selection for mixed-integer linear programming via hierarchical sequence model. arXiv preprint arXiv:2302.00244.

Yang Li, Xinyan Chen, Wenxuan Guo, Xijun Li, Wanqian Luo, Junhua Huang, Hui-Ling Zhen, Mingxuan Yuan, Junchi Yan (2023). Hardsatgen: Understanding the difficulty of hard sat formula generation and a strong structure-hardness-aware baseline. Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

Shi-Jie Ye, Yun-Ju Liu, Liu-Zheng Wang, Hui-Ling Zhen, Wei-Ming Zhang, Yu Huang (2023). Fault simulation acceleration based on ARM multi-core CPU architecture. 2023 IEEE 32nd Asian Test Symposium (ATS).

Zhengyuan Shi, Hongyang Pan, Sadaf Khan, Min Li, Yi Liu, Junhua Huang, Hui-Ling Zhen, Mingxuan Yuan, Zhufei Chu, Qiang Xu (2023). Deepgate2: Functionality-aware circuit representation learning. 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD).

Jiayi Zhang, Chang Liu, Xijun Li, Hui-Ling Zhen, Mingxuan Yuan, Yawen Li, Junchi Yan (2023). A survey for solving mixed integer programming via machine learning. Neurocomputing.

Junhua Huang, Hui-Ling Zhen, Naixing Wang, Hui Mao, Mingxuan Yuan, Yu Huang (2022). Neural fault analysis for sat-based atpg. 2022 IEEE International Test Conference (ITC).

Zeren Huang, Kerong Wang, Furui Liu, Hui-Ling Zhen, Weinan Zhang, Mingxuan Yuan, Jianye Hao, Yong Yu, Jun Wang (2022). Learning to select cuts for efficient mixed-integer programming. Pattern Recognition.

Zeren Huang, Wenhao Chen, Weinan Zhang, Chuhan Shi, Furui Liu, Hui-Ling Zhen, Mingxuan Yuan, Jianye Hao, Yong Yu, Jun Wang (2022). Branch ranking for efficient mixed-integer programming via offline ranking-based policy learning. Joint European Conference on Machine Learning and Knowledge Discovery in Databases.

Longkang Li, Xiaojin Fu, Hui-Ling Zhen, Mingxuan Yuan, Jun Wang, Jiawen Lu, Xialiang Tong, Jia Zeng, Dirk Schnieders (2022). Bilevel learning for large-scale flexible flow shop scheduling. Computers & Industrial Engineering.

Hui-Ling Zhen, Zhenkun Wang, Xijun Li, Qingfu Zhang, Mingxuan Yuan, Jia Zeng (2022). Accelerate the optimization of large-scale manufacturing planning using game theory. Complex & Intelligent Systems.

Junhua Huang, Hui-Ling Zhen, Naixing Wang, Mingxuan Yuan, Hui Mao, Yu Huang, Jiping Tao (2022). Accelerate sat-based atpg via preprocessing and new conflict management heuristics. 2022 27th Asia and South Pacific Design Automation Conference (ASP-DAC).

Zhenkun Wang, Hui-Ling Zhen, Jingda Deng, Qingfu Zhang, Xijun Li, Mingxuan Yuan, Jia Zeng (2021). Multiobjective optimization-aided decision-making system for large-scale manufacturing planning. IEEE Transactions on Cybernetics.

Xijun Li, Weilin Luo, Mingxuan Yuan, Jun Wang, Jiawen Lu, Jie Wang, Jinhu Lü, Jia Zeng (2021). Learning to optimize industry-scale dynamic pickup and delivery problems. 2021 IEEE 37th international conference on data engineering (ICDE).