期刊文章:

[1] Fully Automated Processor Chip Design: Motivation, Challenges and Future Directions, Rui Zhang, Jiaming Guo, Shuyao Cheng, Yunji Chen, National Science Review, Volume 13, Issue 1, January 1, 2026（第一作者）

[2] QiMeng-CPU-v2: Automated Superscalar Processor Design by Learning Data Dependencies, Xiangtao Guan, Shuyao Cheng, Rui Zhang, Pengwei Jin, Chongxiao Li, Tianyun Ma, Zidong Du, Xing Hu, Cheng Li, Yifan Hao, Guanglin Xu, Yuanbo Wen, Ling Li, Qi Guo, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems（CCF A，通讯作者）

[3] Automatic Pipelining for Arbitrary Circuits via Gate-level Forwarding and Customized Scheduling, Chongxiao Li, Shuyao Cheng, Rui Zhang, Qicheng Wang, Pengwei Jin, Di Huang, Jiaming Guo, Zidong Du, Xing Hu, Qi Guo, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems（CCF A，通讯作者）

[4] A Decomposable Winograd Method for N-D Convolution Acceleration in Video Analysis,Di Huang, Rui Zhang, Xishan Zhang, Fan Wu, Xianzhuo Wang, Pengwei Jin, Shaoli Liu,Ling Li, Yunji Chen, International Journal of Computer Vision, 2021, pp.1-21.   (CCF A，第二作者，第一指导老师)

[5] Rethinking the Importance of Quantization Bias, Toward Full Low-Bit Training, Chang Liu,Xishan Zhang, Rui Zhang, Ling Li, Shiyi Zhou, Di Huang, Zhen Li, Zidong Du, Shaoli Liu,Tianshi Chen, IEEE Transactions on Image Processing.   (CCF A)

[6] CodeV: Empowering LLMs With HDL Generation Through Multilevel Summarization, Yang Zhao, Di Huang, Chongxiao Li, Pengwei Jin, Muxin Song, Yinan Xu, Ziyuan Nan, Mingju Gao, Tianyun Ma, Lei Qi, Yansong Pan, Zhenxing Zhang, Rui Zhang, Xishan Zhang, Zidong Du, Qi Guo, Xing Hu, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 45(4): 1893-1906 (2026) (CCF A)

会议文章：

[1] QiMeng-PRepair: Precise Code Repair via Edit-Aware Reward Optimization, ACL 2026 (CCF A，第二作者，第一指导老师)

[2] QiMeng-CRUX: Narrowing the Gap between Natural Language and Verilog via Core Refined Understanding eXpression, AAAI 2026 (CCF A，第二作者，第一指导老师)

[3] QiMeng-SALV: Signal-Aware Learning for Verilog Code Generation, NeurIPS 2025 (CCF A，第二作者，第一指导老师)

[4] QiMeng-MuPa: Mutual-Supervised Learning for Sequential-to-Parallel Code Translation, NeurIPS 2025 (CCF A，第二作者，第一指导老师)

[5] Automated CPU Design by Learning from Input-Output Examples, IJCAI 2024 (CCF A，第二作者，第一指导老师)

[6] DA-Ada: Learning Domain-Aware Adapter for Domain Adaptive Object Detection, NeurIPS 2024 (CCF A，第二作者，第一指导老师)

[7] Prompt-based Visual Alignment for Zero-shot Policy Transfer, ICML 2024 (CCF A，第二作者，第一指导老师)

[8] Efficient Symbolic Policy Learning with Differentiable Symbolic Expression, NeurIPS 2023 (CCF A，第二作者，第一指导老师)

[9] Learning Domain-Aware Detection Head with Prompt Tuning, NeurlPS 2023 (CCF A，第二作者，第一指导老师)

[10]Context Shift Reduction  for Offline  Meta-Reinforcement  Learning, NeurlPS 2023 (CCF A，第二作者，第一指导老师)

[11] Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning, NeurlPS 2023 (CCF A，第二作者，第一指导老师)

[12] Online Prototype Alignment for Few-shot Policy Transfer, ICML 2023 (CCF A，第二作者，第一指导老师))

[13] Visual-Language Prompt Tuning with Knowledge-Guided Context Optimization, ICCV 2023 (CCF A，第二作者)

[14]  Object-Category Aware  Reinforcement Learning,  NeurlPS 2022 (CCF A，第二作者，第一指导老师)

[15] Hindsight Value Function for Variance Reduction in Stochastic Dynamic Environment, IJCAI 2021 (CCF A，第二作者，第一指导老师) 

[16] Distilling object detectors with feature richness, NeurlPS 2021 (CCF A，第二作者，第一指导老师)

[17] Domain-Specific Suppression for Adaptive Object Detection, CVPR 2021 (CCF A，第二作者，第一指导老师))

著作：

智能计算系统：从深度学习到大模型，机械工业出版社，2024-03，第7作者

智能计算系统实验教程，机械工业出版社，2021-08，第4作者

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