Publications

Tianshi Xu, Wenjie Lu, Jiangrui Yu, Chenqi Lin, Yi Chen, Runsheng Wang, 李萌 (2025). Breaking the Layer Barrier: Remodeling Private Transformer Inference with Hybrid CKKS and MPC. In Usenix Security Symposium 2025.

Weikai Xu, Wenxuan Zeng, Qianqian Huang, 李萌, Ru Huang (2025). UniCAIM: A Unified CAM/CIM Architecture with Static-Dynamic KV Cache Pruning for Efficient Long-Context LLM Inference. In Design Automation Conference (DAC) 2025.

Linye Wei, Shuzhang Zhong, Songqiang Xu, Runsheng Wang, Ru Huang, 李萌 (2025). SpecASR: Accelerating LLM-based Automatic Speech Recognition via Speculative Decoding. In Design Automation Conference (DAC) 2025.

Tong Xie, Jiawang Zhao, Zishen Wan, Zuodong Zhang, Yuan Wang, Runsheng Wang, Ru Huang, 李萌 (2025). ReaLM: Reliable and Efficient Large Language Model Inference with Statistical Algorithm-Based Fault Tolerance. In Design Automation Conference (DAC) 2025.

Shuzhang Zhong, Yanfan Sun, Ling Liang, Runsheng Wang, Ru Huang, 李萌 (2025). HybriMoE: Hybrid CPU-GPU Scheduling and Cache Management for Efficient MoE Inference. In Design Automation Conference (DAC) 2025.

Renjie Wei, Zechun Liu, Yuchen Fan, Runsheng Wang, Ru Huang, 李萌 (2025). SCALES: Boost Binary Neural Network for Image Super-Resolution with Efficient Scalings. In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2025.

Renjie Wei, Songqiang Xu, Linfeng Zhong, Zebin Yang, Qingyu Guo, Yuan Wang, Runsheng Wang, 李萌 (2025). LightMamba: Efficient Mamba Acceleration on FPGA with Quantization and Hardware Co-design. In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2025.

Tengyu Zhang, Yufei Xue, Ling Liang, Zhen Gu, Yuan Wang, Runsheng Wang, Ru Huang, 李萌 (2025). FLASH: An Efficient Hardware Accelerator Leveraging Approximate and Sparse FFT for Homomorphic Encryption. In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2025.

Weikai Xu, 李萌, Qianqian Huang, Ru Huang (2025). Compact Non-Volatile Lookup Table Architecture based on Ferroelectric FET Array through In-Situ Combinatorial One-Hot Encoding for Reconfigurable Computing. In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2025.

Xincheng Feng, Guodong Shen, Jianhao Hu, 李萌, Ngai Wong (2025). Stochastic Multivariate Universal-Radix Finite-State Machine: a Theoretically and Practically Elegant Nonlinear Function Approximator. In Asia and South Pacific Design Automation Conference (ASP-DAC) 2025.

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Tianshi Xu, Lemeng Wu, Runsheng Wang, 李萌 (2024). PrivCirNet: Efficient Private Inference via Block Circulant Transformation. In Conference on Neural Information Processing Systems (NeurIPs) 2024.

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Renze Chen, Zhuofeng Wang, Beiquan Cao, Tong Wu, Size Zheng, Xiuhong Li, Xuechao Wei, Shengen Yan, 李萌, Yun Liang (2024). ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction. In Conference on Neural Information Processing Systems (NeurIPs) 2024.

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Shuzhang Zhong, Zebin Yang, Ruihao Gong, Runsheng Wang, Ru Huang, 李萌 (2024). ProPD: Dynamic Token Tree Pruning and Generation for LLM Parallel Decoding. In International Conference on Computer-Aided Design (ICCAD) 2024.

Tianshi Xu, Shuzhang Zhong, Wenxuan Zeng, Runsheng Wang, 李萌 (2024). PrivQuant: Communication-Efficient Private Inference with Quantized Network/Protocol Co-Optimization. In International Conference on Computer-Aided Design (ICCAD) 2024.

Yixuan Hu, Yikang Jia, 李萌, Yuan Wang, Runsheng Wang, Ru Huang (2024). OSCA: End-to-end Serial Stochastic Computing Neural Acceleration with Fine-grained Scaling and Piecewise Activation. In International Conference on Computer-Aided Design (ICCAD) 2024.

Zebin Yang, Renze Chen, Taiqiang Wu, Ngai Wong, Yun (Eric) Liang, Runsheng Wang, Ru Huang, 李萌 (2024). MCUBERT: Memory-Efficient BERT Inference on Commodity Microcontrollers. In International Conference on Computer-Aided Design (ICCAD) 2024.

Qingyu Guo, Jiayong Wan, Songqiang Xu, 李萌, Yuan Wang (2024). HG-PIPE: Vision Transformer Acceleration with Hybrid-Grained Pipeline. In International Conference on Computer-Aided Design (ICCAD) 2024.

Jiangrui Yu, Wenxuan Zeng, Tianshi Xu, Renze Chen, Yun (Eric) Liang, Runsheng Wang, Ru Huang, 李萌 (2024). FlexHE: A flexible Kernel Generation Framework for Homomorphic Encryption-Based Private Inference. In International Conference on Computer-Aided Design (ICCAD) 2024.

Shuzhang Zhong, Ling Liang, Yuan Wang, Runsheng Wang, Ru Huang, 李萌 (2024). AdapMoE: Adaptive Sensitivity-based Expert Gating and Management for Efficient MoE Inference. In International Conference on Computer-Aided Design (ICCAD) 2024.

Qingyu Guo, Haoyang Luo, 李萌, Xiyuan Tang, Yuan Wang (2024). CASCADE: A Framework for CNN Accelerator Synthesis with Concatenation and Refreshing Dataflow. In IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I) (2024).

Chenqi Lin, Tianshi Xu, Zebin Yang, 李萌, Runsheng Wang, Ru Huang (2024). FastQuery: Communication-efficient Embedding Table Query for Private LLMs inference. In Design Automation Conference (DAC) 2024.

Tong Xie, Yixuan Hu, Renjie Wei, 李萌, Runsheng Wang, Yuan Wang, Ru Huang (2024). ASCEND: Accurate yet Efficient End-to-End Stochastic Computing Acceleration of Vision Transformer. In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2024.

Xin Qiao, Qingyu Guo, Xiyuan Tang, Jiahao Song, Renjie Wei, 李萌, Runsheng Wang, Yuan Wang (2024). A 16.38TOPS and 4.55POPS/W SRAM Computing-in-Memory Macro for Signed Operands Computation and Batch Normalization Implementation. In IEEE Transactions on Circuits and Systems I: Regular Papers (TCAS-I) (2024).

Xin Qiao, Jiahao Song, Youming Yang, Renjie Wei, Xiyuan Tang, 李萌, Runsheng Wang, Yuan Wang (2024). MixCIM: A Hybrid-Cell-Based Computing-in-Memory Macro with Less-Data-Movement and Activation-Memory-Reuse for Depthwise Separable Neural Networks. In IEEE Custom Integrated Circuits Conference (CICC) 2024.

Wenxuan Zeng, 李萌, Haichuan Yang, Wen-Jie Lu, Runsheng Wang, Ru Huang (2023). CoPriv: Network/Protocol Co-Optimization for Communication-Efficient Private Inference. In Conference on Neural Information Processing Systems (NeurIPs) 2023.

Zuodong Zhang, 李萌, Yibo Lin, Runsheng Wang, Ru Huang (2023). READ: Reliability-Enhanced Accelerator Dataflow Optimization using Critical Input Pattern Reduction. In ACM/IEEE International Conference on Computer Aided Design (ICCAD) 2023.

李萌, Yixuan Hu, Tengyu Zhang, Renjie Wei, Yawen Zhang, Ru Huang, Runsheng Wang (2023). Not your father’s stochastic computing (SC)! Efficient yet Accurate End-to-End SC Accelerator Design. In International Conference on ASIC (ASICON) 2023.

Wenxuan Zeng, 李萌, Wenjie Xiong, Tong Tong, Wen-Jie Lu, Jin Tan, Runsheng Wang, Ru Huang (2023). MPCViT: Searching for Accurate and Efficient MPC-Friendly Vision Transformer with Heterogeneous Attention. In International Conference on Computer Vision (ICCV) 2023.

Shuzhang Zhong, 李萌, Yun (Eric) Liang, Runsheng Wang, Ru Huang (2023). Memory-aware Scheduling for Complex Wired Networks with Iterative Graph Optimization. In ACM/IEEE International Conference on Computer Aided Design (ICCAD) 2023.

Tianshi Xu, 李萌, Runsheng Wang, Ru Huang (2023). Falcon: Accelerating Homomorphically Encrypted Convolutions for Efficient Private Mobile Network Inference. In ACM/IEEE International Conference on Computer Aided Design (ICCAD) 2023.

Yixuan Hu, Tengyu Zhang, 李萌, Renjie Wei, Liangzhen Lai, Yuan Wang, Runsheng Wang, Ru Huang (2023). Efficient Non-Linear Adder for Stochastic Computing with Approximate Spatial-Temporal Sorting Network. In Design Automation Conference (DAC) 2023.

Zuodong Zhang, Zizheng Guo, Yibo Lin, 李萌, Runsheng Wang, Ru Huang (2023). AVATAR: An Aging- and Variation-Aware Dynamic Timing Analyzer for Error-Efficient Computing. In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2023).

Zuodong Zhang, 李萌, Yibo Lin, Runsheng Wang, Ru Huang (2023). READ: Reliability-Enhanced Accelerator Dataflow Optimization using Critical Input Pattern Reduction. In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2023 (extended abstract).

Yixuan Hu, Tengyu Zhang, Renjie Wei, 李萌, Runsheng Wang, Yuan Wang, Ru Huang (2023). Accurate yet Efficient Stochastic Computing Neural Acceleration with High Precision Residual Fusion. In Design, Automation and Test in Europe Conference and Exhibition (DATE) 2023.

Zechun Liu, Barlas Oguz, Aasish Pappu, Lin Xiao, Scott Yih, 李萌, Raghuraman Krishnamoorthi, Yashar Mehdad (2022). BiT: Robustly Binarized Multi-distilled Transformer. In Conference on Neural Information Processing Systems (NeurIPs) 2022.

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Yonggan Fu, Haichuan Yang, Jiayi Yuan, 李萌, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin (2022). Depth Shrink: Empowering Hardware-Friendly Shallow Neural Networks. In Conference on Machine Learning (ICML) 2022.

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Haichuan Yang, Yuan Shangguan, Dilin Wang, 李萌, Pierce Chuang, Xiaohui Zhang, Ganesh Venkatesh, Ozlem Kalinli, Vikas Chandra (2022). Omni-sparsity DNN: Fast Sparsity Optimization for On-Device Streaming E2E ASR via Supernet. In International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2022.

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Xin Dong, Ziyun Li, 李萌, Zhongnan Qu, Barbara De Salvo, Chiao Liu, Hsiang-Tsung Kung (2022). SplitNets: Designing Neural Architectures for Efficient Distributed Computing on Head-Mounted Systems. In Conference on Computer Vision and Pattern Recognition (CVPR) 2022.

Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, 李萌, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Pan (2022). Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation. In Conference on Computer Vision and Pattern Recognition (CVPR) 2022.

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Chengyue Gong, Dilin Wang, 李萌, Xinlei Chen, Zhicheng Yan, Yuandong Tian, Qiang Liu, Vikas Chandra (2022). NASViT: Neural Architecture Search for Efficient Vision Transformers with Gradient Conflict aware Supernet Training. In Conference on Learning Representations (ICLR) 2022.

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Yongan Zhang, Yonggan Fu, Weiwen Jiang, Chaojian Li, Haoran You, 李萌, Vikas Chandra, Yingyan Lin (2021). DNA: Differentiable Network-Accelerator Co-Search. In International Symposium on Low Power Electronics and Design (ISLPED) 2021.

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Dilin Wang, Chengyue Gong, 李萌, Qiang Liu, Vikas Chandra (2021). AlphaNet: Improved Training of Supernets with Alpha-Divergence. In Conference on Machine Learning (ICML) 2021 (Long Oral).

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Dilin Wang, 李萌, Chengyue Gong, Vikas Chandra (2021). AttentiveNAS: Improving Neural Architecture Search via Attentive Sampling. In Conference on Computer Vision and Pattern Recognition (CVPR) 2021.

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李萌, Yilei Li, Vikas Chandra (2021). Improving efficiency in neural network accelerator using operands hamming distance optimization. In Asia and South Pacific Design Automation Conference (ASP-DAC) 2021.

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Chengyue Gong, Dilin Wang, 李萌, Vikas Chandra, Qiang Liu (2020). KeepAugment: A Simple Information-Preserving Data Augmentation Approach. In Conference on Computer Vision and Pattern Recognition (CVPR) 2021.

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Lei Yang, Zheyu Yan, 李萌, Hyoukjun Kwon, Liangzhen Lai, Tushar Krishna, Vikas Chandra, Weiwen Jiang, Yiyu Shi (2020). Co-exploration of neural architectures and heterogeneous asic accelerator designs targeting multiple tasks. In ACM/IEEE Design Automation Conference (DAC) 2020.

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李萌, Kaveh Shamsi, Yier Jin, David Z Pan (2018). TimingSAT: Decamouflaging timing-based logic obfuscation. In IEEE International Test Conference (ITC) 2018.

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李萌, David Z. Pan (2018). A Synergistic Framework for Hardware IP Privacy and Integrity Protection. In Springer (2018).

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李萌, Bei Yu, Yibo Lin, Xiaoqing Xu, Wuxi Li, David Z. Pan (2018). A Practical Split Manufacturing Framework for Trojan Prevention via Simultaneous Wire Lifting and Cell Insertion. In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2018).

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Yue Zhao, 李萌, Liangzhen Lai, Naveen Suda, Damon Civin, Vikas Chandra (2018). Federated Learning with Non-IID Data. In arXiv:1806.00582 (2018).

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李萌, Bei Yu, Yibo Lin, Xiaoqing Xu, Wuxi Li, David Z. Pan (2018). A Practical Split Manufacturing Framework for Trojan Prevention via Simultaneous Wire Lifting and Cell Insertion. In Asia and South Pacific Design Automation Conference (ASP-DAC) 2018.

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李萌, Liangzhen Lai, Naveen Suda, Vikas Chandra, David Z. Pan (2018). PrivyNet: A Flexible Framework for Privacy-Preserving Deep Neural Network Training. In arXiv:1709:06161 (2018).

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李萌, Kaveh Shamsi, Travis Meade, Zheng Zhao, Bei Yu, Yier Jin, David Z Pan (2017). Provably secure camouflaging strategy for IC protection. In IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD) (2018).

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李萌, Kaveh Shamsi, Travis Meade, Zheng Zhao, Bei Yu, Yier Jin, David Z Pan (2017). Provably secure camouflaging strategy for IC protection. In ACM/IEEE International Conference on Computer Aided Design (ICCAD) 2017.

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李萌, Liangzhen Lai, Vikas Chandra, David Z. Pan (2017). Cross-level monte carlo framework for system vulnerability evaluation against fault attack. In ACM/IEEE Design Automation Conference (DAC) 2017.

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Kaveh Shamsi, 李萌, Travis Meade, Zheng Zhao, David Z Pan, Yier Jin (2017). AppSAT: Approximately Deobfuscating Integrated Circuits. In IEEE International Symposium on Hardware Oriented Security and Trust (HOST) 2017 (Best Paper Award).

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李萌, Jin Miao, Kai Zhong, David Z Pan (2016). Practical public PUF enabled by solving max-flow problem on chip. In ACM/IEEE Design Automation Conference (DAC) 2016.

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李萌, Ye Wang, Michael Orshansky (2016). A monte carlo simulation flow for seu analysis of sequential circuits. In ACM/IEEE Design Automation Conference (DAC) 2016.

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李萌, Runsheng Wang, Jibin Zou, Ru Huang (2013). Characterization of Random Telegraph Noise in Scaled High-κ/Metal-Gate MOSFETs with SiO2/HfO2 Gate Dielectrics. In ECS Transactions, 52 (1) 941-946 (2013).

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Yu Fu, Yu Tong, Yijing Ning, Tianshi Xu, 李萌, Jingqiang Lin, Dengguo Feng (0001). Swift: Fast Secure Neural Network Inference with Fully Homomorphic Encryption.

Renze Chen, Zijian Ding, Size Zheng, 李萌, Yun (Eric) Liang (0001). MoteNN: Memory Optimization via Fine-grained Scheduling for Deep Neural Networks on Tiny Devices.

Lemeng Wu, Dilin Wang, 李萌, Yunyang Xiong, Raghuraman Krishnamoorthi, Qiang Liu, Vikas Chandra (0001). Enhancing 3D Detection Through Feature Aligned Deep Fusion.

Jianan Mu, Husheng Han, Shangyi Shi, Jing Ye, Zizhen Liu, Shengwen Liang, 李萌, Mingzhe Zhang, Song Bian, Xing Hu, Huaiwei Li, Xiaowei Li (0001). Alchemist: A Unified Accelerator Architecture for Cross-Scheme Fully Homomorphic Encryption.