Publications

Xuan Shen, Hangyu Zheng, Yifan Gong, Zhenglun Kong, Changdi Yang, Zheng Zhan, Yushu Wu, Xue Lin, Yanzhi Wang, Pu Zhao, Wei Niu (2025). Sparse Learning for State Space Models on Mobile. In ICLR 2025.

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Jun Liu, Zhenglun Kong, Peiyan Dong, Xuan Shen, Pu Zhao, Hao Tang, Geng Yuan, Wei Niu, Wenbin Zhang, Xue Lin, Dong Huang, Yanzhi Wang (2025). RoRA: Efficient Fine-Tuning of LLM with Reliability Optimization for Rank Adaptation. In ICASSP 2025.

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Xuan Shen, Weize Ma, Jing Liu, Changdi Yang, Rui Ding, Quanyi Wang, Henghui Ding, Wei Niu, Yanzhi Wang, Pu Zhao, Jun Lin, Jiuxiang Gu (2025). QuartDepth: Post-Training Quantization for Real-Time Depth Estimation on the Edge. In CVPR 2025.

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Jun Liu, Zhenglun Kong, Pu Zhao, Changdi Yang, Hao Tang, Xuan Shen, Geng Yuan, Wei Niu, Wenbin Zhang, Xue Lin, Dong Huang, Yanzhi Wang (2025). Toward Adaptive Large Language Models Structured Pruning via Hybrid-grained Weight Importance Assessment. In AAAI 2025.

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Xuan Shen, Zhao Song, Yufa Zhou, Bo Chen, Jing Liu, Ruiyi Zhang, Ryan A- Rossi, Hao Tan, Tong Yu, Xiang Chen, Yufan Zhou, Tong Sun, Pu Zhao, Yanzhi Wang, Jiuxiang Gu (2025). Numerical Pruning for Efficient Autoregressive Models. In AAAI 2025.

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Xuan Shen, Zhao Song, Yufa Zhou, Bo Chen, Yanyu Li, Yifan Gong, Kai Zhang, Hao Tan, Jason Kuen, Henghui Ding, Zhihao Shu, Wei Niu, Pu Zhao, Yanzhi Wang, Jiuxiang Gu (2025). LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers. In AAAI 2025.

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Pinrui Yu, Zhenglun Kong, Pu Zhao, Peiyan Dong, Hao Tang, Fei Sun, Xue Lin, Yanzhi Wang (2025). Q-TempFusion: Quantization-Aware Temporal Multi-Sensor Fusion on Bird's-Eye View Representation. In WACV 2025.

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Xuan Shen, Pu Zhao, Yifan Gong, Zhenglun Kong, Zheng Zhan, Yushu Wu, Ming Lin, Chao Wu, Xue Lin, Yanzhi Wang (2024). Search for Efficient Large Language Models. In NeurIPS 2024.

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Zheng Zhan, Yushu Wu, Yifan Gong, Zichong Meng, Zhenglun Kong, Changdi Yang, Geng Yuan, Pu Zhao, Wei Niu, Yanzhi Wang (2024). Fast and Memory-Efficient Video Diffusion Using Streamlined Inference. In NeurIPS 2024.

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Zheng Zhan, Zhenglun Kong, Yifan Gong, Yushu Wu, Zichong Meng, Hangyu Zheng, Xuan Shen, Stratis Ioannidis, Wei Niu, Pu Zhao, Yanzhi Wang (2024). Exploring Token Pruning in Vision State Space Models. In NeurIPS 2024.

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Zheng Zhan, Yushu Wu, Zhenglun Kong, Changdi Yang, Yifan Gong, Xuan Shen, Xue Lin, Pu Zhao, Yanzhi Wang (2024). Rethinking Token Reduction for State Space Models. In EMNLP 2024.

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Pu Zhao, Fei Sun, Xuan Shen, Pinrui Yu, Zhenglun Kong, Yanzhi Wang, Xue Lin (2024). Pruning Foundation Models for High Accuracy without Retraining. In EMNLP 2024 Findings.

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Jun Liu, Zhenglun Kong, Pu Zhao, Weihao Zeng, Hao Tang, Xuan Shen, Changdi Yang, Wenbin Zhang, Geng Yuan, Wei Niu, Xue Lin, Yanzhi Wang (2024). TSLA: A Task-Specific Learning Adaptation for Semantic Segmentation on Autonomous Vehicles Platform. In TCAD.

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Xuan Shen, Zhaoyang Han, Lei Lu, Zhenglun Kong, Peiyan Dong, Zhengang Li, Yanyue Xie, Chao Wu, Miriam Leeser, Pu Zhao, Xue Lin, Yanzhi Wang (2024). HotaQ: Hardware Oriented Token Adaptive Quantization for Large Language Models. In TCAD.

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Zichong Meng, Changdi Yang, Jun Liu, Hao Tang, Pu Zhao, Yanzhi Wang (2024). InstructGIE: Towards Generalizable Image Editing. In ECCV 2024.

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Zichong Meng, Jie Zhang, Changdi Yang, Zheng Zhan, Pu Zhao, Yanzhi Wang (2024). DiffClass: Diffusion-Based Class Incremental Learning. In ECCV 2024.

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Yize Li, Pu Zhao, Ruyi Ding, Tong Zhou, Yunsi Fei, Xiaolin Xu, Xue Lin (2024). Neural architecture search for adversarial robustness via learnable pruning. In Front. HPC.

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Pinrui Yu, Dan Luo, Timothy Rupprecht, Lei Lu, Zhenglun Kong, Pu Zhao, Yanyu Li, Octavia Camps, Xue Lin, Yanzhi Wang (2024). FasterVD: On Acceleration of Video Diffusion Models. In IJCAI Demo 2024.

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Yifan Gong, Yushu Wu, Zheng Zhan, Pu Zhao, Liangkai Liu, Chao Wu, Xulong Tang, Yanzhi Wang (2024). Lotus: learning-based online thermal and latency variation management for two-stage detectors on edge devices. In DAC 2024.

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Paul D.S. Fink, Stacy A. Doore, Xue Lin, Matthew Maring, Pu Zhao, Aubree Nygaard, Grant Beals, Richard R. Corey, Raymond J. Perry, Katherine Freund, Velin Dimitrov, Nicholas A. Giudice (2023). The Autonomous Vehicle Assistant (AVA): Emerging technology design supporting blind and visually impaired travelers in autonomous transportation. In Int. J. Hum. Comp. Stud..

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Changdi Yang, Pu Zhao, Yanyu Li, Wei Niu, Jiexiong Guan, Hao Tang, Minghai Qin, Bin Ren, Xue Lin, Yanzhi Wang (2023). Pruning Parameterization with Bi-level Optimization for Efficient Semantic Segmentation on the Edge. In CVPR 2023.

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Yifan Gong, Pu Zhao, Zheng Zhan, Yushu Wu, Chao Wu, Zhenglun Kong, Minghai Qin, Caiwen Ding, Yanzhi Wang (2023). Condense: A Framework for Device and Frequency Adaptive Neural Network Models on the Edge. In DAC 2023.

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Yanyu Li, Changdi Yang, Pu Zhao, Geng Yuan, Wei Niu, Jiexiong Guan, Hao Tang, Minghai Qin, Qing Jin, Bin Ren, Xue Lin, Yanzhi Wang (2023). Towards Real-Time Segmentation on the Edge. In AAAI 2023.

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Yihua Zhang, Yuguang Yao, Parikshit Ram, Pu Zhao, Tianlong Chen, Mingyi Hong, Yanzhi Wang, Sijia Liu (2022). Advancing Model Pruning via Bi-level Optimization. In NeurIPS 2022.

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Yifan Gong, Zheng Zhan, Pu Zhao, Yushu Wu, Chao Wu, Caiwen Ding, Weiwen Jiang, Minghai Qin, Yanzhi Wang (2022). All-in-One: A Highly Representative DNN Pruning Framework for Edge Devices with Dynamic Power Management. In ICCAD 2022.

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Yushu Wu, Yifan Gong, Pu Zhao, Yanyu Li, Zheng Zhan, Wei Niu, Hao Tang, Minghai Qin, Bin Ren, Yanzhi Wang (2022). Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution. In ECCV 2022.

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Yanyu Li, Pu Zhao, Geng Yuan, Xue Lin, Yanzhi Wang, Xin Chen (2022). Pruning-as-Search: Effcient Neural Architecture Search via Channel Pruning and Structural Reparameterization. In IJCAI 2022.

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Pu Zhao, Parikshit Ram, Songtao Lu, Yuguang Yao, Djallel Bouneffouf, Xue Lin, Sijia Liu (2022). Learning to Generate Image Source-Agnostic Universal Adversarial Perturbations. In IJCAI 2022.

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Xiaolong Ma, Geng Yuan, Zhengang Li, Yifan Gong, Tianyun Zhang, Wei Niu, Zheng Zhan, Pu Zhao, Jian Tang, Xue Lin, Bin Ren, Yanzhi Wang (2022). BLCR: Towards Real-time DNN Execution with Block-based Reweighted Pruning. In ISQED 2022.

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Pu Zhao, Geng Yuan, Yuxuan Cai, Wei Niu, Qi Liu, Wujie Wen, Bin Ren, Yanzhi Wang, Xue Lin (2021). Neural Pruning Search for Real-Time Object Detection of Autonomous Vehicles. In DAC 2021.

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Siyue Wang, Pu Zhao, Xiao Wang, Sang Chin, Thomas Wahl, Yunsi Fei, Qi Chen, Xue Lin (2021). Intrinsic Examples: Robust Fingerprinting of Deep Neural Networks. In BMVC 2021.

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Zheng Zhan, Yifan Gong, Pu Zhao, Geng Yuan, Wei Niu, Yushu Wu, Tianyun Zhang, Malith Jayaweera, David Kaeli, Bin Ren, Xue Lin, Yanzhi Wang (2021). Achieving On-Mobile Real-Time Super-Resolution With Neural Architecture and Pruning Search. In ICCV 2021.

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Mengshu Sun, Pu Zhao, Xue Lin (2021). Power management in hybrid electric vehicles using deep recurrent reinforcement learning. In Electrical Engineering.

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Siyue Wang, Xiao Wang, Pin-Yu Chen, Pu Zhao, Xue Lin (2021). Characteristic Examples: High-Robustness, Low-Transferability Fingerprinting of Neural Networks. In IJCAI 2021.

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Zhengang Li, Geng Yuan, Wei Niu, Pu Zhao, Yanyu Li, Yuxuan Cai, Xuan Shen, Zheng Zhan, Zhenglun Kong, Qing Jin, Zhiyu Chen, Sijia Liu, Kaiyuan Yang, Bin Ren, Yanzhi Wang, Xue Lin (2021). NPAS: A Compiler-Aware Framework of Unified Network Pruning and Architecture Search for Beyond Real-Time Mobile Acceleration. In CVPR 2021.

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Hui Guan, Shaoshan Liu, Xiaolong Ma, Wei Niu, Bin Ren, Xipeng Shen, Yanzhi Wang, Pu Zhao (2021). CoCoPIE: Enabling Real-Time AI on Off-the-Shelf Mobile Devices via Compression-Compilation Co-Design. In CACM.

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Pu Zhao, Wei Niu, Geng Yuan, Yuxuan Cai, Hsin-Hsuan Sung, Shaoshan Liu, Sijia Liu, Xipeng Shen, Bin Ren, Yanzhi Wang, Xue Lin (2021). Brief Industry Paper: Towards Real-Time 3D Object Detection for Autonomous Vehicles with Pruning Search. In RTAS 2021.

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Wei Niu, Pu Zhao, Zheng Zhan, Xue Lin, Yanzhi Wang, Bin Ren (2021). Towards Real-Time DNN Inference on Mobile Platforms with Model Pruning and Compiler Optimization. In IJCAI-PRICAI 2020.

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Shi Dong, Pu Zhao, Xue Lin, David Kaeli (2020). Exploring GPU acceleration of Deep Neural Networks using Block Circulant Matrices. In Parallel Computing.

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Mengshu Sun, Pu Zhao, Mehmet Gungor, Massoud Pedram, Miriam Leeser, Xue Lin (2020). 3D CNN Acceleration on FPGA using Hardware-Aware Pruning. In DAC 2020.

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Pu Zhao, Pin-Yu Chen, Payel Das, Karthikeyan Natesan Ramamurthy, Xue Lin (2020). Bridging Mode Connectivity in Loss Landscapes and Adversarial Robustness. In ICLR 2020.

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Pu Zhao, Pin-Yu Chen, Siyue Wang, Xue Lin (2020). Towards query-efficient black-box adversary with zeroth-order natural gradient descent. In AAAI 2020.

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Tsui-Wei Weng, Pu Zhao, Sijia Liu, Pin-Yu Chen, Xue Lin, Luca Daniel (2020). Towards certificated model robustness against weight perturbations. In AAAI 2020.

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Pu Zhao, Sijia Liu, Pin-Yu Chen, Trong Nghia Hoang, Kaidi Xu, Bhavya Kailkhura, Xue Lin (2019). On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method. In ICCV 2019.

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Pu Zhao, Siyue Wang, Cheng Gongye, Yanzhi Wang, Yunsi Fei, Xue Lin (2019). Fault Sneaking Attack: a Stealthy Framework for Misleading Deep Neural Networks. In DAC 2019.

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Mengshu Sun, Pu Zhao, Yanzhi Wang, Naehyuck Chang, Xue Lin (2019). HSIM-DNN: Hardware Simulator for Computation-, Storage- and Power-Efficient Deep Neural Networks. In GLSVLSI 2019.

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Kaidi Xu, Sijia Liu, Pu Zhao, Pin-Yu Chen, Huan Zhang, Quanfu Fan, Deniz Erdogmus, Yanzhi Wang, Xue Lin (2019). Structured Adversarial Attack: Towards General Implementation and Better Interpretability. In ICLR 2019.

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Pu Zhao, Kaidi Xu, Sijia Liu, Yanzhi Wang, Xue Lin (2019). Admm attack: an enhanced adversarial attack for deep neural networks with undetectable distortions. In ASP-DAC 2019.

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Pu Zhao, Kaidi Xu, Tianyun Zhang, Makan Fardad, Yanzhi Wang, Xue Lin (2018). Reinforced Adversarial Attacks on Deep Neural Networks Using ADMM. In GlobalSIP 2018.

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Siyue Wang, Xiao Wang, Shaokai Ye, Pu Zhao, Xue Lin (2018). Defending DNN Adversarial Attacks with Pruning and Logits Augmentation. In GlobalSIP 2018.

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Siyue Wang, Xiao Wang, Pu Zhao, Wujie Wen, David Kaeli, Peter Chin, Xue Lin (2018). Defensive Dropout for Hardening Deep Neural Networks under Adversarial Attacks. In ICCAD 2018.

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Pu Zhao, Sijia Liu, Yanzhi Wang, Xue Lin (2018). An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks. In ACM MM 2018.

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Pu Zhao, Yanzhi Wang, Naehyuck Chang, Qi Zhu, Xue Lin (2018). A Deep Reinforcement Learning Framework for Optimizing Fuel Economy of Hybrid Electric Vehicles. In ASP-DAC 2018.

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Pu Zhao, Xue Lin, Yanzhi Wang, Shuang Chen, Massoud Pedram (2017). A Hierarchical Resource Allocation and Consolidation Framework in a Multi-Core Server Cluster Using a Markov Decision Process Model. In IET-CPS.

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Pu Zhao, Meng Zhang, Hui Yu, Hanwen Luo, Wen Chen (2015). Robust Beamforming Design for Sum Secrecy Rate Optimization in MU-MISO Networks. In T TFS.

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