A fully automated technique for constructing FSM abstractions of non-ideal latches in communication systems. - Aadithya V. Karthik; Yingyan Lin; Chenjie Gu; Aolin Xu 001; Jaijeet S. Roychowdhury; Naresh R. Shanbhag (ICASSP, 2012)

Variation-Tolerant Architectures for Convolutional Neural Networks in the Near Threshold Voltage Regime. - Yingyan Lin; Sai Zhang; Naresh R. Shanbhag (SiPS, 2016)

A Study of BER-Optimal ADC-Based Receiver for Serial Links. - Yingyan Lin; Min-Sun Keel; Adam C. Faust; Aolin Xu 001; Naresh R. Shanbhag; Elyse Rosenbaum; Andrew C. Singer (IEEE Trans. Circuits Syst. I Regul. Pap., 2016)

PredictiveNet: An energy-efficient convolutional neural network via zero prediction. - Yingyan Lin; Charbel Sakr; Yongjune Kim 001; Naresh R. Shanbhag (ISCAS, 2017)

Energy-efficient systems for information transfer and processing - Yingyan (Celine) Lin (2017)

Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions. - Junru Wu; Yue Wang 036; Zhenyu Wu 002; Zhangyang Wang; Ashok Veeraraghavan; Yingyan Lin (ICML, 2018)

Energy-efficient Convolutional Neural Networks via Statistical Error Compensated Near Threshold Computing. - Yingyan Lin; Joseph R. Cavallaro (ISCAS, 2018)

On-Demand Deep Model Compression for Mobile Devices: A Usage-Driven Model Selection Framework. - Sicong Liu 005; Yingyan Lin; Zimu Zhou; Kaiming Nan; Hui Liu 006; Junzhao Du (MobiSys, 2018)

ASTRO: Autonomous, Sensing, and Tetherless netwoRked drOnes. - Riccardo Petrolo; Yingyan Lin; Edward W. Knightly (DroNet@MobiSys, 2018)

A Rank Decomposed Statistical Error Compensation Technique for Robust Convolutional Neural Networks in the Near Threshold Voltage Regime. - Yingyan Lin; Sai Zhang; Naresh R. Shanbhag (J. Signal Process. Syst., 2018)

Live Demonstration: Bringing Powerful Deep Learning into Daily-Life Devices (Mobiles and FPGAs) Via Deep k-Means. - Pengfei Xu 011; Yue Wang 036; Yang Zhao 013; Yingyan Lin (ISCAS, 2019)

E2-Train: Training State-of-the-art CNNs with Over 80% Energy Savings. - Yue Wang 036; Ziyu Jiang; Xiaohan Chen; Pengfei Xu 011; Yang Zhao 013; Yingyan Lin; Zhangyang Wang (NeurIPS, 2019)

Drawing early-bird tickets: Towards more efficient training of deep networks. - Haoran You; Chaojian Li; Pengfei Xu 011; Yonggan Fu; Yue Wang 036; Xiaohan Chen; Yingyan Lin; Zhangyang Wang; Richard G. Baraniuk (CoRR, 2019)

E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving. - Yue Wang 036; Ziyu Jiang; Xiaohan Chen; Pengfei Xu 011; Yang Zhao 013; Yingyan Lin; Zhangyang Wang (CoRR, 2019)

Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference. - Jianghao Shen; Yue Wang 036; Pengfei Xu 011; Yonggan Fu; Zhangyang Wang; Yingyan Lin (AAAI, 2020)

HALO: Hardware-Aware Learning to Optimize. - Chaojian Li; Tianlong Chen 001; Haoran You; Zhangyang Wang; Yingyan Lin (ECCV (9), 2020)

AutoDNNchip: An Automated DNN Chip Predictor and Builder for Both FPGAs and ASICs. - Pengfei Xu 011; Xiaofan Zhang 001; Cong Hao; Yang Zhao 013; Yongan Zhang; Yue Wang 036; Chaojian Li; Zetong Guan; Deming Chen; Yingyan Lin (FPGA, 2020)

DNN-Chip Predictor: An Analytical Performance Predictor for DNN Accelerators with Various Dataflows and Hardware Architectures. - Yang Zhao 013; Chaojian Li; Yue Wang 036; Pengfei Xu 011; Yongan Zhang; Yingyan Lin (ICASSP, 2020)

Drawing Early-Bird Tickets: Toward More Efficient Training of Deep Networks. - Haoran You; Chaojian Li; Pengfei Xu 011; Yonggan Fu; Yue Wang 036; Xiaohan Chen; Richard G. Baraniuk; Zhangyang Wang; Yingyan Lin (ICLR, 2020)

AutoGAN-Distiller: Searching to Compress Generative Adversarial Networks. - Yonggan Fu; Wuyang Chen 001; Haotao Wang; Haoran Li; Yingyan Lin; Zhangyang Wang (ICML, 2020)

Timely: Pushing Data Movements And Interfaces In Pim Accelerators Towards Local And In Time Domain. - Weitao Li; Pengfei Xu 011; Yang Zhao 013; Haitong Li; Yuan Xie 001; Yingyan Lin (ISCA, 2020)

SmartExchange: Trading Higher-cost Memory Storage/Access for Lower-cost Computation. - Yang Zhao 013; Xiaohan Chen; Yue Wang 036; Chaojian Li; Haoran You; Yonggan Fu; Yuan Xie 001; Zhangyang Wang; Yingyan Lin (ISCA, 2020)

A New MRAM-Based Process In-Memory Accelerator for Efficient Neural Network Training with Floating Point Precision. - Hongjie Wang 002; Yang Zhao 013; Chaojian Li; Yue Wang 036; Yingyan Lin (ISCAS, 2020)

FracTrain: Fractionally Squeezing Bit Savings Both Temporally and Spatially for Efficient DNN Training. - Yonggan Fu; Haoran You; Yang Zhao 013; Yue Wang 036; Chaojian Li; Kailash Gopalakrishnan; Zhangyang Wang; Yingyan Lin (NeurIPS, 2020)

ShiftAddNet: A Hardware-Inspired Deep Network. - Haoran You; Xiaohan Chen; Yongan Zhang; Chaojian Li; Sicheng Li 001; Zihao Liu; Zhangyang Wang; Yingyan Lin (NeurIPS, 2020)

Bringing Powerful Machine-Learning Systems to Daily-Life Devices via Algorithm-Hardware Co-Design. - Yingyan Lin (VLSI-DAT, 2020)

AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles. - Sicong Liu 005; Junzhao Du; Kaiming Nan; Zimu Zhou; Atlas Wang; Yingyan Lin (CoRR, 2020)

DNA: Differentiable Network-Accelerator Co-Search. - Yongan Zhang; Yonggan Fu; Weiwen Jiang; Chaojian Li; Haoran You; Meng Li 004; Vikas Chandra; Yingyan Lin (CoRR, 2020)

Auto-Agent-Distiller: Towards Efficient Deep Reinforcement Learning Agents via Neural Architecture Search. - Yonggan Fu; Zhongzhi Yu; Yongan Zhang; Yingyan Lin (CoRR, 2020)

Dual Dynamic Inference: Enabling More Efficient, Adaptive, and Controllable Deep Inference. - Yue Wang 036; Jianghao Shen; Ting-Kuei Hu; Pengfei Xu 011; Tan M. Nguyen; Richard G. Baraniuk; Zhangyang Wang; Yingyan Lin (IEEE J. Sel. Top. Signal Process., 2020)

InstantNet: Automated Generation and Deployment of Instantaneously Switchable-Precision Networks. - Yonggan Fu; Zhongzhi Yu; Yongan Zhang; Yifan Jiang 001; Chaojian Li; Yongyuan Liang; Mingchao Jiang; Zhangyang Wang; Yingyan Lin (DAC, 2021)

A3C-S: Automated Agent Accelerator Co-Search towards Efficient Deep Reinforcement Learning. - Yonggan Fu; Yongan Zhang; Chaojian Li; Zhongzhi Yu; Yingyan Lin (DAC, 2021)

Toward reconfigurable kernel datapaths with learned optimizations. - Yiming Qiu; Hongyi Liu; Thomas E. Anderson; Yingyan Lin; Ang Chen 001 (HotOS, 2021)

O-HAS: Optical Hardware Accelerator Search for Boosting Both Acceleration Performance and Development Speed. - Mengquan Li; Zhongzhi Yu; Yongan Zhang; Yonggan Fu; Yingyan Lin (ICCAD, 2021)

G-CoS: GNN-Accelerator Co-Search Towards Both Better Accuracy and Efficiency. - Yongan Zhang; Haoran You; Yonggan Fu; Tong Geng; Ang Li 006; Yingyan Lin (ICCAD, 2021)

SACoD: Sensor Algorithm Co-Design Towards Efficient CNN-powered Intelligent PhlatCam. - Yonggan Fu; Yang Zhang 001; Yue Wang 036; Zhihan Lu; Vivek Boominathan; Ashok Veeraraghavan; Yingyan Lin (ICCV, 2021)

CPT: Efficient Deep Neural Network Training via Cyclic Precision. - Yonggan Fu; Han Guo; Meng Li 004; Xin Yang; Yining Ding; Vikas Chandra; Yingyan Lin (ICLR, 2021)

HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark. - Chaojian Li; Zhongzhi Yu; Yonggan Fu; Yongan Zhang; Yang Zhao 013; Haoran You; Qixuan Yu 001; Yue Wang 036; Cong Hao; Yingyan Lin (ICLR, 2021)

Double-Win Quant: Aggressively Winning Robustness of Quantized Deep Neural Networks via Random Precision Training and Inference. - Yonggan Fu; Qixuan Yu 001; Meng Li 004; Vikas Chandra; Yingyan Lin (ICML, 2021)

Auto-NBA: Efficient and Effective Search Over the Joint Space of Networks, Bitwidths, and Accelerators. - Yonggan Fu; Yongan Zhang; Yang Zhang 001; David D. Cox; Yingyan Lin (ICML, 2021)

DIAN: Differentiable Accelerator-Network Co-Search Towards Maximal DNN Efficiency. - Yongan Zhang; Yonggan Fu; Weiwen Jiang; Chaojian Li; Haoran You; Meng Li 004; Vikas Chandra; Yingyan Lin (ISLPED, 2021)

2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency. - Yonggan Fu; Yang Zhao 013; Qixuan Yu 001; Chaojian Li; Yingyan Lin (MICRO, 2021)

I-GCN: A Graph Convolutional Network Accelerator with Runtime Locality Enhancement through Islandization. - Tong Geng; Chunshu Wu; Yongan Zhang; Cheng Tan 002; Chenhao Xie 001; Haoran You; Martin C. Herbordt; Yingyan Lin; Ang Li 006 (MICRO, 2021)

Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks. - Yonggan Fu; Qixuan Yu 001; Yang Zhang 001; Shang Wu 003; Xu Ouyang; David D. Cox; Yingyan Lin (NeurIPS, 2021)

Locality Sensitive Teaching. - Zhaozhuo Xu; Beidi Chen; Chaojian Li; Weiyang Liu; Le Song; Yingyan Lin; Anshumali Shrivastava (NeurIPS, 2021)

SmartDeal: Re-Modeling Deep Network Weights for Efficient Inference and Training. - Xiaohan Chen; Yang Zhao 013; Yue Wang 036; Pengfei Xu 011; Haoran You; Chaojian Li; Yonggan Fu; Yingyan Lin; Zhangyang Wang (CoRR, 2021)

Max-Affine Spline Insights Into Deep Network Pruning. - Randall Balestriero; Haoran You; Zhihan Lu; Yutong Kou; Yingyan Lin; Richard G. Baraniuk (CoRR, 2021)

GEBT: Drawing Early-Bird Tickets in Graph Convolutional Network Training. - Haoran You; Zhihan Lu; Zijian Zhou; Yingyan Lin (CoRR, 2021)

HW-NAS-Bench: Hardware-Aware Neural Architecture Search Benchmark. - Chaojian Li; Zhongzhi Yu; Yonggan Fu; Yongan Zhang; Yang Zhao 013; Haoran You; Qixuan Yu 001; Yue Wang 036; Yingyan Lin (CoRR, 2021)

FBNetV5: Neural Architecture Search for Multiple Tasks in One Run. - Bichen Wu; Chaojian Li; Hang Zhang 005; Xiaoliang Dai; Peizhao Zhang; Matthew Yu; Jialiang Wang 001; Yingyan Lin; Peter Vajda (CoRR, 2021)

Introduction of Special Issue on Hardware and Algorithms for Efficient Machine Learning-Part 1. - Yiran Chen 001; Qinru Qiu; Yingyan Lin (ACM J. Emerg. Technol. Comput. Syst., 2021)

Introduction to the Special Issue on Hardware and Algorithms for Efficient Machine Learning - Part 2. - Yiran Chen 001; Qinru Qiu; Yingyan Lin (ACM J. Emerg. Technol. Comput. Syst., 2021)

Practical Attacks on Deep Neural Networks by Memory Trojaning. - Xing Hu 001; Yang Zhao 013; Lei Deng 003; Ling Liang; Pengfei Zuo; Jing Ye 001; Yingyan Lin; Yuan Xie 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021)

ASTRO: A System for Off-grid Networked Drone Sensing Missions. - Riccardo Petrolo; Zhambyl Shaikhanov; Yingyan Lin; Edward W. Knightly (ACM Trans. Internet Things, 2021)

AdaDeep: A Usage-Driven, Automated Deep Model Compression Framework for Enabling Ubiquitous Intelligent Mobiles. - Sicong Liu 005; Junzhao Du; Kaiming Nan; Zimu Zhou; Hui Liu 006; Zhangyang Wang; Yingyan Lin (IEEE Trans. Mob. Comput., 2021)

Early-Bird GCNs: Graph-Network Co-optimization towards More Efficient GCN Training and Inference via Drawing Early-Bird Lottery Tickets. - Haoran You; Zhihan Lu; Zijian Zhou; Yonggan Fu; Yingyan Lin (AAAI, 2022)

MIA-Former: Efficient and Robust Vision Transformers via Multi-Grained Input-Adaptation. - Zhongzhi Yu; Yonggan Fu; Sicheng Li 001; Chaojian Li; Yingyan Lin (AAAI, 2022)

Contrastive quant: quantization makes stronger contrastive learning. - Yonggan Fu; Qixuan Yu 001; Meng Li 004; Xu Ouyang; Vikas Chandra; Yingyan Lin (DAC, 2022)

INGeo: Accelerating Instant Neural Scene Reconstruction with Noisy Geometry Priors. - Chaojian Li; Bichen Wu; Albert Pumarola; Peizhao Zhang; Yingyan Lin; Peter Vajda (ECCV Workshops (3), 2022)

SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning. - Haoran You; Baopu Li; Zhanyi Sun; Xu Ouyang; Yingyan Lin (ECCV (11), 2022)

FCsN: A FPGA-Centric SmartNIC Framework for Neural Networks. - Anqi Guo; Tong Geng; Yongan Zhang; Pouya Haghi; Chunshu Wu; Cheng Tan 002; Yingyan Lin; Ang Li 006; Martin C. Herbordt (FCCM, 2022)

A Framework for Neural Network Inference on FPGA-Centric SmartNICs. - Anqi Guo; Tong Geng; Yongan Zhang; Pouya Haghi; Chunshu Wu; Cheng Tan 002; Yingyan Lin; Ang Li 006; Martin C. Herbordt (FPL, 2022)

GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design. - Haoran You; Tong Geng; Yongan Zhang; Ang Li 006; Yingyan Lin (HPCA, 2022)

RT-NeRF: Real-Time On-Device Neural Radiance Fields Towards Immersive AR/VR Rendering. - Chaojian Li; Sixu Li; Yang Zhao 013; Wenbo Zhu; Yingyan Lin (ICCAD, 2022)

NASA: Neural Architecture Search and Acceleration for Hardware Inspired Hybrid Networks. - Huihong Shi; Haoran You; Yang Zhao 013; Zhongfeng Wang 001; Yingyan Lin (ICCAD, 2022)

Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations? - Yonggan Fu; Shunyao Zhang; Shang Wu 003; Cheng Wan 005; Yingyan Lin (ICLR, 2022)

PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication. - Cheng Wan 005; Youjie Li; Cameron R. Wolfe; Anastasios Kyrillidis; Nam Sung Kim; Yingyan Lin (ICLR, 2022)

DepthShrinker: A New Compression Paradigm Towards Boosting Real-Hardware Efficiency of Compact Neural Networks. - Yonggan Fu; Haichuan Yang; Jiayi Yuan 001; Meng Li 004; Cheng Wan 005; Raghuraman Krishnamoorthi; Vikas Chandra; Yingyan Lin (ICML, 2022)

ShiftAddNAS: Hardware-Inspired Search for More Accurate and Efficient Neural Networks. - Haoran You; Baopu Li; Huihong Shi; Yonggan Fu; Yingyan Lin (ICML, 2022)

EyeCoD: eye tracking system acceleration via flatcam-based algorithm & accelerator co-design. - Haoran You; Cheng Wan 005; Yang Zhao 013; Zhongzhi Yu; Yonggan Fu; Jiayi Yuan 001; Shang Wu 003; Shunyao Zhang; Yongan Zhang; Chaojian Li; Vivek Boominathan; Ashok Veeraraghavan; et al. (ISCA, 2022)

BNS-GCN: Efficient Full-Graph Training of Graph Convolutional Networks with Partition-Parallelism and Random Boundary Node Sampling. - Cheng Wan 005; Youjie Li; Ang Li 006; Nam Sung Kim; Yingyan Lin (MLSys, 2022)

Losses Can Be Blessings: Routing Self-Supervised Speech Representations Towards Efficient Multilingual and Multitask Speech Processing. - Yonggan Fu; Yang Zhang 001; Kaizhi Qian; Zhifan Ye; Zhongzhi Yu; Cheng-I Jeff Lai; Celine Lin (NeurIPS, 2022)

i-FlatCam: A 253 FPS, 91.49 µJ/Frame Ultra-Compact Intelligent Lensless Camera for Real-Time and Efficient Eye Tracking in VR/AR. - Yang Zhao 013; Ziyun Li; Yonggan Fu; Yongan Zhang; Chaojian Li; Cheng Wan 005; Haoran You; Shang Wu 003; Xu Ouyang; Vivek Boominathan; Ashok Veeraraghavan; Yingyan Lin (VLSI Technology and Circuits, 2022)

e-G2C: A 0.14-to-8.31 µJ/Inference NN-based Processor with Continuous On-chip Adaptation for Anomaly Detection and ECG Conversion from EGM. - Yang Zhao 013; Yongan Zhang; Yonggan Fu; Xu Ouyang; Cheng Wan 005; Shang Wu 003; Anton Banta; Mathews M. John; Allison Post; Mehdi Razavi; Joseph R. Cavallaro; Behnaam Aazhang; et al. (VLSI Technology and Circuits, 2022)

LDP: Learnable Dynamic Precision for Efficient Deep Neural Network Training and Inference. - Zhongzhi Yu; Yonggan Fu; Shang Wu 003; Mengquan Li; Haoran You; Yingyan Lin (CoRR, 2022)

Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention During Vision Transformer Inference. - Haoran You; Yunyang Xiong; Xiaoliang Dai; Bichen Wu; Peizhao Zhang; Haoqi Fan 001; Peter Vajda; Yingyan Lin (CoRR, 2022)

RT-RCG: Neural Network and Accelerator Search Towards Effective and Real-time ECG Reconstruction from Intracardiac Electrograms. - Yongan Zhang; Anton Banta; Yonggan Fu; Mathews M. John; Allison Post; Mehdi Razavi; Joseph R. Cavallaro; Behnaam Aazhang; Yingyan Lin (ACM J. Emerg. Technol. Comput. Syst., 2022)

Max-Affine Spline Insights Into Deep Network Pruning. - Haoran You; Randall Balestriero; Zhihan Lu; Yutong Kou; Huihong Shi; Shunyao Zhang; Shang Wu 003; Yingyan Lin; Richard G. Baraniuk (Trans. Mach. Learn. Res., 2022)

DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference. - Chaojian Li; Wuyang Chen 001; Yuchen Gu; Tianlong Chen 001; Yonggan Fu; Zhangyang Wang; Yingyan Lin (ACM Trans. Design Autom. Electr. Syst., 2022)

Auto-CARD: Efficient and Robust Codec Avatar Driving for Real-time Mobile Telepresence. - Yonggan Fu; Yuecheng Li; Chenghui Li; Jason M. Saragih; Peizhao Zhang; Xiaoliang Dai; Yingyan Celine Lin (CVPR, 2023)

Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention at Vision Transformer Inference. - Haoran You; Yunyang Xiong; Xiaoliang Dai; Bichen Wu; Peizhao Zhang; Haoqi Fan 001; Peter Vajda; Yingyan Celine Lin (CVPR, 2023)

Hint-Aug: Drawing Hints from Foundation Vision Transformers towards Boosted Few-shot Parameter-Efficient Tuning. - Zhongzhi Yu; Shang Wu 003; Yonggan Fu; Shunyao Zhang; Yingyan Celine Lin (CVPR, 2023)

Robust Tickets Can Transfer Better: Drawing More Transferable Subnetworks in Transfer Learning. - Yonggan Fu; Ye Yuan; Shang Wu 003; Jiayi Yuan 001; Yingyan Celine Lin (DAC, 2023)

NetBooster: Empowering Tiny Deep Learning By Standing on the Shoulders of Deep Giants. - Zhongzhi Yu; Yonggan Fu; Jiayi Yuan 001; Haoran You; Yingyan Celine Lin (DAC, 2023)

Instant-NeRF: Instant On-Device Neural Radiance Field Training via Algorithm-Accelerator Co-Designed Near-Memory Processing. - Yang Katie Zhao; Shang Wu 003; Jingqun Zhang; Sixu Li; Chaojian Li; Yingyan Celine Lin (DAC, 2023)

ViTALiTy: Unifying Low-rank and Sparse Approximation for Vision Transformer Acceleration with a Linear Taylor Attention. - Jyotikrishna Dass; Shang Wu 003; Huihong Shi; Chaojian Li; Zhifan Ye; Zhongfeng Wang 001; Yingyan Lin (HPCA, 2023)

ViTCoD: Vision Transformer Acceleration via Dedicated Algorithm and Accelerator Co-Design. - Haoran You; Zhanyi Sun; Huihong Shi; Zhongzhi Yu; Yang Zhao 013; Yongan Zhang; Chaojian Li; Baopu Li; Yingyan Lin (HPCA, 2023)

ERSAM: Neural Architecture Search for Energy-Efficient and Real-Time Social Ambiance Measurement. - Chaojian Li; Wenwan Chen; Jiayi Yuan 001; Yingyan Celine Lin; Ashutosh Sabharwal (ICASSP, 2023)

GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models. - Yonggan Fu; Yongan Zhang; Zhongzhi Yu; Sixu Li; Zhifan Ye; Chaojian Li; Cheng Wan 005; Yingyan Celine Lin (ICCAD, 2023)

NeRFool: Uncovering the Vulnerability of Generalizable Neural Radiance Fields against Adversarial Perturbations. - Yonggan Fu; Ye Yuan; Souvik Kundu 009; Shang Wu 003; Shunyao Zhang; Yingyan Celine Lin (ICML, 2023)

Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning. - Zhongzhi Yu; Yang Zhang 001; Kaizhi Qian; Cheng Wan 005; Yonggan Fu; Yongan Zhang; Yingyan Celine Lin (ICML, 2023)

Gen-NeRF: Efficient and Generalizable Neural Radiance Fields via Algorithm-Hardware Co-Design. - Yonggan Fu; Zhifan Ye; Jiayi Yuan 001; Shunyao Zhang; Sixu Li; Haoran You; Yingyan Lin (ISCA, 2023)

Instant-3D: Instant Neural Radiance Field Training Towards On-Device AR/VR 3D Reconstruction. - Sixu Li; Chaojian Li; Wenbo Zhu; Boyang Tony Yu; Yang Katie Zhao; Cheng Wan 005; Haoran You; Huihong Shi; Yingyan Celine Lin (ISCA, 2023)

ShiftAddViT: Mixture of Multiplication Primitives Towards Efficient Vision Transformer. - Haoran You; Huihong Shi; Yipin Guo; Yingyan Lin (NeurIPS, 2023)

Memory-Based Computing for Energy-Efficient AI: Grand Challenges. - Foroozan Karimzadeh; Mohsen Imani; Bahar Asgari; Ningyuan Cao; Yingyan Lin; Yan Fang (VLSI-SoC, 2023)

A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware. - Shichang Zhang; Atefeh Sohrabizadeh; Cheng Wan 005; Zijie Huang 002; Ziniu Hu; Yewen Wang; Yingyan Lin; Jason Cong; Yizhou Sun (CoRR, 2023)

Master-ASR: Achieving Multilingual Scalability and Low-Resource Adaptation in ASR with Modular Learning. - Zhongzhi Yu; Yang Zhang 001; Kaizhi Qian; Yonggan Fu; Yingyan Lin (CoRR, 2023)

EyeCoD: Eye Tracking System Acceleration via FlatCam-Based Algorithm and Hardware Co-Design. - Haoran You; Yang Zhao 013; Cheng Wan 005; Zhongzhi Yu; Yonggan Fu; Jiayi Yuan 001; Shang Wu 003; Shunyao Zhang; Yongan Zhang; Chaojian Li; Vivek Boominathan; Ashok Veeraraghavan; et al. (IEEE Micro, 2023)

NetDistiller: Empowering Tiny Deep Learning via In Situ Distillation. - Shunyao Zhang; Yonggan Fu; Shang Wu 003; Jyotikrishna Dass; Haoran You; Yingyan Lin (IEEE Micro, 2023)

NASA+: Neural Architecture Search and Acceleration for Multiplication-Reduced Hybrid Networks. - Huihong Shi; Haoran You; Zhongfeng Wang 001; Yingyan Lin (IEEE Trans. Circuits Syst. I Regul. Pap., 2023)

SmartDeal: Remodeling Deep Network Weights for Efficient Inference and Training. - Xiaohan Chen; Yang Zhao 013; Yue Wang 036; Pengfei Xu 011; Haoran You; Chaojian Li; Yonggan Fu; Yingyan Lin; Zhangyang Wang (IEEE Trans. Neural Networks Learn. Syst., 2023)

MixRT: Mixed Neural Representations For Real-Time NeRF Rendering. - Chaojian Li; Bichen Wu; Peter Vajda; Yingyan Lin (3DV, 2024)

EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Unified Compression and Adaptive Layer Voting. - Zhongzhi Yu; Zheng Wang; Yuhan Li; Ruijie Gao; Xiaoya Zhou; Sreenidhi Reddy Bommu; Yang Katie Zhao; Yingyan (Celine) Lin (DAC, 2024)

3D-Carbon: An Analytical Carbon Modeling Tool for 3D and 2.5D Integrated Circuits. - Yujie Zhao; Yang Katie Zhao; Cheng Wan 005; Yingyan Celine Lin (DAC, 2024)

Omni-Recon: Harnessing Image-Based Rendering for General-Purpose Neural Radiance Fields. - Yonggan Fu; Huaizhi Qu; Zhifan Ye; Chaojian Li; Kevin Zhao; Yingyan Lin (ECCV (16), 2024)

Invited Paper: LLM4HWDesign Contest: Constructing a Comprehensive Dataset for LLM-Assisted Hardware Code Generation with Community Efforts. - Zhongzhi Yu; Chaojian Li; Yongan Zhang; Mingjie Liu; Nathaniel Ross Pinckney; Wenfei Zhou; Haoyu Yang; Rongjian Liang; Haoxing Ren; Yingyan Celine Lin (ICCAD, 2024)

When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models. - Haoran You; Yichao Fu; Zheng Wang; Amir Yazdanbakhsh; Yingyan Celine Lin (ICML, 2024)

Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration. - Zhongzhi Yu; Zheng Wang; Yonggan Fu; Huihong Shi; Khalid Shaikh 002; Yingyan Celine Lin (ICML, 2024)

Towards Cognitive AI Systems: Workload and Characterization of Neuro-Symbolic AI. - Zishen Wan; Che-Kai Liu; Hanchen Yang; Ritik Raj; Chaojian Li; Haoran You; Yonggan Fu; Cheng Wan 005; Ananda Samajdar; Yingyan Celine Lin; Tushar Krishna; Arijit Raychowdhury (ISPASS, 2024)

Fusion-3D: Integrated Acceleration for Instant 3D Reconstruction and Real-Time Rendering. - Sixu Li; Yang Zhao 013; Chaojian Li; Bowei Guo; Jingqun Zhang; Wenbo Zhu; Zhifan Ye; Cheng Wan 005; Yingyan Celine Lin (MICRO, 2024)

AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment. - Yonggan Fu; Zhongzhi Yu; Junwei Li; Jiayi Qian; Yongan Zhang; Xiangchi Yuan; Dachuan Shi; Roman Yakunin; Yingyan (Celine) Lin (NeurIPS, 2024)

Rad-NeRF: Ray-decoupled Training of Neural Radiance Field. - Lidong Guo; Xuefei Ning; Yonggan Fu; Tianchen Zhao; Zhuoliang Kang; Jincheng Yu; Yingyan (Celine) Lin; Yu Wang 002 (NeurIPS, 2024)

3D Gaussian Rendering Can Be Sparser: Efficient Rendering via Learned Fragment Pruning. - Zhifan Ye; Chenxi Wan; Chaojian Li; Jihoon Hong; Sixu Li; Leshu Li; Yongan Zhang; Yingyan (Celine) Lin (NeurIPS, 2024)

ShiftAddLLM: Accelerating Pretrained LLMs via Post-Training Multiplication-Less Reparameterization. - Haoran You; Yipin Guo; Yichao Fu; Wei Zhou; Huihong Shi; Xiaofan Zhang 001; Souvik Kundu 009; Amir Yazdanbakhsh; Yingyan (Celine) Lin (NeurIPS, 2024)

Towards Cognitive AI Systems: a Survey and Prospective on Neuro-Symbolic AI. - Zishen Wan; Che-Kai Liu; Hanchen Yang; Chaojian Li; Haoran You; Yonggan Fu; Cheng Wan 005; Tushar Krishna; Yingyan Lin; Arijit Raychowdhury (CoRR, 2024)

Omni-Recon: Towards General-Purpose Neural Radiance Fields for Versatile 3D Applications. - Yonggan Fu; Huaizhi Qu; Zhifan Ye; Chaojian Li; Kevin Zhao; Yingyan Lin (CoRR, 2024)

EDGE-LLM: Enabling Efficient Large Language Model Adaptation on Edge Devices via Layerwise Unified Compression and Adaptive Layer Tuning and Voting. - Zhongzhi Yu; Zheng Wang; Yuhan Li; Haoran You; Ruijie Gao; Xiaoya Zhou; Sreenidhi Reddy Bommu; Yang Katie Zhao; Yingyan Celine Lin (CoRR, 2024)

MG-Verilog: Multi-grained Dataset Towards Enhanced LLM-assisted Verilog Generation. - Yongan Zhang; Zhongzhi Yu; Yonggan Fu; Cheng Wan 005; Yingyan Celine Lin (CoRR, 2024)

Towards Efficient Neuro-Symbolic AI: From Workload Characterization to Hardware Architecture. - Zishen Wan; Che-Kai Liu; Hanchen Yang; Ritik Raj; Chaojian Li; Haoran You; Yonggan Fu; Cheng Wan 005; Sixu Li; Youbin Kim; Ananda Samajdar; Yingyan Celine Lin; et al. (CoRR, 2024)

An Investigation on Hardware-Aware Vision Transformer Scaling. - Chaojian Li; Kyungmin Kim 002; Bichen Wu; Peizhao Zhang; Hang Zhang 005; Xiaoliang Dai; Peter Vajda; Yingyan (Celine) Lin (ACM Trans. Embed. Comput. Syst., 2024)

AutoAI2C: An Automated Hardware Generator for DNN Acceleration on Both FPGA and ASIC. - Yongan Zhang; Xiaofan Zhang 001; Pengfei Xu 011; Yang Zhao 013; Cong Hao; Deming Chen; Yingyan Lin (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

Early-Bird Diffusion: Investigating and Leveraging Timestep-Aware Early-Bird Tickets in Diffusion Models for Efficient Training. - Lexington Whalen; Zhenbang Du; Haoran You; Chaojian Li; Sixu Li; Yingyan Lin (CVPR, 2025)

Layer- and Timestep-Adaptive Differentiable Token Compression Ratios for Efficient Diffusion Transformers. - Haoran You; Connelly Barnes; Yuqian Zhou; Yan Kang; Zhenbang Du; Wei Zhou; Lingzhi Zhang; Yotam Nitzan; Xiaoyang Liu; Zhe Lin; Eli Shechtman; Sohrab Amirghodsi; et al. (CVPR, 2025)

Uni-Render: A Unified Accelerator for Real-Time Rendering Across Diverse Neural Renderers. - Chaojian Li; Sixu Li; Linrui Jiang; Jingqun Zhang; Yingyan Celine Lin (HPCA, 2025)

Gaussian Blending Unit: An Edge GPU Plug-in for Real-Time Gaussian-Based Rendering in AR/VR. - Zhifan Ye; Yonggan Fu; Jingqun Zhang; Leshu Li; Yongan Zhang; Sixu Li; Cheng Wan 005; Chenxi Wan; Chaojian Li; Sreemanth Prathipati; Yingyan Celine Lin (HPCA, 2025)

Hymba: A Hybrid-head Architecture for Small Language Models. - Xin Dong 009; Yonggan Fu; Shizhe Diao; Wonmin Byeon; Zijia Chen; Ameya Sunil Mahabaleshwarkar; Shih-Yang Liu; Matthijs Van Keirsbilck; Min-Hung Chen; Yoshi Suhara; Yingyan Celine Lin; Jan Kautz; et al. (ICLR, 2025)

LongMamba: Enhancing Mamba's Long-Context Capabilities via Training-Free Receptive Field Enlargement. - Zhifan Ye; Kejing Xia; Yonggan Fu; Xin Dong 009; Jihoon Hong; Xiangchi Yuan; Shizhe Diao; Jan Kautz; Pavlo Molchanov 001; Yingyan Celine Lin (ICLR, 2025)

MixGCN: Scalable GCN Training by Mixture of Parallelism and Mixture of Accelerators. - Cheng Wan 005; Runkai Tao; Zheng Du; Yang Katie Zhao; Yingyan Celine Lin (CoRR, 2025)

GauRast: Enhancing GPU Triangle Rasterizers to Accelerate 3D Gaussian Splatting. - Sixu Li; Ben Keller; Yingyan Celine Lin; Brucek Khailany (CoRR, 2025)

Scaling Laws of Graph Neural Networks for Atomistic Materials Modeling. - Chaojian Li; Zhifan Ye; Massimiliano Lupo Pasini; Jong Youl Choi; Cheng Wan 005; Yingyan Celine Lin; Prasanna Balaprakash (CoRR, 2025)

CLIMB: CLustering-based Iterative Data Mixture Bootstrapping for Language Model Pre-training. - Shizhe Diao; Yu Yang; Yonggan Fu; Xin Dong 009; Dan Su 003; Markus Kliegl; Zijia Chen; Peter Belcak; Yoshi Suhara; Hongxu Yin; Mostofa Patwary; Yingyan Lin; et al. (CoRR, 2025)

Small Language Models are the Future of Agentic AI. - Peter Belcak; Greg Heinrich; Shizhe Diao; Yonggan Fu; Xin Dong 009; Saurav Muralidharan; Yingyan Celine Lin; Pavlo Molchanov 001 (CoRR, 2025)

Spec2RTL-Agent: Automated Hardware Code Generation from Complex Specifications Using LLM Agent Systems. - Zhongzhi Yu; Mingjie Liu; Michael Zimmer 006; Yingyan Celine Lin; Yong Liu; Haoxing Ren (CoRR, 2025)

LaCache: Ladder-Shaped KV Caching for Efficient Long-Context Modeling of Large Language Models. - Dachuan Shi; Yonggan Fu; Xiangchi Yuan; Zhongzhi Yu; Haoran You; Sixu Li; Xin Dong 009; Jan Kautz; Pavlo Molchanov 001; Yingyan Lin (CoRR, 2025)

3DGauCIM: Accelerating Static/Dynamic 3D Gaussian Splatting via Digital CIM for High Frame Rate Real-Time Edge Rendering. - Wei-Hsing Huang; Cheng-Jhih Shih; Jian-Wei Su; Samuel Wade Wang; Vaidehi Garg; Yuyao Kong; Jen-Chun Tien; Nealson Li; Arijit Raychowdhury; Meng-Fan Chang; Yingyan Lin; Shimeng Yu (CoRR, 2025)

A3D-MoE: Acceleration of Large Language Models with Mixture of Experts via 3D Heterogeneous Integration. - Wei-Hsing Huang; Janak Sharda; Cheng-Jhih Shih; Yuyao Kong; Faaiq Waqar; Pin-Jun Chen; Yingyan Lin; Shimeng Yu (CoRR, 2025)

Fewer Denoising Steps or Cheaper Per-Step Inference: Towards Compute-Optimal Diffusion Model Deployment. - Zhenbang Du; Yonggan Fu; Lifu Wang; Jiayi Qian; Xiao Luo; Yingyan Lin (CoRR, 2025)

Re-CATA: Real-Time and Flexible Accelerator Design Framework for On-Device Codec Avatars. - Yongan Zhang; Yuecheng Li; Syed Shakib Sarwar; Huseyin Ekin Sumbul; Yonggan Fu; Haoran You; Cheng Wan 005; Yingyan Lin (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)