Bit-level optimization for high-level synthesis and FPGA-based acceleration. - Jiyu Zhang; Zhiru Zhang; Sheng Zhou; Mingxing Tan; Xianhua Liu 001; Xu Cheng 001; Jason Cong (FPGA, 2010)

Energy-efficient branch prediction with Compiler-guided History Stack. - Mingxing Tan; Xianhua Liu 001; Zichao Xie; Dong Tong 001; Xu Cheng 001 (DATE, 2012)

CVP: an energy-efficient indirect branch prediction with compiler-guided value pattern. - Mingxing Tan; Xianhua Liu 001; Tong Tong; Xu Cheng 001 (ICS, 2012)

Flushing-Enabled Loop Pipelining for High-Level Synthesis. - Steve Dai; Mingxing Tan; Kecheng Hao; Zhiru Zhang (DAC, 2014)

Multithreaded pipeline synthesis for data-parallel kernels. - Mingxing Tan; Bin Liu 006; Steve Dai; Zhiru Zhang (ICCAD, 2014)

CASA: correlation-aware speculative adders. - Gai Liu; Ye Tao; Mingxing Tan; Zhiru Zhang (ISLPED, 2014)

Architectural Specialization for Inter-Iteration Loop Dependence Patterns. - Shreesha Srinath; Berkin Ilbeyi; Mingxing Tan; Gai Liu; Zhiru Zhang; Christopher Batten (MICRO, 2014)

Area-efficient pipelining for FPGA-targeted high-level synthesis. - Ritchie Zhao; Mingxing Tan; Steve Dai; Zhiru Zhang (DAC, 2015)

Mapping-Aware Constrained Scheduling for LUT-Based FPGAs. - Mingxing Tan; Steve Dai; Udit Gupta; Zhiru Zhang (FPGA, 2015)

ElasticFlow: A Complexity-Effective Approach for Pipelining Irregular Loop Nests. - Mingxing Tan; Gai Liu; Ritchie Zhao; Steve Dai; Zhiru Zhang (ICCAD, 2015)

An Energy-Efficient Branch Prediction with Grouped Global History. - Mingkai Huang; Dan He; Xianhua Liu 001; Mingxing Tan; Xu Cheng 001 (ICPP, 2015)

Architecture and Synthesis for Area-Efficient Pipelining of Irregular Loop Nests. - Gai Liu; Mingxing Tan; Steve Dai; Ritchie Zhao; Zhiru Zhang (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2017)

MnasNet: Platform-Aware Neural Architecture Search for Mobile. - Mingxing Tan; Bo Chen 019; Ruoming Pang; Vijay Vasudevan; Quoc V. Le (CoRR, 2018)

MixConv: Mixed Depthwise Convolutional Kernels. - Mingxing Tan; Quoc V. Le (BMVC, 2019)

MnasNet: Platform-Aware Neural Architecture Search for Mobile. - Mingxing Tan; Bo Chen 019; Ruoming Pang; Vijay Vasudevan; Mark Sandler 002; Andrew Howard 002; Quoc V. Le (CVPR, 2019)

Searching for MobileNetV3. - Andrew Howard 002; Ruoming Pang; Hartwig Adam; Quoc V. Le; Mark Sandler 002; Bo Chen 019; Weijun Wang; Liang-Chieh Chen; Mingxing Tan; Grace Chu; Vijay Vasudevan; Yukun Zhu (ICCV, 2019)

EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. - Mingxing Tan; Quoc V. Le (ICML, 2019)

Search to Distill: Pearls are Everywhere but not the Eyes. - Yu Liu; Xuhui Jia; Mingxing Tan; Raviteja Vemulapalli; Yukun Zhu; Bradley Green; Xiaogang Wang (CoRR, 2019)

SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization. - Xianzhi Du; Tsung-Yi Lin; Pengchong Jin; Golnaz Ghiasi; Mingxing Tan; Yin Cui; Quoc V. Le; Xiaodan Song (CVPR, 2020)

Search to Distill: Pearls Are Everywhere but Not the Eyes. - Yu Liu 015; Xuhui Jia; Mingxing Tan; Raviteja Vemulapalli; Yukun Zhu; Bradley Green; Xiaogang Wang 001 (CVPR, 2020)

EfficientDet: Scalable and Efficient Object Detection. - Mingxing Tan; Ruoming Pang; Quoc V. Le (CVPR, 2020)

Adversarial Examples Improve Image Recognition. - Cihang Xie; Mingxing Tan; Boqing Gong; Jiang Wang 001; Alan L. Yuille; Quoc V. Le (CVPR, 2020)

Efficient Scale-Permuted Backbone with Learned Resource Distribution. - Xianzhi Du; Tsung-Yi Lin; Pengchong Jin; Yin Cui; Mingxing Tan; Quoc V. Le; Xiaodan Song (ECCV (23), 2020)

BigNAS: Scaling up Neural Architecture Search with Big Single-Stage Models. - Jiahui Yu; Pengchong Jin; Hanxiao Liu; Gabriel Bender; Pieter-Jan Kindermans; Mingxing Tan; Thomas S. Huang; Xiaodan Song; Ruoming Pang; Quoc Le 001 (ECCV (7), 2020)

AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures. - Michael S. Ryoo; A. J. Piergiovanni; Mingxing Tan; Anelia Angelova (ICLR, 2020)

Go Wide, Then Narrow: Efficient Training of Deep Thin Networks. - Denny Zhou; Mao Ye 006; Chen Chen; Tianjian Meng; Mingxing Tan; Xiaodan Song; Quoc V. Le; Qiang Liu 001; Dale Schuurmans (ICML, 2020)

PyGlove: Symbolic Programming for Automated Machine Learning. - Daiyi Peng; Xuanyi Dong; Esteban Real; Mingxing Tan; Yifeng Lu; Gabriel Bender; Hanxiao Liu; Adam Kraft; Chen Liang; Quoc Le 001 (NeurIPS, 2020)

MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. - Yunyang Xiong; Hanxiao Liu; Suyog Gupta; Berkin Akin; Gabriel Bender; Pieter-Jan Kindermans; Mingxing Tan; Vikas Singh; Bo Chen 019 (CoRR, 2020)

When Ensembling Smaller Models is More Efficient than Single Large Models. - Dan Kondratyuk; Mingxing Tan; Matthew Brown 001; Boqing Gong (CoRR, 2020)

AutoHAS: Differentiable Hyper-parameter and Architecture Search. - Xuanyi Dong; Mingxing Tan; Adams Wei Yu; Daiyi Peng; Bogdan Gabrys; Quoc V. Le (CoRR, 2020)

Smooth Adversarial Training. - Cihang Xie; Mingxing Tan; Boqing Gong; Alan L. Yuille; Quoc V. Le (CoRR, 2020)

Nyströmformer: A Nyström-based Algorithm for Approximating Self-Attention. - Yunyang Xiong; Zhanpeng Zeng; Rudrasis Chakraborty; Mingxing Tan; Glenn Fung; Yin Li 003; Vikas Singh (AAAI, 2021)

Searching for Fast Model Families on Datacenter Accelerators. - Sheng Li 007; Mingxing Tan; Ruoming Pang; Andrew Li; Liqun Cheng; Quoc V. Le; Norman P. Jouppi (CVPR, 2021)

Robust and Accurate Object Detection via Adversarial Learning. - Xiangning Chen; Cihang Xie; Mingxing Tan; Li Zhang 003; Cho-Jui Hsieh; Boqing Gong (CVPR, 2021)

MoViNets: Mobile Video Networks for Efficient Video Recognition. - Dan Kondratyuk; Liangzhe Yuan; Yandong Li; Li Zhang 003; Mingxing Tan; Matthew Brown 001; Boqing Gong (CVPR, 2021)

MobileDets: Searching for Object Detection Architectures for Mobile Accelerators. - Yunyang Xiong; Hanxiao Liu; Suyog Gupta; Berkin Akin; Gabriel Bender; Yongzhe Wang; Pieter-Jan Kindermans; Mingxing Tan; Vikas Singh; Bo Chen 019 (CVPR, 2021)

Shape-Texture Debiased Neural Network Training. - Yingwei Li 002; Qihang Yu; Mingxing Tan; Jieru Mei; Peng Tang; Wei Shen 002; Alan L. Yuille; Cihang Xie (ICLR, 2021)

EfficientNetV2: Smaller Models and Faster Training. - Mingxing Tan; Quoc V. Le (ICML, 2021)

Training EfficientNets at Supercomputer Scale: 83% ImageNet Top-1 Accuracy in One Hour. - Arissa Wongpanich; Hieu Pham 001; James Demmel; Mingxing Tan; Quoc V. Le; Yang You 001; Sameer Kumar (IPDPS Workshops, 2021)

CoAtNet: Marrying Convolution and Attention for All Data Sizes. - Zihang Dai; Hanxiao Liu; Quoc V. Le; Mingxing Tan (NeurIPS, 2021)

Rethinking Co-design of Neural Architectures and Hardware Accelerators. - Yanqi Zhou; Xuanyi Dong; Berkin Akin; Mingxing Tan; Daiyi Peng; Tianjian Meng; Amir Yazdanbakhsh; Da Huang; Ravi Narayanaswami; James Laudon (CoRR, 2021)

Combined Scaling for Zero-shot Transfer Learning. - Hieu Pham 001; Zihang Dai; Golnaz Ghiasi; Hanxiao Liu; Adams Wei Yu; Minh-Thang Luong; Mingxing Tan; Quoc V. Le (CoRR, 2021)

DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection. - Yingwei Li 002; Adams Wei Yu; Tianjian Meng; Benjamin Caine; Jiquan Ngiam; Daiyi Peng; Junyang Shen; Yifeng Lu; Denny Zhou; Quoc V. Le; Alan L. Yuille; Mingxing Tan (CVPR, 2022)

PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds. - Zhaoqi Leng; Shuyang Cheng; Benjamin Caine; Weiyue Wang 002; Xiao Zhang; Jonathon Shlens; Mingxing Tan; Dragomir Anguelov (ECCV (31), 2022)

LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds. - Chenxi Liu 001; Zhaoqi Leng; Pei Sun; Shuyang Cheng; Charles R. Qi; Yin Zhou; Mingxing Tan; Dragomir Anguelov (ECCV (21), 2022)

SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds. - Pei Sun; Mingxing Tan; Weiyue Wang 002; Chenxi Liu 001; Fei Xia 005; Zhaoqi Leng; Dragomir Anguelov (ECCV (10), 2022)

PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. - Zhaoqi Leng; Mingxing Tan; Chenxi Liu 001; Ekin Dogus Cubuk; Jay Shi; Shuyang Cheng; Dragomir Anguelov (ICLR, 2022)

Towards the Co-design of Neural Networks and Accelerators. - Yanqi Zhou; Xuanyi Dong; Tianjian Meng; Mingxing Tan; Berkin Akin; Daiyi Peng; Amir Yazdanbakhsh; Da Huang; Ravi Narayanaswami; James Laudon (MLSys, 2022)

DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection. - Yingwei Li 002; Adams Wei Yu; Tianjian Meng; Benjamin Caine; Jiquan Ngiam; Daiyi Peng; Junyang Shen; Bo Wu; Yifeng Lu; Denny Zhou; Quoc V. Le; Alan L. Yuille; et al. (CoRR, 2022)

Revisiting Multi-Scale Feature Fusion for Semantic Segmentation. - Tianjian Meng; Golnaz Ghiasi; Reza Mahjourian; Quoc V. Le; Mingxing Tan (CoRR, 2022)

PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. - Zhaoqi Leng; Mingxing Tan; Chenxi Liu 001; Ekin Dogus Cubuk; Xiaojie Shi; Shuyang Cheng; Dragomir Anguelov (CoRR, 2022)

LidarAugment: Searching for Scalable 3D LiDAR Data Augmentations. - Zhaoqi Leng; Guowang Li; Chenxi Liu 001; Ekin Dogus Cubuk; Pei Sun; Tong He; Dragomir Anguelov; Mingxing Tan (CoRR, 2022)

Occupancy Flow Fields for Motion Forecasting in Autonomous Driving. - Reza Mahjourian; Jinkyu Kim 001; Yuning Chai; Mingxing Tan; Ben Sapp; Dragomir Anguelov (IEEE Robotics Autom. Lett., 2022)

Hyperscale Hardware Optimized Neural Architecture Search. - Sheng Li 007; Garrett Andersen; Tao Chen 003; Liqun Cheng; Julian Grady; Da Huang; Quoc V. Le; Andrew Li; Xin Li 082; Yang Li 005; Chen Liang; Yifeng Lu; et al. (ASPLOS (3), 2023)

Lidar Augment: Searching for Scalable 3D LiDAR Data Augmentations. - Zhaoqi Leng; Guowang Li; Chenxi Liu 001; Ekin Dogus Cubuk; Pei Sun; Tong He; Dragomir Anguelov; Mingxing Tan (ICRA, 2023)

LEF: Late-to-Early Temporal Fusion for LiDAR 3D Object Detection. - Tong He; Pei Sun; Zhaoqi Leng; Chenxi Liu 001; Dragomir Anguelov; Mingxing Tan (IROS, 2023)

Combined scaling for zero-shot transfer learning. - Hieu Pham 001; Zihang Dai; Golnaz Ghiasi; Kenji Kawaguchi; Hanxiao Liu; Adams Wei Yu; Jiahui Yu; Yi-Ting Chen; Minh-Thang Luong; Yonghui Wu; Mingxing Tan; Quoc V. Le (Neurocomputing, 2023)

WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting. - Kan Chen; Runzhou Ge; Hang Qiu 001; Rami Ai-Rfou; Charles R. Qi; Xuanyu Zhou; Zoey Yang; Scott Ettinger; Pei Sun; Zhaoqi Leng; Mustafa Baniodeh; Ivan Bogun; et al. (ICRA, 2024)

STT: Stateful Tracking with Transformers for Autonomous Driving. - Longlong Jing; Ruichi Yu; Xu Chen; Zhengli Zhao; Shiwei Sheng; Colin Graber; Qi Chen; Qinru Li; Shangxuan Wu; Han Deng; Sangjin Lee; Chris Sweeney; et al. (ICRA, 2024)

PVTransformer: Point-to-Voxel Transformer for Scalable 3D Object Detection. - Zhaoqi Leng; Pei Sun; Tong He; Dragomir Anguelov; Mingxing Tan (ICRA, 2024)

SceneDiffuser: Efficient and Controllable Driving Simulation Initialization and Rollout. - Chiyu Max Jiang; Yijing Bai; Andre Cornman; Christopher Davis; Xiukun Huang; Hong Jeon; Sakshum Kulshrestha; John Lambert; Shuangyu Li; Xuanyu Zhou; Carlos Fuertes; Chang Yuan; et al. (NeurIPS, 2024)

STT: Stateful Tracking with Transformers for Autonomous Driving. - Longlong Jing; Ruichi Yu; Xu Chen; Zhengli Zhao; Shiwei Sheng; Colin Graber; Qi Chen; Qinru Li; Shangxuan Wu; Han Deng; Sangjin Lee; Chris Sweeney; et al. (CoRR, 2024)

EMMA: End-to-End Multimodal Model for Autonomous Driving. - Jyh-Jing Hwang; Runsheng Xu; Hubert Lin; Wei-Chih Hung; Jingwei Ji; Kristy Choi; Di Huang; Tong He; Paul Covington; Benjamin Sapp; James Guo; Dragomir Anguelov; et al. (CoRR, 2024)

S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Model with Spatio-Temporal Visual Representation. - Yichen Xie 002; Runsheng Xu; Tong He; Jyh-Jing Hwang; Katie Luo; Jingwei Ji; Hubert Lin; Letian Chen; Yiren Lu 001; Zhaoqi Leng; Dragomir Anguelov; Mingxing Tan (CVPR, 2025)

SceneDiffuser++: City-Scale Traffic Simulation via a Generative World Model. - Shuhan Tan; John Lambert; Hong Jeon; Sakshum Kulshrestha; Yijing Bai; Jing Luo; Dragomir Anguelov; Mingxing Tan; Chiyu Max Jiang (CVPR, 2025)

SceneCrafter: Controllable Multi-View Driving Scene Editing. - Zehao Zhu; Yuliang Zou; Chiyu Max Jiang; Bo Sun; Vincent Casser; Xiukun Huang; Jiahao Wang; Zhenpei Yang; Ruiqi Gao; Leonidas J. Guibas; Mingxing Tan; Dragomir Anguelov (CVPR, 2025)

EMMA: End-to-End Multimodal Model for Autonomous Driving. - Jyh-Jing Hwang; Runsheng Xu; Hubert Lin; Wei-Chih Hung; Jingwei Ji; Kristy Choi; Di Huang; Tong He; Paul Covington; Benjamin Sapp; Yin Zhou; James Guo; et al. (Trans. Mach. Learn. Res., 2025)

S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Modelwith Spatio-Temporal Visual Representation. - Yichen Xie 002; Runsheng Xu; Tong He; Jyh-Jing Hwang; Katie Luo; Jingwei Ji; Hubert Lin; Letian Chen; Yiren Lu 001; Zhaoqi Leng; Dragomir Anguelov; Mingxing Tan (CoRR, 2025)