Mingxing Tan
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
46
Venues
18
Active years
2010–2025
Best venue rank
A*
Where they publish
Papers
46 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | CVPR | S4-Driver: Scalable Self-Supervised Driving Multimodal Large Language Model with Spatio-Temporal Visual Representation. | Yichen Xie, Runsheng Xu, Tong He, Jyh-Jing Hwang, Katie Luo, Jingwei Ji, Hubert Lin, Letian Chen, Yiren Lu, Zhaoqi Leng, Dragomir Anguelov, Mingxing Tan |
| 2025 | CVPR | 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 |
| 2025 | CVPR | 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 |
| 2025 | IROS | Enhanced Motion Forecasting with Plug-and-Play Multimodal Large Language Models. | Katie Luo, Jingwei Ji, Tong He, Runsheng Xu, Yichen Xie, Dragomir Anguelov, Mingxing Tan |
| 2025 | IROS | Drive&Gen: Co-Evaluating End-to-End Driving and Video Generation Models. | Jiahao Wang, Zhenpei Yang, Yijing Bai, Yingwei Li, Yuliang Zou, Bo Sun, Abhijit Kundu, Jos Lezama, Luna Yue Huang, Zehao Zhu, Jyh-Jing Hwang, Dragomir Anguelov, Mingxing Tan, Chiyu Max Jiang |
| 2024 | ICRA | WOMD-LiDAR: Raw Sensor Dataset Benchmark for Motion Forecasting. | Kan Chen, Runzhou Ge, Hang Qiu, Rami Ai-Rfou, Charles R. Qi, Xuanyu Zhou, Zoey Yang, Scott Ettinger, Pei Sun, Zhaoqi Leng, Mustafa Baniodeh, Ivan Bogun, Weiyue Wang, Mingxing Tan, Dragomir Anguelov |
| 2024 | ICRA | 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, Qiurui He, Wei-Chih Hung, Tong He, Xingyi Zhou, Farshid Moussavi, James Guo, Yin Zhou, Mingxing Tan, Weilong Yang, Congcong Li |
| 2024 | ICRA | PVTransformer: Point-to-Voxel Transformer for Scalable 3D Object Detection. | Zhaoqi Leng, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan |
| 2023 | ASPLOS | Hyperscale Hardware Optimized Neural Architecture Search. | Sheng Li, Garrett Andersen, Tao Chen, Liqun Cheng, Julian Grady, Da Huang, Quoc V. Le, Andrew Li, Xin Li, Yang Li, Chen Liang, Yifeng Lu, Yun Ni, Ruoming Pang, Mingxing Tan, Martin Wicke, Gang Wu, Shengqi Zhu, Parthasarathy Ranganathan, Norman P. Jouppi |
| 2023 | ICRA | Lidar Augment: Searching for Scalable 3D LiDAR Data Augmentations. | Zhaoqi Leng, Guowang Li, Chenxi Liu, Ekin Dogus Cubuk, Pei Sun, Tong He, Dragomir Anguelov, Mingxing Tan |
| 2023 | IROS | LEF: Late-to-Early Temporal Fusion for LiDAR 3D Object Detection. | Tong He, Pei Sun, Zhaoqi Leng, Chenxi Liu, Dragomir Anguelov, Mingxing Tan |
| 2022 | CVPR | DeepFusion: Lidar-Camera Deep Fusion for Multi-Modal 3D Object Detection. | Yingwei Li, 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 |
| 2022 | ECCV | PseudoAugment: Learning to Use Unlabeled Data for Data Augmentation in Point Clouds. | Zhaoqi Leng, Shuyang Cheng, Benjamin Caine, Weiyue Wang, Xiao Zhang, Jonathon Shlens, Mingxing Tan, Dragomir Anguelov |
| 2022 | ECCV | LidarNAS: Unifying and Searching Neural Architectures for 3D Point Clouds. | Chenxi Liu, Zhaoqi Leng, Pei Sun, Shuyang Cheng, Charles R. Qi, Yin Zhou, Mingxing Tan, Dragomir Anguelov |
| 2022 | ECCV | SWFormer: Sparse Window Transformer for 3D Object Detection in Point Clouds. | Pei Sun, Mingxing Tan, Weiyue Wang, Chenxi Liu, Fei Xia, Zhaoqi Leng, Dragomir Anguelov |
| 2022 | ICLR | PolyLoss: A Polynomial Expansion Perspective of Classification Loss Functions. | Zhaoqi Leng, Mingxing Tan, Chenxi Liu, Ekin Dogus Cubuk, Jay Shi, Shuyang Cheng, Dragomir Anguelov |
| 2021 | AAAI | Nystrmformer: A Nystrm-based Algorithm for Approximating Self-Attention. | Yunyang Xiong, Zhanpeng Zeng, Rudrasis Chakraborty, Mingxing Tan, Glenn Fung, Yin Li, Vikas Singh |
| 2021 | CVPR | Searching for Fast Model Families on Datacenter Accelerators. | Sheng Li, Mingxing Tan, Ruoming Pang, Andrew Li, Liqun Cheng, Quoc V. Le, Norman P. Jouppi |
| 2021 | CVPR | Robust and Accurate Object Detection via Adversarial Learning. | Xiangning Chen, Cihang Xie, Mingxing Tan, Li Zhang, Cho-Jui Hsieh, Boqing Gong |
| 2021 | CVPR | MoViNets: Mobile Video Networks for Efficient Video Recognition. | Dan Kondratyuk, Liangzhe Yuan, Yandong Li, Li Zhang, Mingxing Tan, Matthew Brown, Boqing Gong |
| 2021 | CVPR | 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 |
| 2021 | ICLR | Shape-Texture Debiased Neural Network Training. | Yingwei Li, Qihang Yu, Mingxing Tan, Jieru Mei, Peng Tang, Wei Shen, Alan L. Yuille, Cihang Xie |
| 2021 | ICML | EfficientNetV2: Smaller Models and Faster Training. | Mingxing Tan, Quoc V. Le |
| 2020 | CVPR | 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 |
| 2020 | CVPR | Search to Distill: Pearls Are Everywhere but Not the Eyes. | Yu Liu, Xuhui Jia, Mingxing Tan, Raviteja Vemulapalli, Yukun Zhu, Bradley Green, Xiaogang Wang |
| 2020 | CVPR | EfficientDet: Scalable and Efficient Object Detection. | Mingxing Tan, Ruoming Pang, Quoc V. Le |
| 2020 | CVPR | Adversarial Examples Improve Image Recognition. | Cihang Xie, Mingxing Tan, Boqing Gong, Jiang Wang, Alan L. Yuille, Quoc V. Le |
| 2020 | ECCV | Efficient Scale-Permuted Backbone with Learned Resource Distribution. | Xianzhi Du, Tsung-Yi Lin, Pengchong Jin, Yin Cui, Mingxing Tan, Quoc V. Le, Xiaodan Song |
| 2020 | ECCV | 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 |
| 2020 | ICLR | AssembleNet: Searching for Multi-Stream Neural Connectivity in Video Architectures. | Michael S. Ryoo, A. J. Piergiovanni, Mingxing Tan, Anelia Angelova |
| 2020 | ICML | Go Wide, Then Narrow: Efficient Training of Deep Thin Networks. | Denny Zhou, Mao Ye, Chen Chen, Tianjian Meng, Mingxing Tan, Xiaodan Song, Quoc V. Le, Qiang Liu, Dale Schuurmans |
| 2019 | BMVC | MixConv: Mixed Depthwise Convolutional Kernels. | Mingxing Tan, Quoc V. Le |
| 2019 | CVPR | MnasNet: Platform-Aware Neural Architecture Search for Mobile. | Mingxing Tan, Bo Chen, Ruoming Pang, Vijay Vasudevan, Mark Sandler, Andrew Howard, Quoc V. Le |
| 2019 | ICCV | Searching for MobileNetV3. | Andrew Howard, Ruoming Pang, Hartwig Adam, Quoc V. Le, Mark Sandler, Bo Chen, Weijun Wang, Liang-Chieh Chen, Mingxing Tan, Grace Chu, Vijay Vasudevan, Yukun Zhu |
| 2019 | ICML | EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks. | Mingxing Tan, Quoc V. Le |
| 2015 | DAC | Area-efficient pipelining for FPGA-targeted high-level synthesis. | Ritchie Zhao, Mingxing Tan, Steve Dai, Zhiru Zhang |
| 2015 | FPGA | Mapping-Aware Constrained Scheduling for LUT-Based FPGAs. | Mingxing Tan, Steve Dai, Udit Gupta, Zhiru Zhang |
| 2015 | ICCAD | ElasticFlow: A Complexity-Effective Approach for Pipelining Irregular Loop Nests. | Mingxing Tan, Gai Liu, Ritchie Zhao, Steve Dai, Zhiru Zhang |
| 2015 | ICPP | An Energy-Efficient Branch Prediction with Grouped Global History. | Mingkai Huang, Dan He, Xianhua Liu, Mingxing Tan, Xu Cheng |
| 2014 | DAC | Flushing-Enabled Loop Pipelining for High-Level Synthesis. | Steve Dai, Mingxing Tan, Kecheng Hao, Zhiru Zhang |
| 2014 | ICCAD | Multithreaded pipeline synthesis for data-parallel kernels. | Mingxing Tan, Bin Liu, Steve Dai, Zhiru Zhang |
| 2014 | ISLPED | CASA: correlation-aware speculative adders. | Gai Liu, Ye Tao, Mingxing Tan, Zhiru Zhang |
| 2014 | MICRO | Architectural Specialization for Inter-Iteration Loop Dependence Patterns. | Shreesha Srinath, Berkin Ilbeyi, Mingxing Tan, Gai Liu, Zhiru Zhang, Christopher Batten |
| 2012 | DATE | Energy-efficient branch prediction with Compiler-guided History Stack. | Mingxing Tan, Xianhua Liu, Zichao Xie, Dong Tong, Xu Cheng |
| 2012 | ICS | CVP: an energy-efficient indirect branch prediction with compiler-guided value pattern. | Mingxing Tan, Xianhua Liu, Tong Tong, Xu Cheng |
| 2010 | FPGA | Bit-level optimization for high-level synthesis and FPGA-based acceleration. | Jiyu Zhang, Zhiru Zhang, Sheng Zhou, Mingxing Tan, Xianhua Liu, Xu Cheng, Jason Cong |