Xiaoliang Dai

According to our database, Xiaoliang Dai authored at least 53 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

DePNR: A DeBERTa-based deep learning model with complete position embedding for place name recognition from geographical literature.

Weirong Li, Kai Sun, Shu Wang, Yunqiang Zhu, Xiaoliang Dai, Lei Hu

Trans. GIS, August, 2024

An Investigation on Hardware-Aware Vision Transformer Scaling.

Chaojian Li, Kyungmin Kim, Bichen Wu, Peizhao Zhang, Hang Zhang, Xiaoliang Dai, Peter Vajda, Yingyan (Celine) Lin

ACM Trans. Embed. Comput. Syst., May, 2024

GeoTPE: A neural network model for geographical topic phrases extraction from literature based on BERT enhanced with relative position embedding.

Weirong Li, Kai Sun, Yunqiang Zhu, Fangyu Ding, Lei Hu, Xiaoliang Dai, Jia Song, Jie Yang, Lang Qian, Shu Wang

Expert Syst. Appl., January, 2024

Deep learning prediction of rainfall-driven debris flows considering the similar critical thresholds within comparable background conditions.

Hu Jiang, Qiang Zou, Yunqiang Zhu, Yong Li, Bin Zhou, Wentao Zhou, Shunyu Yao, Xiaoliang Dai, Hongkun Yao, Siyu Chen

Environ. Model. Softw., 2024

Movie Gen: A Cast of Media Foundation Models.

Adam Polyak, Amit Zohar, Andrew Brown, Andros Tjandra, Animesh Sinha, Ann Lee, Apoorv Vyas, Bowen Shi, Chih-Yao Ma, Ching-Yao Chuang, David Yan, Dhruv Choudhary, Dingkang Wang, Geet Sethi, Guan Pang, Haoyu Ma, Ishan Misra, Ji Hou, Jialiang Wang, Kiran Jagadeesh, Kunpeng Li, Luxin Zhang, Mannat Singh, Mary Williamson, Matt Le, Matthew Yu, Mitesh Kumar Singh, Peizhao Zhang, Peter Vajda, Quentin Duval, Rohit Girdhar, Roshan Sumbaly, Sai Saketh Rambhatla, Sam S. Tsai, Samaneh Azadi, Samyak Datta, Sanyuan Chen, Sean Bell, Sharadh Ramaswamy, Shelly Sheynin, Siddharth Bhattacharya, Simran Motwani, Tao Xu, Tianhe Li, Tingbo Hou, Wei-Ning Hsu, Xi Yin, Xiaoliang Dai, Yaniv Taigman, Yaqiao Luo, Yen-Cheng Liu, Yi-Chiao Wu, Yue Zhao, Yuval Kirstain, Zecheng He, Zijian He, Albert Pumarola, Ali K. Thabet, Artsiom Sanakoyeu, Arun Mallya, Baishan Guo, Boris Araya, Breena Kerr, Carleigh Wood, Ce Liu, Cen Peng, Dmitry Vengertsev, Edgar Schönfeld, Elliot Blanchard, Felix Juefei-Xu, Fraylie Nord, Jeff Liang, John Hoffman, Jonas Kohler, Kaolin Fire, Karthik Sivakumar, Lawrence Chen, Licheng Yu, Luya Gao, Markos Georgopoulos, Rashel Moritz, Sara K. Sampson, Shikai Li, Simone Parmeggiani, Steve Fine, Tara Fowler, Vladan Petrovic, Yuming Du

CoRR, 2024

An Analysis on Quantizing Diffusion Transformers.

Yuewei Yang, Jialiang Wang, Xiaoliang Dai, Peizhao Zhang, Hongbo Zhang

CoRR, 2024

SceneTextGen: Layout-Agnostic Scene Text Image Synthesis with Diffusion Models.

Qilong Zhangli, Jindong Jiang, Di Liu, Licheng Yu, Xiaoliang Dai, Ankit Ramchandani, Guan Pang, Dimitris N. Metaxas, Praveen Krishnan

CoRR, 2024

LEGO: Learning EGOcentric Action Frame Generation via Visual Instruction Tuning.

Bolin Lai, Xiaoliang Dai, Lawrence Chen, Guan Pang, James M. Rehg, Miao Liu

Proceedings of the Computer Vision - ECCV 2024, 2024

Layout-Agnostic Scene Text Image Synthesis with Diffusion Models.

Qilong Zhangli, Jindong Jiang, Di Liu, Licheng Yu, Xiaoliang Dai, Ankit Ramchandani, Guan Pang, Dimitris N. Metaxas, Praveen Krishnan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything.

Yunyang Xiong, Bala Varadarajan, Lemeng Wu, Xiaoyu Xiang, Fanyi Xiao, Chenchen Zhu, Xiaoliang Dai, Dilin Wang, Fei Sun, Forrest N. Iandola, Raghuraman Krishnamoorthi, Vikas Chandra

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Cache Me if You Can: Accelerating Diffusion Models through Block Caching.

Felix Wimbauer, Bichen Wu, Edgar Schönfeld, Xiaoliang Dai, Ji Hou, Zijian He, Artsiom Sanakoyeu, Peizhao Zhang, Sam S. Tsai, Jonas Kohler, Christian Rupprecht, Daniel Cremers, Peter Vajda, Jialiang Wang

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Examining the Spatially Varying Relationships between Landslide Susceptibility and Conditioning Factors Using a Geographical Random Forest Approach: A Case Study in Liangshan, China.

Xiaoliang Dai, Yunqiang Zhu, Kai Sun, Qiang Zou, Shen Zhao, Weirong Li, Lei Hu, Shu Wang

Remote. Sens., March, 2023

Efficient Quantization Strategies for Latent Diffusion Models.

Yuewei Yang, Xiaoliang Dai, Jialiang Wang, Peizhao Zhang, Hongbo Zhang

CoRR, 2023

Emu: Enhancing Image Generation Models Using Photogenic Needles in a Haystack.

Xiaoliang Dai, Ji Hou, Chih-Yao Ma, Sam S. Tsai, Jialiang Wang, Rui Wang, Peizhao Zhang, Simon Vandenhende, Xiaofang Wang, Abhimanyu Dubey, Matthew Yu, Abhishek Kadian, Filip Radenovic, Dhruv Mahajan, Kunpeng Li, Yue Zhao, Vladan Petrovic, Mitesh Kumar Singh, Simran Motwani, Yi Wen, Yiwen Song, Roshan Sumbaly, Vignesh Ramanathan, Zijian He, Peter Vajda, Devi Parikh

CoRR, 2023

Unveiling Optimal SDG Pathways: An Innovative Approach Leveraging Graph Pruning and Intent Graph for Effective Recommendations.

Zhihang Yu, Shu Wang, Yunqiang Zhu, Wen Yuan, Xiaoliang Dai, Zhiqiang Zou

CoRR, 2023

Mask3D: Pre-training 2D Vision Transformers by Learning Masked 3D Priors.

Ji Hou, Xiaoliang Dai, Zijian He, Angela Dai, Matthias Nießner

CoRR, 2023

Pruning Compact ConvNets for Efficient Inference.

Sayan Ghosh, Karthik Prasad, Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Graham Cormode, Peter Vajda

CoRR, 2023

NASRec: Weight Sharing Neural Architecture Search for Recommender Systems.

Tunhou Zhang, Dehua Cheng, Yuchen He, Zhengxing Chen, Xiaoliang Dai, Liang Xiong, Feng Yan, Hai Li, Yiran Chen, Wei Wen

Proceedings of the ACM Web Conference 2023, 2023

Token Merging: Your ViT But Faster.

Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai, Peizhao Zhang, Christoph Feichtenhofer, Judy Hoffman

Proceedings of the Eleventh International Conference on Learning Representations, 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, Peter Vajda, Yingyan Celine Lin

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Trainable Projected Gradient Method for Robust Fine-Tuning.

Junjiao Tian, Xiaoliang Dai, Chih-Yao Ma, Zecheng He, Yen-Cheng Liu, Zsolt Kira

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Open-Vocabulary Semantic Segmentation with Mask-adapted CLIP.

Feng Liang, Bichen Wu, Xiaoliang Dai, Kunpeng Li, Yinan Zhao, Hang Zhang, Peizhao Zhang, Peter Vajda, Diana Marculescu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Mask3D: Pretraining 2D Vision Transformers by Learning Masked 3D Priors.

Ji Hou, Xiaoliang Dai, Zijian He, Angela Dai, Matthias Nießner

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

Fully Dynamic Inference With Deep Neural Networks.

Wenhan Xia, Hongxu Yin, Xiaoliang Dai, Niraj K. Jha

IEEE Trans. Emerg. Top. Comput., 2022

Incremental Learning Using a Grow-and-Prune Paradigm With Efficient Neural Networks.

Xiaoliang Dai, Hongxu Yin, Niraj K. Jha

IEEE Trans. Emerg. Top. Comput., 2022

CURIOUS: Efficient Neural Architecture Search Based on a Performance Predictor and Evolutionary Search.

Shayan Hassantabar, Xiaoliang Dai, Niraj K. Jha

IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 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, Peter Vajda, Yingyan Lin

CoRR, 2022

3D-Aware Encoding for Style-based Neural Radiance Fields.

Yu-Jhe Li, Tao Xu, Bichen Wu, Ningyuan Zheng, Xiaoliang Dai, Albert Pumarola, Peizhao Zhang, Peter Vajda, Kris Kitani

CoRR, 2022

Open-Set Semi-Supervised Object Detection.

Yen-Cheng Liu, Chih-Yao Ma, Xiaoliang Dai, Junjiao Tian, Peter Vajda, Zijian He, Zsolt Kira

Proceedings of the Computer Vision - ECCV 2022, 2022

Hydra Attention: Efficient Attention with Many Heads.

Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai, Peizhao Zhang, Judy Hoffman

Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022

Cross-Domain Adaptive Teacher for Object Detection.

Yu-Jhe Li, Xiaoliang Dai, Chih-Yao Ma, Yen-Cheng Liu, Kan Chen, Bichen Wu, Zijian He, Kris Kitani, Peter Vajda

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

YSUY: Your Smartphone Understands You - Using Machine Learning to Address Fundamental Human Needs.

Ayten Ozge Akmandor, Xiaoliang Dai, Niraj K. Jha

IEEE Trans. Syst. Man Cybern. Syst., 2021

DiabDeep: Pervasive Diabetes Diagnosis Based on Wearable Medical Sensors and Efficient Neural Networks.

Hongxu Yin, Bilal Mukadam, Xiaoliang Dai, Niraj K. Jha

IEEE Trans. Emerg. Top. Comput., 2021

Cross-Domain Object Detection via Adaptive Self-Training.

Yu-Jhe Li, Xiaoliang Dai, Chih-Yao Ma, Yen-Cheng Liu, Kan Chen, Bichen Wu, Zijian He, Kris Kitani, Peter Vajda

CoRR, 2021

FBNetV5: Neural Architecture Search for Multiple Tasks in One Run.

Bichen Wu, Chaojian Li, Hang Zhang, Xiaoliang Dai, Peizhao Zhang, Matthew Yu, Jialiang Wang, Yingyan Lin, Peter Vajda

CoRR, 2021

Visual Transformers: Where Do Transformers Really Belong in Vision Models?

Bichen Wu, Chenfeng Xu, Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Zhicheng Yan, Masayoshi Tomizuka, Joseph Gonzalez, Kurt Keutzer, Peter Vajda

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

FP-NAS: Fast Probabilistic Neural Architecture Search.

Zhicheng Yan, Xiaoliang Dai, Peizhao Zhang, Yuandong Tian, Bichen Wu, Matt Feiszli

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Rethinking the Self-Attention in Vision Transformers.

Kyungmin Kim, Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Zhicheng Yan, Peter Vajda, Seon Joo Kim

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

FBNetV3: Joint Architecture-Recipe Search Using Predictor Pretraining.

Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Grow and Prune Compact, Fast, and Accurate LSTMs.

Xiaoliang Dai, Hongxu Yin, Niraj K. Jha

IEEE Trans. Computers, 2020

Visual Transformers: Token-based Image Representation and Processing for Computer Vision.

Bichen Wu, Chenfeng Xu, Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Masayoshi Tomizuka, Kurt Keutzer, Peter Vajda

CoRR, 2020

FBNetV3: Joint Architecture-Recipe Search using Neural Acquisition Function.

Xiaoliang Dai, Alvin Wan, Peizhao Zhang, Bichen Wu, Zijian He, Zhen Wei, Kan Chen, Yuandong Tian, Matthew Yu, Peter Vajda, Joseph E. Gonzalez

CoRR, 2020

FBNetV2: Differentiable Neural Architecture Search for Spatial and Channel Dimensions.

Alvin Wan, Xiaoliang Dai, Peizhao Zhang, Zijian He, Yuandong Tian, Saining Xie, Bichen Wu, Matthew Yu, Tao Xu, Kan Chen, Peter Vajda, Joseph E. Gonzalez

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Synthesis of Efficient Neural Networks

Xiaoliang Dai

PhD thesis, 2019

NeST: A Neural Network Synthesis Tool Based on a Grow-and-Prune Paradigm.

Xiaoliang Dai, Hongxu Yin, Niraj K. Jha

IEEE Trans. Computers, 2019

STEERAGE: Synthesis of Neural Networks Using Architecture Search and Grow-and-Prune Methods.

Shayan Hassantabar, Xiaoliang Dai, Niraj K. Jha

CoRR, 2019

FBNet: Hardware-Aware Efficient ConvNet Design via Differentiable Neural Architecture Search.

Bichen Wu, Xiaoliang Dai, Peizhao Zhang, Yanghan Wang, Fei Sun, Yiming Wu, Yuandong Tian, Peter Vajda, Yangqing Jia, Kurt Keutzer

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

ChamNet: Towards Efficient Network Design Through Platform-Aware Model Adaptation.

Xiaoliang Dai, Peizhao Zhang, Bichen Wu, Hongxu Yin, Fei Sun, Yanghan Wang, Marat Dukhan, Yunqing Hu, Yiming Wu, Yangqing Jia, Peter Vajda, Matt Uyttendaele, Niraj K. Jha

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

PinMe: Tracking a Smartphone User around the World.

Arsalan Mosenia, Xiaoliang Dai, Prateek Mittal, Niraj K. Jha

IEEE Trans. Multi Scale Comput. Syst., 2018

2017

Using a Device State Library to Boost the Performance of TCAD Mixed-Mode Simulation.

Xiaoliang Dai, Niraj K. Jha

IEEE Trans. Very Large Scale Integr. Syst., 2017

Improving Convergence and Simulation Time of Quantum Hydrodynamic Simulation: Application to Extraction of Best 10-nm FinFET Parameter Values.

Xiaoliang Dai, Niraj K. Jha

IEEE Trans. Very Large Scale Integr. Syst., 2017

2008

The Common Problems on the Peer-to-Peer Multicast Overlay Networks.

Feng Yang, Xiaoliang Dai, Ruzhi Xu

Proceedings of the International Conference on Computer Science and Software Engineering, 2008