Benlin Liu

I am a Ph.D. student in Paul G. Allen School of Computer Science & Engineering, University of Washington, working with Ranjay Krishna. I am affiliated with UW Graphics and Imaging Laboratory (GRAIL).

I receive my master degree from Department of Computer Science, UCLA, where I was a research assistant under the supervision of Prof. Cho-jui Hsieh . I also collaborated with Prof. Xiaolong Wang at UCSD . I obtained my BEng. degree from the Department of Electronic Engineering , Tsinghua University , and I worked with Prof. Jiwen Lu of the Department of Automation . During undergraduate, I visited the GRASP Lab at University of Pennsylvania and worked with Prof. Jianbo Shi.

My current research interest is at the intersection of compution vision and machine learning, with a current focus on diffusion, self-supervised learning and large language model. Past research is more about efficient machine learning model and how to learn more generlizable vision model in a data-efficient way.

Email / CV / Google Scholar / Github / Twitter

News

2025-02: One papers got accepted by CVPR 2025!

2025-01: Two papers got accepted by ICLR 2025! One of them is a spotlight presentation!

2024-07: One papers got accepted by ECCV 2024!

2023-07: Two papers got accepted by ICCV 2023!

2023-05: I'll be a student researcher at Google Deepmind this summer!

2022-06: I am greatly honored to be chosen as UW Reality Lab-Meta Fellow!

2021-09: DynamicViT is accepted to NeurIPS 2021.

2021-07: Two papers are accepted to ICCV 2021.

2020-12: One paper on image classification is accepted to AAAI 2021.

2020-07: One paper on knowledge distillation is accepted by ECCV 2020.

Publications

* indicates equal contribution

	Coarse Correspondences Boost Spatial-Temporal Reasoning in Multimodal Language Model Benlin Liu, Yuhao Dong, Yiqin Wang, Zixian Ma, Yansong Tang, Luming Tang, Yongming Rao, Wei-Chiu Ma, Ranjay Krishna Conference on Computer Vision and Pattern Recognition (CVPR), 2025 [Paper][Project Page]
	Interleaved Scene Graph for Interleaved Text-and-Image Generation Assessment (Spotlight) Dongping Chen, Ruoxi Chen, Shu Pu, Zhaoyi Liu, Yanru Wu, Caixi Chen, Benlin Liu, Yue Huang, Yao Wan, Pan Zhou, Ranjay Krishna International Conference on Learning Representations (ICLR), 2025 [Paper][Project Page]
	GMValuator: Similarity-based Data Valuation for Generative Models Jiaxi Yang, Wenlong Deng, Benlin Liu, Yangsibo Huang, James Zou, Xiaoxiao L International Conference on Learning Representations (ICLR), 2025 [Paper]
	Efficient Inference of Vision and Language Instruction-Following Models with Elastic Cache Zuyan Liu, Benlin Liu, Jiahui Wang, Yuhao Dong, Guangyi Chen, Yongming Rao, Ranjay Krishna, Jiwen Lu European Conference on Computer Vision (ECCV), 2024 [Paper]
	TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering Yushi Hu, Benlin Liu, Jungo Kasai, Yizhong Wang, Mari Ostendorf, Ranjay Krishna, Noah A. Smith IEEE/CVF International Conference on Computer Vision (ICCV), 2023 [Paper][Project Page][Code]
	Unleashing Text-to-Image Diffusion Models for Visual Perception Wenliang Zhao, Yongming Rao, Zuyan Liu, Benlin Liu, Jie Zhou, Jiwen Lu IEEE/CVF International Conference on Computer Vision (ICCV)*, 2023 [Paper][Project Page][Code]
	DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, Cho-Jui Hsieh Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), 2021 [Paper][Project Page][Code][Video]
	RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object Detection Benlin Liu, Yongming Rao, Yi Wei, Jiwen Lu, Cho-Jui Hsieh, Jie Zhou IEEE/CVF International Conference on Computer Vision (ICCV), 2021 [Paper]
	Robust Object Detection via Instance-Level Temporal Cycle Confusion Xin Wang, Benlin Liu, Thomas E. Huang, Fisher Yu, Xiaolong Wang, Joseph E. Gonzalez, Trevor Darrell IEEE/CVF International Conference on Computer Vision (ICCV), 2021 [Paper][Project Page]
	Multi-ProxyWasserstein Classifier for Image Classification Benlin Liu, Yongming Rao, Jiwen Lu, Jie Zhou, Cho-Jui Hsieh 35th AAAI Conference on Artificial Intelligence (AAAI), 2021 [Paper]
	MetaDistiller: Network Self-Boosting via Meta-Learned Top-Down Distillation Benlin Liu, Yongming Rao, Jiwen Lu, Jie Zhou, Cho-Jui Hsieh 16th European Conference on Computer Vision (ECCV), 2020 [Paper]

Academic Services

Conference Reviewer: CVPR, ICCV, ECCV, ICLR, NeurIPS, ICML, WACV

Website Template