Liu, Zhuang

35 publications

ICLR 2025 A Coefficient Makes SVRG Effective Yida Yin, Zhiqiu Xu, Zhiyuan Li, Trevor Darrell, Zhuang Liu

ICLR 2025 A Decade's Battle on Dataset Bias: Are We There yet? Zhuang Liu, Kaiming He

ICLR 2025 Deconstructing Denoising Diffusion Models for Self-Supervised Learning Xinlei Chen, Zhuang Liu, Saining Xie, Kaiming He

ICML 2025 Idiosyncrasies in Large Language Models Mingjie Sun, Yida Yin, Zhiqiu Xu, J Zico Kolter, Zhuang Liu

ICML 2025 LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding Xiaoqian Shen, Yunyang Xiong, Changsheng Zhao, Lemeng Wu, Jun Chen, Chenchen Zhu, Zechun Liu, Fanyi Xiao, Balakrishnan Varadarajan, Florian Bordes, Zhuang Liu, Hu Xu, Hyunwoo J. Kim, Bilge Soran, Raghuraman Krishnamoorthi, Mohamed Elhoseiny, Vikas Chandra

NeurIPS 2025 Meta CLIP 2: A Worldwide Scaling Recipe Yung-Sung Chuang, Yang Li, Dong Wang, Ching-Feng Yeh, Kehan Lyu, Ramya Raghavendra, James R. Glass, Lifei Huang, Jason E Weston, Luke Zettlemoyer, Xinlei Chen, Zhuang Liu, Saining Xie, Wen-tau Yih, Shang-Wen Li, Hu Xu

ICCV 2025 MetaMorph: Multimodal Understanding and Generation via Instruction Tuning Shengbang Tong, David Fan, Jiachen Li, Yunyang Xiong, Xinlei Chen, Koustuv Sinha, Michael Rabbat, Yann LeCun, Saining Xie, Zhuang Liu

ICCV 2025 Scaling Language-Free Visual Representation Learning David Fan, Shengbang Tong, Jiachen Zhu, Koustuv Sinha, Zhuang Liu, Xinlei Chen, Michael Rabbat, Nicolas Ballas, Yann LeCun, Amir Bar, Saining Xie

CVPR 2025 Transformers Without Normalization Jiachen Zhu, Xinlei Chen, Kaiming He, Yann LeCun, Zhuang Liu

ICLR 2024 A Simple and Effective Pruning Approach for Large Language Models Mingjie Sun, Zhuang Liu, Anna Bair, J Zico Kolter

ICML 2024 ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu

CVPR 2024 Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie

ICLR 2024 Initializing Models with Larger Ones Zhiqiu Xu, Yanjie Chen, Kirill Vishniakov, Yida Yin, Zhiqiang Shen, Trevor Darrell, Lingjie Liu, Zhuang Liu

ICLRW 2024 Massive Activations in Large Language Models Mingjie Sun, Xinlei Chen, J Zico Kolter, Zhuang Liu

NeurIPS 2024 Understanding Bias in Large-Scale Visual Datasets Boya Zeng, Yida Yin, Zhuang Liu

ICMLW 2023 A Simple and Effective Pruning Approach for Large Language Models Mingjie Sun, Zhuang Liu, Anna Bair, J Zico Kolter

CVPR 2023 ConvNeXt V2: Co-Designing and Scaling ConvNets with Masked Autoencoders Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, Saining Xie

ICML 2023 Dropout Reduces Underfitting Zhuang Liu, Zhiqiu Xu, Joseph Jin, Zhiqiang Shen, Trevor Darrell

CVPR 2023 ImageBind: One Embedding Space to Bind Them All Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, Mannat Singh, Kalyan Vasudev Alwala, Armand Joulin, Ishan Misra

ICCVW 2023 RCV2023 Challenges: Benchmarking Model Training and Inference for Resource-Constrained Deep Learning Rishabh Tiwari, Arnav Chavan, Deepak K. Gupta, Gowreesh Mago, Animesh Gupta, Akash Gupta, Suraj Sharan, Yukun Yang, Shanwei Zhao, Shihao Wang, Youngjun Kwak, Seonghun Jeong, Yunseung Lee, Changick Kim, Subin Kim, Ganzorig Gankhuyag, Ho Jung, Junwhan Ryu, HaeMoon Kim, Byeong Hak Kim, Tu Vo, Sheir Zaheer, Alexander Holston, Chan Y. Park, Dheemant Dixit, Nahush Lele, Kushagra Bhushan, Debjani Bhowmick, Devanshu Arya, Sadaf Gulshad, Amirhossein Habibian, Amir Ghodrati, Babak Ehteshami Bejnordi, Jai Gupta, Zhuang Liu, Jiahui Yu, Dilip K. Prasad, Zhiqiang Shen

CVPR 2022 A ConvNet for the 2020s Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie

ICLR 2022 Anytime Dense Prediction with Confidence Adaptivity Zhuang Liu, Zhiqiu Xu, Hung-Ju Wang, Trevor Darrell, Evan Shelhamer

AAAI 2022 Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell, Eric Poe Xing

CVPR 2022 Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing

ICCV 2021 Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning Yinbo Chen, Zhuang Liu, Huijuan Xu, Trevor Darrell, Xiaolong Wang

ICLR 2021 Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control Zhuang Liu, Xuanlin Li, Bingyi Kang, Trevor Darrell

IJCAI 2020 FinBERT: A Pre-Trained Financial Language Representation Model for Financial Text Mining Zhuang Liu, Degen Huang, Kaiyu Huang, Zhuang Li, Jun Zhao

ICML 2020 Test-Time Training with Self-Supervision for Generalization Under Distribution Shifts Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei Efros, Moritz Hardt

ICLR 2019 Rethinking the Value of Network Pruning Zhuang Liu, Mingjie Sun, Tinghui Zhou, Gao Huang, Trevor Darrell

ICCVW 2017 Continuous Gesture Recognition with Hand-Oriented Spatiotemporal Feature Zhipeng Liu, Xiujuan Chai, Zhuang Liu, Xilin Chen

ICCV 2017 DSOD: Learning Deeply Supervised Object Detectors from Scratch Zhiqiang Shen, Zhuang Liu, Jianguo Li, Yu-Gang Jiang, Yurong Chen, Xiangyang Xue

CVPR 2017 Densely Connected Convolutional Networks Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger

ICCV 2017 Learning Efficient Convolutional Networks Through Network Slimming Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, Changshui Zhang

ICLR 2017 Snapshot Ensembles: Train 1, Get M for Free Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger

ECCV 2016 Deep Networks with Stochastic Depth Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Q. Weinberger