News

[12/2023] Preprints and code on model initialization, model behaviors, and SVRG optimizer released. Congrats to David, Kirill, Oscar, and Yanjie!

[11/2023] Happy to speak and join the panel at the CMU PhD Career Workshop at Pittsburgh



Recent and selected publications (* equal contribution)

A Decade's Battle on Dataset Bias: Are We There Yet?

Zhuang Liu, Kaiming He

arXiv 2024

[Paper] [Code]

Massive Activations in Large Language Models

Mingjie Sun, Xinlei Chen, J. Zico Kolter, Zhuang Liu

arXiv 2024

[Paper] [Code]

Neural Network Diffusion

Kai Wang, Zhaopan Xu, Yukun Zhou, Zelin Zang, Trevor Darrell, Zhuang Liu*, Yang You*

arXiv 2024

[Paper] [Code]

Deconstructing Denoising Diffusion Models for Self-Supervised Learning

Xinlei Chen, Zhuang Liu, Saining Xie, Kaiming He

arXiv 2024

[Paper]

Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs

Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie

CVPR 2024

[Paper] [Code]

Initializing Models with Larger Ones

Zhiqiu Xu, Yanjie Chen, Kirill Vishniakov, Yida Yin, Zhiqiang Shen, Trevor Darrell, Lingjie Liu, Zhuang Liu

ICLR 2024

[Paper] [Code]

Spotlight Presentation

ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy

Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu

arXiv 2023

[Paper] [Code]

A Coefficient Makes SVRG Effective

Yida Yin, Zhiqiu Xu, Zhiyuan Li, Trevor Darrell, Zhuang Liu

arXiv 2023

[Paper] [Code]

A Simple and Effective Pruning Approach for Large Language Models

Mingjie Sun*, Zhuang Liu*, Anna Bair, Zico Kolter

ICLR 2024

[Paper] [Code]

Dropout Reduces Underfitting

Zhuang Liu*, Zhiqiu Xu*, Joseph Jin, Zhiqiang Shen, Trevor Darrell

ICML 2023

[Paper] [Code]

ImageBind: One Embedding Space To Bind Them All

Rohit Girdhar*, Alaaeldin El-Nouby*, Zhuang Liu, Mannat Singh, Kalyan Vasudev Alwala, Armand Joulin, Ishan Misra*

CVPR 2023

[Paper] [Code] [Blog] [Demo]

Highlighted Paper

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

CVPR 2023

[Paper] [Code]

A ConvNet for the 2020s

Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie

CVPR 2022

[Paper] [Video] [Code]

Rethinking the Value of Network Pruning

Zhuang Liu*, Mingjie Sun*, Tinghui Zhou, Gao Huang, Trevor Darrell

ICLR 2019

[Paper] [OpenReview] [Code]

NeurIPS'18 Compact Neural Networks Workshop Best Paper Award

Learning Efficient Convolutional Networks through Network Slimming

Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, Changshui Zhang

ICCV 2017

[Paper] [Code1] [Code2] [Code3 (3rd-party)]

Densely Connected Convolutional Networks

Gao Huang*, Zhuang Liu*, Laurens van der Maaten, Kilian Weinberger

CVPR 2017

[Paper] [Code]

CVPR Best Paper Award



Previous Publications (* equal contribution)

Exploring Simple and Transferable Recognition-Aware Image Processing

Zhuang Liu, Hungju Wang, Tinghui Zhou, Zhiqiang Shen, Bingyi Kang, Evan Shelhamer, Trevor Darrell

TPAMI 2022

[Paper] [Code]

Anytime Dense Prediction with Confidence Adaptivity

Zhuang Liu, Hung-Ju Wang, Zhiqiu Xu, Trevor Darrell, Evan Shelhamer

ICLR 2022

[Paper] [Code] [OpenReview]

Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space

Arnav Chavan*, Zhiqiang Shen*, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric Xing

CVPR 2022

[Paper] [Code]

Un-Mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning

Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell

AAAI 2022

[Paper] [Code]

Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning

Yinbo Chen, Zhuang Liu, Huijuan Xu, Trevor Darrell, Xiaolong Wang

ICCV 2021

[Paper] [Code]

SensAI: Fast ConvNets Serving on Live Data via Class Parallelism

Guanhua Wang, Zhuang Liu, Siyuan Zhuang, Brandon Hsieh, Joseph E. Gonzalez, Trevor Darrell, Ion Stoica

Machine Learning and Systems 2021

[Paper] [Code]

Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control

Zhuang Liu*, Xuanlin Li*, Bingyi Kang, Trevor Darrell

ICLR 2021

[Paper] [Code] [OpenReview] [Video]

Spotlight Presentation

Test-Time Training for Out-of-Distribution Generalization

Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei A. Efros, Moritz Hardt

ICML 2020

[Paper] [Code] [Video]

MSeg: A Composite Dataset for Multi-domain Semantic Segmentation

John Lambert*, Zhuang Liu*, Ozan Sener, James Hays, Vladlen Koltun

CVPR 2020

[Paper] [Code] [Demo]

Few Sample Knowledge Distillation for Efficient Network Compression

Tianhong Li, Jianguo Li, Zhuang Liu, Changshui Zhang

CVPR 2020

[Paper] [Code]

Few-shot Object Detection via Feature Reweighting

Bingyi Kang*, Zhuang Liu*, Xin Wang, Fisher Yu, Jiashi Feng, Trevor Darrell

ICCV 2019

[Paper] [Code]

DSOD: Learning Deeply Supervised Object Detectors from Scratch

Zhiqiang Shen*, Zhuang Liu*, Jianguo Li, Yu-Gang Jiang, Yurong Chen, Xiangyang Xue

ICCV 2017

[Paper] [Code]

Deep Networks with Stochastic Depth

Gao Huang*, Yu Sun*, Zhuang Liu, Daniel Sedra, Kilian Weinberger

ECCV 2016

[Paper] [Code]

Spotlight Presentation

Misc

I served as an Area Chair for NeurIPS 2023 and ICCV 2023.

I also regularly serve as a reviewer for CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR.

Fun fact 1: I served as a NeurIPS Area Chair before publishing my first NeurIPS paper. (I tried many times, but I still haven't)

Fun fact 2: Once upon a time, I scored the highest in China's National College Entrance Exam in Sciences among 300,000 students.