[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


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


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.