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Zhuang Liu 0003
Person information
- affiliation: University of California at Berkeley, CA, USA
- affiliation (former): Tsinghua University, Beijing, China
Other persons with the same name
- Zhuang Liu — disambiguation page
- Zhuang Liu 0001
— Dalian University of Technology, School of Computer Science and Technology, China
- Zhuang Liu 0002 — Changchun University of Science and Technology, College of Computer Science and Technology, China (and 1 more)
- Zhuang Liu 0004
- Zhuang Liu 0005 — Union Mobile Financial Technology, China
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2020 – today
- 2024
- [c24]Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie:
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. CVPR 2024: 9568-9578 - [c23]Mingjie Sun, Zhuang Liu, Anna Bair, J. Zico Kolter:
A Simple and Effective Pruning Approach for Large Language Models. ICLR 2024 - [c22]Zhiqiu Xu, Yanjie Chen, Kirill Vishniakov, Yida Yin, Zhiqiang Shen, Trevor Darrell, Lingjie Liu, Zhuang Liu:
Initializing Models with Larger Ones. ICLR 2024 - [c21]Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu:
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy. ICML 2024 - [i31]Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie:
Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. CoRR abs/2401.06209 (2024) - [i30]Xinlei Chen, Zhuang Liu, Saining Xie, Kaiming He:
Deconstructing Denoising Diffusion Models for Self-Supervised Learning. CoRR abs/2401.14404 (2024) - [i29]Kai Wang, Zhaopan Xu, Yukun Zhou, Zelin Zang, Trevor Darrell, Zhuang Liu, Yang You:
Neural Network Diffusion. CoRR abs/2402.13144 (2024) - [i28]Mingjie Sun, Xinlei Chen, J. Zico Kolter, Zhuang Liu:
Massive Activations in Large Language Models. CoRR abs/2402.17762 (2024) - [i27]Zhuang Liu, Kaiming He:
A Decade's Battle on Dataset Bias: Are We There Yet? CoRR abs/2403.08632 (2024) - 2023
- [j4]John Lambert, Zhuang Liu
MSeg: A Composite Dataset for Multi-Domain Semantic Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 796-810 (2023) - [j3]Zhuang Liu
Exploring Simple and Transferable Recognition-Aware Image Processing. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3032-3046 (2023) - [c20]Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, Saining Xie:
ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders. CVPR 2023: 16133-16142 - [c19]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:
RCV2023 Challenges: Benchmarking Model Training and Inference for Resource-Constrained Deep Learning. ICCV (Workshops) 2023: 1526-1535 - [c18]Zhuang Liu, Zhiqiu Xu, Joseph Jin, Zhiqiang Shen, Trevor Darrell:
Dropout Reduces Underfitting. ICML 2023: 22233-22248 - [i26]Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, Saining Xie:
ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders. CoRR abs/2301.00808 (2023) - [i25]Zhuang Liu, Zhiqiu Xu, Joseph Jin, Zhiqiang Shen, Trevor Darrell:
Dropout Reduces Underfitting. CoRR abs/2303.01500 (2023) - [i24]Arnav Chavan, Zhuang Liu, Deepak K. Gupta, Eric P. Xing, Zhiqiang Shen:
One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning. CoRR abs/2306.07967 (2023) - [i23]Mingjie Sun, Zhuang Liu, Anna Bair, J. Zico Kolter:
A Simple and Effective Pruning Approach for Large Language Models. CoRR abs/2306.11695 (2023) - [i22]Yida Yin, Zhiqiu Xu, Zhiyuan Li, Trevor Darrell, Zhuang Liu:
A Coefficient Makes SVRG Effective. CoRR abs/2311.05589 (2023) - [i21]Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu:
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy. CoRR abs/2311.09215 (2023) - [i20]Zhiqiu Xu, Yanjie Chen, Kirill Vishniakov, Yida Yin, Zhiqiang Shen, Trevor Darrell, Lingjie Liu, Zhuang Liu:
Initializing Models with Larger Ones. CoRR abs/2311.18823 (2023) - 2022
- [b1]Zhuang Liu:
Efficient and Scalable Neural Architectures for Visual Recognition. University of California, Berkeley, USA, 2022 - [j2]Gao Huang
Convolutional Networks with Dense Connectivity. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 8704-8716 (2022) - [c17]Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell, Eric Poe Xing:
Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning. AAAI 2022: 2216-2224 - [c16]Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing:
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CVPR 2022: 4921-4931 - [c15]Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie:
A ConvNet for the 2020s. CVPR 2022: 11966-11976 - [c14]Zhuang Liu, Zhiqiu Xu, Hung-Ju Wang, Trevor Darrell, Evan Shelhamer:
Anytime Dense Prediction with Confidence Adaptivity. ICLR 2022 - [i19]Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing:
Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CoRR abs/2201.00814 (2022) - [i18]Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie:
A ConvNet for the 2020s. CoRR abs/2201.03545 (2022) - 2021
- [c13]Yinbo Chen, Zhuang Liu, Huijuan Xu, Trevor Darrell, Xiaolong Wang:
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning. ICCV 2021: 9042-9051 - [c12]Zhuang Liu, Xuanlin Li, Bingyi Kang, Trevor Darrell:
Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control. ICLR 2021 - [c11]Guanhua Wang, Zhuang Liu, Brandon Hsieh, Siyuan Zhuang, Joseph Gonzalez, Trevor Darrell, Ion Stoica:
sensAI: ConvNets Decomposition via Class Parallelism for Fast Inference on Live Data. MLSys 2021 - [i17]Zhuang Liu, Trevor Darrell, Evan Shelhamer:
Confidence Adaptive Anytime Pixel-Level Recognition. CoRR abs/2104.00749 (2021) - [i16]John Lambert, Zhuang Liu, Ozan Sener, James Hays, Vladlen Koltun:
MSeg: A Composite Dataset for Multi-domain Semantic Segmentation. CoRR abs/2112.13762 (2021) - 2020
- [j1]Zhiqiang Shen
Object Detection from Scratch with Deep Supervision. IEEE Trans. Pattern Anal. Mach. Intell. 42(2): 398-412 (2020) - [c10]John Lambert, Zhuang Liu, Ozan Sener, James Hays, Vladlen Koltun:
MSeg: A Composite Dataset for Multi-Domain Semantic Segmentation. CVPR 2020: 2876-2885 - [c9]Tianhong Li, Jianguo Li, Zhuang Liu, Changshui Zhang:
Few Sample Knowledge Distillation for Efficient Network Compression. CVPR 2020: 14627-14635 - [c8]Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei A. Efros, Moritz Hardt:
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts. ICML 2020: 9229-9248 - [i15]Gao Huang, Zhuang Liu, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger:
Convolutional Networks with Dense Connectivity. CoRR abs/2001.02394 (2020) - [i14]Yinbo Chen, Xiaolong Wang, Zhuang Liu, Huijuan Xu, Trevor Darrell:
A New Meta-Baseline for Few-Shot Learning. CoRR abs/2003.04390 (2020) - [i13]Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell:
Rethinking Image Mixture for Unsupervised Visual Representation Learning. CoRR abs/2003.05438 (2020)
2010 – 2019
- 2019
- [c7]Bingyi Kang, Zhuang Liu, Xin Wang, Fisher Yu, Jiashi Feng, Trevor Darrell:
Few-Shot Object Detection via Feature Reweighting. ICCV 2019: 8419-8428 - [c6]Zhuang Liu, Mingjie Sun, Tinghui Zhou, Gao Huang, Trevor Darrell:
Rethinking the Value of Network Pruning. ICLR (Poster) 2019 - [i12]Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei A. Efros, Moritz Hardt:
Test-Time Training for Out-of-Distribution Generalization. CoRR abs/1909.13231 (2019) - [i11]Zhuang Liu, Tinghui Zhou, Zhiqiang Shen, Bingyi Kang, Trevor Darrell:
Transferable Recognition-Aware Image Processing. CoRR abs/1910.09185 (2019) - [i10]Zhuang Liu, Xuanlin Li, Bingyi Kang, Trevor Darrell:
Regularization Matters in Policy Optimization. CoRR abs/1910.09191 (2019) - 2018
- [i9]Zhiqiang Shen, Zhuang Liu, Jianguo Li, Yu-Gang Jiang, Yurong Chen, Xiangyang Xue:
Object Detection from Scratch with Deep Supervision. CoRR abs/1809.09294 (2018) - [i8]Zhuang Liu, Mingjie Sun, Tinghui Zhou, Gao Huang, Trevor Darrell:
Rethinking the Value of Network Pruning. CoRR abs/1810.05270 (2018) - [i7]Tianhong Li, Jianguo Li, Zhuang Liu, Changshui Zhang:
Knowledge Distillation from Few Samples. CoRR abs/1812.01839 (2018) - [i6]Bingyi Kang, Zhuang Liu, Xin Wang, Fisher Yu, Jiashi Feng, Trevor Darrell:
Few-shot Object Detection via Feature Reweighting. CoRR abs/1812.01866 (2018) - 2017
- [c5]Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger:
Densely Connected Convolutional Networks. CVPR 2017: 2261-2269 - [c4]Zhiqiang Shen, Zhuang Liu, Jianguo Li, Yu-Gang Jiang, Yurong Chen
DSOD: Learning Deeply Supervised Object Detectors from Scratch. ICCV 2017: 1937-1945 - [c3]Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, Changshui Zhang:
Learning Efficient Convolutional Networks through Network Slimming. ICCV 2017: 2755-2763 - [c2]Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger:
Snapshot Ensembles: Train 1, Get M for Free. ICLR (Poster) 2017 - [i5]Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger:
Snapshot Ensembles: Train 1, get M for free. CoRR abs/1704.00109 (2017) - [i4]Zhiqiang Shen, Zhuang Liu, Jianguo Li, Yu-Gang Jiang, Yurong Chen, Xiangyang Xue:
DSOD: Learning Deeply Supervised Object Detectors from Scratch. CoRR abs/1708.01241 (2017) - [i3]Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, Changshui Zhang:
Learning Efficient Convolutional Networks through Network Slimming. CoRR abs/1708.06519 (2017) - 2016
- [c1]Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Q. Weinberger:
Deep Networks with Stochastic Depth. ECCV (4) 2016: 646-661 - [i2]Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Q. Weinberger:
Deep Networks with Stochastic Depth. CoRR abs/1603.09382 (2016) - [i1]Gao Huang, Zhuang Liu, Kilian Q. Weinberger:
Densely Connected Convolutional Networks. CoRR abs/1608.06993 (2016)
Coauthor Index
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