default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDZhuang Liu 0003
Person information
- affiliation: Princeton University, Princeton, NJ, USA
- affiliation (former): Meta Fundamental AI Research (FAIR), New York City, NY, USA
- affiliation (former, PhD): 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
![[0000-0002-4695-6345]](https://devdomain4test.ir/img/orcid-mark.12x12.png "0000-0002-4695-6345")
— 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 — Beihang University, State Key Laboratory of Software Development Environment, Beijing, China
- Zhuang Liu 0005 — Union Mobile Financial Technology, China
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
showing all ?? records
2020 – today
- 2026
[j5]Sondos Mahmoud Bsharat, Mukul Ranjan, Aidar Myrzakhan, Jiacheng Liu, Bowei Guo, Shengkun Tang, Zhuang Liu, Yuanzhi Li, Zhiqiang Shen:
Mobile-MMLU: A Mobile Intelligence Language Understanding Benchmark. J. Data-centric Mach. Learn. Res. 3: (1):1-48 (2026)- [i56]Shuming Liu, Mingchen Zhuge, Changsheng Zhao, Jun Chen, Lemeng Wu, Zechun Liu, Chenchen Zhu, Zhipeng Cai, Chong Zhou, Haozhe Liu, Ernie Chang, Saksham Suri, Hongyu Xu, Qi Qian, Wei Wen, Balakrishnan Varadarajan, Zhuang Liu, Hu Xu, Florian Bordes, Raghuraman Krishnamoorthi, Bernard Ghanem, Vikas Chandra, Yunyang Xiong:
VideoAuto-R1: Video Auto Reasoning via Thinking Once, Answering Twice. CoRR abs/2601.05175 (2026) - [i55]Bo Li, Yida Yin, Wenhao Chai, Xingyu Fu, Zhuang Liu:
UEval: A Benchmark for Unified Multimodal Generation. CoRR abs/2601.22155 (2026) - [i54]Gabriel Sarch, Linrong Cai, Qunzhong Wang, Haoyang Wu, Danqi Chen, Zhuang Liu:
Vero: An Open RL Recipe for General Visual Reasoning. CoRR abs/2604.04917 (2026) - [i53]Guanyu Zhou, Yida Yin, Wenhao Chai, Shengbang Tong, Xingyu Fu, Zhuang Liu:
VisionFoundry: Teaching VLMs Visual Perception with Synthetic Images. CoRR abs/2604.09531 (2026) - [i52]Taiming Lu, Zhuang Liu:
Strong Teacher Not Needed? On Distillation in LLM Pretraining. CoRR abs/2605.23857 (2026) - [i51]Zhipeng Cai, Zhuang Liu, Yunyang Xiong, Zechun Liu, Vikas Chandra, Yangyang Shi:
VLM3: Vision Language Models Are Native 3D Learners. CoRR abs/2605.30561 (2026) - [i50]Yida Yin, Harish Krishnakumar, Chung Peng Lee, Boya Zeng, Wenhao Chai, Shengbang Tong, Wenhu Chen, Hu Xu, Xingyu Fu, Gabriel Sarch, Aleksandra Korolova, Zhuang Liu:
WorldBench: A Challenging and Visually Diverse Multimodal Reasoning Benchmark. CoRR abs/2606.06538 (2026) - [i49]Boya Zeng, Tianze Luo, Shu Pu, Jucheng Shen, Taiming Lu, Gabriel Sarch, Zhuang Liu:
i1: A Simple and Fully Open Recipe for Strong Text-to-Image Models. CoRR abs/2606.11289 (2026) - [i48]Yufeng Xu, Taiming Lu, Kunjun Li, Jiachen Zhu, Mingjie Sun, Zhuang Liu:
Small LLMs: Pruning vs. Training from Scratch. CoRR abs/2606.14150 (2026) - 2025
- [c35]Jiachen Zhu, Xinlei Chen, Kaiming He, Yann LeCun, Zhuang Liu:
Transformers without Normalization. CVPR 2025: 14901-14911 - [c34]David Fan, Shengbang Tong, Jiachen Zhu, Koustuv Sinha, Zhuang Liu, Xinlei Chen, Michael Rabbat, Nicolas Ballas, Yann LeCun, Amir Bar, Saining Xie:
Scaling Language-Free Visual Representation Learning. ICCV 2025: 1-13 - [c33]Shengbang Tong, David Fan, Jiachen Zhu, Yunyang Xiong, Xinlei Chen, Koustuv Sinha, Michael Rabbat, Yann LeCun, Saining Xie, Zhuang Liu:
MetaMorph: Multimodal Understanding and Generation via Instruction Tuning. ICCV 2025: 17001-17012 - [c32]Zhuang Liu, Kaiming He:
A Decade's Battle on Dataset Bias: Are We There Yet? ICLR 2025 - [c31]Xinlei Chen, Zhuang Liu, Saining Xie, Kaiming He:
Deconstructing Denoising Diffusion Models for Self-Supervised Learning. ICLR 2025 - [c30]Yida Yin, Zhiqiu Xu, Zhiyuan Li, Trevor Darrell, Zhuang Liu:
A Coefficient Makes SVRG Effective. ICLR 2025 - [c29]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:
LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding. ICML 2025 - [c28]Mingjie Sun, Yida Yin, Zhiqiu Xu, J. Zico Kolter, Zhuang Liu:
Idiosyncrasies in Large Language Models. ICML 2025 - [c27]Yung-Sung Chuang, Yang Li, Dong Wang, Ching-Feng Yeh, Kehan Lyu, Ramya Raghavendra, Jim Glass, Lifei Huang, Jason E. Weston, Luke Zettlemoyer, Xinlei Chen, Zhuang Liu, Saining Xie, Scott Yih, Shang-Wen Li, Hu Xu:
Meta CLIP 2: A Worldwide Scaling Recipe. NeurIPS 2025 - [i47]Mingjie Sun, Yida Yin, Zhiqiu Xu, J. Zico Kolter, Zhuang Liu:
Idiosyncrasies in Large Language Models. CoRR abs/2502.12150 (2025) - [i46]Jiachen Zhu, Xinlei Chen, Kaiming He, Yann LeCun, Zhuang Liu:
Transformers without Normalization. CoRR abs/2503.10622 (2025) - [i45]Sondos Mahmoud Bsharat, Mukul Ranjan, Aidar Myrzakhan, Jiacheng Liu, Bowei Guo, Shengkun Tang, Zhuang Liu, Yuanzhi Li, Zhiqiang Shen:
Mobile-MMLU: A Mobile Intelligence Language Understanding Benchmark. CoRR abs/2503.20786 (2025) - [i44]David Fan, Shengbang Tong, Jiachen Zhu, Koustuv Sinha, Zhuang Liu, Xinlei Chen, Michael Rabbat, Nicolas Ballas, Yann LeCun, Amir Bar, Saining Xie:
Scaling Language-Free Visual Representation Learning. CoRR abs/2504.01017 (2025) - [i43]Boya Zeng, Yida Yin, Zhiqiu Xu, Zhuang Liu:
Generative Modeling of Weights: Generalization or Memorization? CoRR abs/2506.07998 (2025) - [i42]Yung-Sung Chuang, Yang Li, Dong Wang, Ching-Feng Yeh, Kehan Lyu, Ramya Raghavendra, James Glass, Lifei Huang, Jason Weston, Luke Zettlemoyer, Xinlei Chen, Zhuang Liu, Saining Xie, Wen-tau Yih, Shang-Wen Li, Hu Xu:
Meta CLIP 2: A Worldwide Scaling Recipe. CoRR abs/2507.22062 (2025) - [i41]Zhipeng Cai, Ching-Feng Yeh, Hu Xu, Zhuang Liu, Gregory P. Meyer, Xinjie Lei, Changsheng Zhao, Shang-Wen (Daniel) Li, Vikas Chandra, Yangyang Shi:
DepthLM: Metric Depth From Vision Language Models. CoRR abs/2509.25413 (2025) - [i40]Shang Zhou, Zihan Zheng, Kaiyuan Liu, Zeyu Shen, Zerui Cheng, Zexing Chen, Hansen He, Jianzhu Yao, Huanzhi Mao, Qiuyang Mang, Tianfu Fu, Beichen Li, Dongruixuan Li, Wenhao Chai, Zhuang Liu, Aleksandra Korolova, Peter Henderson, Natasha Jaques, Pramod Viswanath, Saining Xie, Jingbo Shang:
AutoCode: LLMs as Problem Setters for Competitive Programming. CoRR abs/2510.12803 (2025) - [i39]Mingzhi Chen, Taiming Lu, Jiachen Zhu, Mingjie Sun, Zhuang Liu:
Stronger Normalization-Free Transformers. CoRR abs/2512.10938 (2025) - [i38]Tianze Luo, Haotian Yuan, Zhuang Liu:
SoFlow: Solution Flow Models for One-Step Generative Modeling. CoRR abs/2512.15657 (2025) - [i37]Qiuyang Mang, Wenhao Chai, Zhifei Li, Huanzhi Mao, Shang Zhou, Alexander Du, Hanchen Li, Shu Liu, Edwin Chen, Yichuan Wang, Xieting Chu, Zerui Cheng, Yuan Xu, Tian Xia, Zirui Wang, Tianneng Shi, Jianzhu Yao, Yilong Zhao, Qizheng Zhang, Charlie Ruan, Zeyu Shen, Kaiyuan Liu, Runyuan He, Dong Xing, Zerui Li, Zirong Zeng, Yige Jiang, Lufeng Cheng, Ziyi Zhao, Youran Sun, Wesley Zheng, Meiyuwang Zhang, Ruyi Ji, Xuechang Tu, Zihan Zheng, Zexing Chen, Kangyang Zhou, Zhaozi Wang, Jingbang Chen, Aleksandra Korolova, Peter Henderson, Pramod Viswanath, Vijay Ganesh, Saining Xie, Zhuang Liu, Dawn Song, Sewon Min, Ion Stoica, Joseph E. Gonzalez, Jingbo Shang, Alvin Cheung:
FrontierCS: Evolving Challenges for Evolving Intelligence. CoRR abs/2512.15699 (2025) - [i36]Shu Pu, Boya Zeng, Kaichen Zhou, Mengyu Wang, Zhuang Liu:
Memorization in 3D Shape Generation: An Empirical Study. CoRR abs/2512.23628 (2025) - 2024
- [c26]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 - [c25]Mingjie Sun, Zhuang Liu, Anna Bair, J. Zico Kolter:
A Simple and Effective Pruning Approach for Large Language Models. ICLR 2024 - [c24]Zhiqiu Xu, Yanjie Chen, Kirill Vishniakov, Yida Yin, Zhiqiang Shen, Trevor Darrell, Lingjie Liu, Zhuang Liu:
Initializing Models with Larger Ones. ICLR 2024 - [c23]Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu:
ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy. ICML 2024: 49545-49557 - [c22]Boya Zeng, Yida Yin, Zhuang Liu:
Understanding Bias in Large-Scale Visual Datasets. NeurIPS 2024 - [i35]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) - [i34]Xinlei Chen, Zhuang Liu, Saining Xie, Kaiming He:
Deconstructing Denoising Diffusion Models for Self-Supervised Learning. CoRR abs/2401.14404 (2024) - [i33]Kai Wang, Zhaopan Xu, Yukun Zhou, Zelin Zang, Trevor Darrell, Zhuang Liu, Yang You:
Neural Network Diffusion. CoRR abs/2402.13144 (2024) - [i32]Mingjie Sun, Xinlei Chen, J. Zico Kolter, Zhuang Liu:
Massive Activations in Large Language Models. CoRR abs/2402.17762 (2024) - [i31]Zhuang Liu, Kaiming He:
A Decade's Battle on Dataset Bias: Are We There Yet? CoRR abs/2403.08632 (2024) - [i30]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:
LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding. CoRR abs/2410.17434 (2024) - [i29]Boya Zeng, Yida Yin, Zhuang Liu:
Understanding Bias in Large-Scale Visual Datasets. CoRR abs/2412.01876 (2024) - [i28]Shengbang Tong, David Fan, Jiachen Zhu, Yunyang Xiong, Xinlei Chen, Koustuv Sinha, Michael Rabbat, Yann LeCun, Saining Xie, Zhuang Liu:
MetaMorph: Multimodal Understanding and Generation via Instruction Tuning. CoRR abs/2412.14164 (2024) - 2023
- [j4]John Lambert, Zhuang Liu, Ozan Sener, James Hays, Vladlen Koltun:
MSeg: A Composite Dataset for Multi-Domain Semantic Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 796-810 (2023) - [j3]Zhuang Liu, Hung-Ju Wang, Tinghui Zhou, Zhiqiang Shen, Bingyi Kang, Evan Shelhamer, Trevor Darrell:
Exploring Simple and Transferable Recognition-Aware Image Processing. IEEE Trans. Pattern Anal. Mach. Intell. 45(3): 3032-3046 (2023) - [c21]Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, Mannat Singh, Kalyan Vasudev Alwala, Armand Joulin, Ishan Misra:
ImageBind One Embedding Space to Bind Them All. CVPR 2023: 15180-15190 - [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 C. 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 - [i27]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) - [i26]Zhuang Liu, Zhiqiu Xu, Joseph Jin, Zhiqiang Shen, Trevor Darrell:
Dropout Reduces Underfitting. CoRR abs/2303.01500 (2023) - [i25]Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, Mannat Singh, Kalyan Vasudev Alwala, Armand Joulin, Ishan Misra:
ImageBind: One Embedding Space To Bind Them All. CoRR abs/2305.05665 (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, Zhuang Liu, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger:
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, Zhuang Liu, Jianguo Li, Yu-Gang Jiang, Yurong Chen, Xiangyang Xue:
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, Xiangyang Xue:
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
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2026-08-11 23:21 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated, funded, and maintained by:
Schloss Dagstuhl - Leibniz Center for Informatics is a member of the Leibniz Association and is funded by the federal government of Germany and the states of Germany, especially Saarland and Rhineland‑Palatinate.
