Zhuang Liu - RankMe

87 papers A* 27Journal 54Unranked 5

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Mobile-MMLU: A Mobile Intelligence Language Understanding Benchmark. J. Data-centric Mach. Learn. Res. Sondos Mahmoud Bsharat, Mukul Ranjan, Aidar Myrzakhan, Jiacheng Liu, Bowei Guo, Shengkun Tang, Zhuang Liu, Yuanzhi Li, Zhiqiang Shen
2026	J	`jnl`	UEval: A Benchmark for Unified Multimodal Generation. CoRR Bo Li, Yida Yin, Wenhao Chai, Xingyu Fu, Zhuang Liu
2026	J	`jnl`	VideoAuto-R1: Video Auto Reasoning via Thinking Once, Answering Twice. CoRR 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
2025	A*	`conf`	A Coefficient Makes SVRG Effective. ICLR Yida Yin, Zhiqiu Xu, Zhiyuan Li, Trevor Darrell, Zhuang Liu
2025	A*	`conf`	A Decade's Battle on Dataset Bias: Are We There Yet? ICLR Zhuang Liu, Kaiming He
2025	J	`jnl`	AutoCode: LLMs as Problem Setters for Competitive Programming. CoRR 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
2025	A*	`conf`	Deconstructing Denoising Diffusion Models for Self-Supervised Learning. ICLR Xinlei Chen, Zhuang Liu, Saining Xie, Kaiming He
2025	J	`jnl`	DepthLM: Metric Depth From Vision Language Models. CoRR Zhipeng Cai, Ching-Feng Yeh, Hu Xu, Zhuang Liu, Gregory P. Meyer, Xinjie Lei, Changsheng Zhao, Shang-Wen (Daniel) Li, Vikas Chandra, Yangyang Shi
2025	J	`jnl`	FrontierCS: Evolving Challenges for Evolving Intelligence. CoRR 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
2025	J	`jnl`	Generative Modeling of Weights: Generalization or Memorization? CoRR Boya Zeng, Yida Yin, Zhiqiu Xu, Zhuang Liu
2025	A*	`conf`	Idiosyncrasies in Large Language Models. ICML Mingjie Sun, Yida Yin, Zhiqiu Xu, J. Zico Kolter, Zhuang Liu
2025	J	`jnl`	Idiosyncrasies in Large Language Models. CoRR Mingjie Sun, Yida Yin, Zhiqiu Xu, J. Zico Kolter, Zhuang Liu
2025	A*	`conf`	LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding. ICML 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
2025	J	`jnl`	Memorization in 3D Shape Generation: An Empirical Study. CoRR Shu Pu, Boya Zeng, Kaichen Zhou, Mengyu Wang, Zhuang Liu
2025	J	`jnl`	Meta CLIP 2: A Worldwide Scaling Recipe. CoRR 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
2025	J	`jnl`	Mobile-MMLU: A Mobile Intelligence Language Understanding Benchmark. CoRR Sondos Mahmoud Bsharat, Mukul Ranjan, Aidar Myrzakhan, Jiacheng Liu, Bowei Guo, Shengkun Tang, Zhuang Liu, Yuanzhi Li, Zhiqiang Shen
2025	J	`jnl`	Scaling Language-Free Visual Representation Learning. CoRR David Fan, Shengbang Tong, Jiachen Zhu, Koustuv Sinha, Zhuang Liu, Xinlei Chen, Michael Rabbat, Nicolas Ballas, Yann LeCun, Amir Bar, Saining Xie
2025	J	`jnl`	SoFlow: Solution Flow Models for One-Step Generative Modeling. CoRR Tianze Luo, Haotian Yuan, Zhuang Liu
2025	J	`jnl`	Stronger Normalization-Free Transformers. CoRR Mingzhi Chen, Taiming Lu, Jiachen Zhu, Mingjie Sun, Zhuang Liu
2025	A*	`conf`	Transformers without Normalization. CVPR Jiachen Zhu, Xinlei Chen, Kaiming He, Yann LeCun, Zhuang Liu
2025	J	`jnl`	Transformers without Normalization. CoRR Jiachen Zhu, Xinlei Chen, Kaiming He, Yann LeCun, Zhuang Liu
2024	J	`jnl`	A Decade's Battle on Dataset Bias: Are We There Yet? CoRR Zhuang Liu, Kaiming He
2024	A*	`conf`	A Simple and Effective Pruning Approach for Large Language Models. ICLR Mingjie Sun, Zhuang Liu, Anna Bair, J. Zico Kolter
2024	A*	`conf`	ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy. ICML Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu
2024	J	`jnl`	Deconstructing Denoising Diffusion Models for Self-Supervised Learning. CoRR Xinlei Chen, Zhuang Liu, Saining Xie, Kaiming He
2024	A*	`conf`	Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. CVPR Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie
2024	J	`jnl`	Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs. CoRR Shengbang Tong, Zhuang Liu, Yuexiang Zhai, Yi Ma, Yann LeCun, Saining Xie
2024	A*	`conf`	Initializing Models with Larger Ones. ICLR Zhiqiu Xu, Yanjie Chen, Kirill Vishniakov, Yida Yin, Zhiqiang Shen, Trevor Darrell, Lingjie Liu, Zhuang Liu
2024	J	`jnl`	LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding. CoRR 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
2024	J	`jnl`	Massive Activations in Large Language Models. CoRR Mingjie Sun, Xinlei Chen, J. Zico Kolter, Zhuang Liu
2024	J	`jnl`	MetaMorph: Multimodal Understanding and Generation via Instruction Tuning. CoRR Shengbang Tong, David Fan, Jiachen Zhu, Yunyang Xiong, Xinlei Chen, Koustuv Sinha, Michael Rabbat, Yann LeCun, Saining Xie, Zhuang Liu
2024	J	`jnl`	Neural Network Diffusion. CoRR Kai Wang, Zhaopan Xu, Yukun Zhou, Zelin Zang, Trevor Darrell, Zhuang Liu, Yang You
2024	A*	`conf`	Understanding Bias in Large-Scale Visual Datasets. NeurIPS Boya Zeng, Yida Yin, Zhuang Liu
2024	J	`jnl`	Understanding Bias in Large-Scale Visual Datasets. CoRR Boya Zeng, Yida Yin, Zhuang Liu
2023	J	`jnl`	A Coefficient Makes SVRG Effective. CoRR Yida Yin, Zhiqiu Xu, Zhiyuan Li, Trevor Darrell, Zhuang Liu
2023	J	`jnl`	A Simple and Effective Pruning Approach for Large Language Models. CoRR Mingjie Sun, Zhuang Liu, Anna Bair, J. Zico Kolter
2023	A*	`conf`	ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders. CVPR Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, Saining Xie
2023	J	`jnl`	ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders. CoRR Sanghyun Woo, Shoubhik Debnath, Ronghang Hu, Xinlei Chen, Zhuang Liu, In So Kweon, Saining Xie
2023	J	`jnl`	ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy. CoRR Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu
2023	A*	`conf`	Dropout Reduces Underfitting. ICML Zhuang Liu, Zhiqiu Xu, Joseph Jin, Zhiqiang Shen, Trevor Darrell
2023	J	`jnl`	Dropout Reduces Underfitting. CoRR Zhuang Liu, Zhiqiu Xu, Joseph Jin, Zhiqiang Shen, Trevor Darrell
2023	J	`jnl`	Exploring Simple and Transferable Recognition-Aware Image Processing. IEEE Trans. Pattern Anal. Mach. Intell. Zhuang Liu, Hung-Ju Wang, Tinghui Zhou, Zhiqiang Shen, Bingyi Kang, Evan Shelhamer, Trevor Darrell
2023	A*	`conf`	ImageBind One Embedding Space to Bind Them All. CVPR Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, Mannat Singh, Kalyan Vasudev Alwala, Armand Joulin, Ishan Misra
2023	J	`jnl`	ImageBind: One Embedding Space To Bind Them All. CoRR Rohit Girdhar, Alaaeldin El-Nouby, Zhuang Liu, Mannat Singh, Kalyan Vasudev Alwala, Armand Joulin, Ishan Misra
2023	J	`jnl`	Initializing Models with Larger Ones. CoRR Zhiqiu Xu, Yanjie Chen, Kirill Vishniakov, Yida Yin, Zhiqiang Shen, Trevor Darrell, Lingjie Liu, Zhuang Liu
2023	J	`jnl`	MSeg: A Composite Dataset for Multi-Domain Semantic Segmentation. IEEE Trans. Pattern Anal. Mach. Intell. John Lambert, Zhuang Liu, Ozan Sener, James Hays, Vladlen Koltun
2023	J	`jnl`	One-for-All: Generalized LoRA for Parameter-Efficient Fine-tuning. CoRR Arnav Chavan, Zhuang Liu, Deepak K. Gupta, Eric P. Xing, Zhiqiang Shen
2023	—	`conf`	RCV2023 Challenges: Benchmarking Model Training and Inference for Resource-Constrained Deep Learning. ICCV (Workshops) 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
2022	A*	`conf`	A ConvNet for the 2020s. CVPR Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie
2022	J	`jnl`	A ConvNet for the 2020s. CoRR Zhuang Liu, Hanzi Mao, Chao-Yuan Wu, Christoph Feichtenhofer, Trevor Darrell, Saining Xie
2022	A*	`conf`	Anytime Dense Prediction with Confidence Adaptivity. ICLR Zhuang Liu, Zhiqiu Xu, Hung-Ju Wang, Trevor Darrell, Evan Shelhamer
2022	J	`jnl`	Convolutional Networks with Dense Connectivity. IEEE Trans. Pattern Anal. Mach. Intell. Gao Huang, Zhuang Liu, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger
2022	—	`—`	Efficient and Scalable Neural Architectures for Visual Recognition Zhuang Liu
2022	A*	`conf`	Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning. AAAI Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell, Eric Poe Xing
2022	A*	`conf`	Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CVPR Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing
2022	J	`jnl`	Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space. CoRR Arnav Chavan, Zhiqiang Shen, Zhuang Liu, Zechun Liu, Kwang-Ting Cheng, Eric P. Xing
2021	J	`jnl`	Confidence Adaptive Anytime Pixel-Level Recognition. CoRR Zhuang Liu, Trevor Darrell, Evan Shelhamer
2021	J	`jnl`	MSeg: A Composite Dataset for Multi-domain Semantic Segmentation. CoRR John Lambert, Zhuang Liu, Ozan Sener, James Hays, Vladlen Koltun
2021	A*	`conf`	Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning. ICCV Yinbo Chen, Zhuang Liu, Huijuan Xu, Trevor Darrell, Xiaolong Wang
2021	A*	`conf`	Regularization Matters in Policy Optimization - An Empirical Study on Continuous Control. ICLR Zhuang Liu, Xuanlin Li, Bingyi Kang, Trevor Darrell
2021	—	`conf`	sensAI: ConvNets Decomposition via Class Parallelism for Fast Inference on Live Data. MLSys Guanhua Wang, Zhuang Liu, Brandon Hsieh, Siyuan Zhuang, Joseph Gonzalez, Trevor Darrell, Ion Stoica
2020	J	`jnl`	A New Meta-Baseline for Few-Shot Learning. CoRR Yinbo Chen, Xiaolong Wang, Zhuang Liu, Huijuan Xu, Trevor Darrell
2020	J	`jnl`	Convolutional Networks with Dense Connectivity. CoRR Gao Huang, Zhuang Liu, Geoff Pleiss, Laurens van der Maaten, Kilian Q. Weinberger
2020	A*	`conf`	Few Sample Knowledge Distillation for Efficient Network Compression. CVPR Tianhong Li, Jianguo Li, Zhuang Liu, Changshui Zhang
2020	A*	`conf`	MSeg: A Composite Dataset for Multi-Domain Semantic Segmentation. CVPR John Lambert, Zhuang Liu, Ozan Sener, James Hays, Vladlen Koltun
2020	J	`jnl`	Object Detection from Scratch with Deep Supervision. IEEE Trans. Pattern Anal. Mach. Intell. Zhiqiang Shen, Zhuang Liu, Jianguo Li, Yu-Gang Jiang, Yurong Chen, Xiangyang Xue
2020	J	`jnl`	Rethinking Image Mixture for Unsupervised Visual Representation Learning. CoRR Zhiqiang Shen, Zechun Liu, Zhuang Liu, Marios Savvides, Trevor Darrell
2020	A*	`conf`	Test-Time Training with Self-Supervision for Generalization under Distribution Shifts. ICML Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei A. Efros, Moritz Hardt
2019	A*	`conf`	Few-Shot Object Detection via Feature Reweighting. ICCV Bingyi Kang, Zhuang Liu, Xin Wang, Fisher Yu, Jiashi Feng, Trevor Darrell
2019	J	`jnl`	Regularization Matters in Policy Optimization. CoRR Zhuang Liu, Xuanlin Li, Bingyi Kang, Trevor Darrell
2019	—	`conf`	Rethinking the Value of Network Pruning. ICLR (Poster) Zhuang Liu, Mingjie Sun, Tinghui Zhou, Gao Huang, Trevor Darrell
2019	J	`jnl`	Test-Time Training for Out-of-Distribution Generalization. CoRR Yu Sun, Xiaolong Wang, Zhuang Liu, John Miller, Alexei A. Efros, Moritz Hardt
2019	J	`jnl`	Transferable Recognition-Aware Image Processing. CoRR Zhuang Liu, Tinghui Zhou, Zhiqiang Shen, Bingyi Kang, Trevor Darrell
2018	J	`jnl`	Few-shot Object Detection via Feature Reweighting. CoRR Bingyi Kang, Zhuang Liu, Xin Wang, Fisher Yu, Jiashi Feng, Trevor Darrell
2018	J	`jnl`	Knowledge Distillation from Few Samples. CoRR Tianhong Li, Jianguo Li, Zhuang Liu, Changshui Zhang
2018	J	`jnl`	Object Detection from Scratch with Deep Supervision. CoRR Zhiqiang Shen, Zhuang Liu, Jianguo Li, Yu-Gang Jiang, Yurong Chen, Xiangyang Xue
2018	J	`jnl`	Rethinking the Value of Network Pruning. CoRR Zhuang Liu, Mingjie Sun, Tinghui Zhou, Gao Huang, Trevor Darrell
2017	A*	`conf`	DSOD: Learning Deeply Supervised Object Detectors from Scratch. ICCV Zhiqiang Shen, Zhuang Liu, Jianguo Li, Yu-Gang Jiang, Yurong Chen, Xiangyang Xue
2017	J	`jnl`	DSOD: Learning Deeply Supervised Object Detectors from Scratch. CoRR Zhiqiang Shen, Zhuang Liu, Jianguo Li, Yu-Gang Jiang, Yurong Chen, Xiangyang Xue
2017	A*	`conf`	Densely Connected Convolutional Networks. CVPR Gao Huang, Zhuang Liu, Laurens van der Maaten, Kilian Q. Weinberger
2017	A*	`conf`	Learning Efficient Convolutional Networks through Network Slimming. ICCV Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, Changshui Zhang
2017	J	`jnl`	Learning Efficient Convolutional Networks through Network Slimming. CoRR Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, Changshui Zhang
2017	—	`conf`	Snapshot Ensembles: Train 1, Get M for Free. ICLR (Poster) Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger
2017	J	`jnl`	Snapshot Ensembles: Train 1, get M for free. CoRR Gao Huang, Yixuan Li, Geoff Pleiss, Zhuang Liu, John E. Hopcroft, Kilian Q. Weinberger
2016	—	`conf`	Deep Networks with Stochastic Depth. ECCV (4) Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Q. Weinberger
2016	J	`jnl`	Deep Networks with Stochastic Depth. CoRR Gao Huang, Yu Sun, Zhuang Liu, Daniel Sedra, Kilian Q. Weinberger
2016	J	`jnl`	Densely Connected Convolutional Networks. CoRR Gao Huang, Zhuang Liu, Kilian Q. Weinberger