| Densely Connected Convolutional Networks Z Liu*, G Huang*, L Maaten, KQ Weinberger Computer Vision and Pattern Recognition (CVPR), 2017, 2017 | 48743* | 2017 |
| A ConvNet for the 2020s Z Liu, H Mao, CY Wu, C Feichtenhofer, T Darrell, S Xie Computer Vision and Pattern Recognition (CVPR), 2022, 2022 | 5646 | 2022 |
| Learning Efficient Convolutional Networks through Network Slimming Z Liu, J Li, Z Shen, G Huang, S Yan, C Zhang International Conference on Computer Vision (ICCV), 2017, 2017 | 2987 | 2017 |
| Deep Networks with Stochastic Depth G Huang*, Y Sun*, Z Liu, D Sedra, KQ Weinberger European Conference on Computer Vision (ECCV), 2016, 2016 | 2776 | 2016 |
| Rethinking the Value of Network Pruning Z Liu*, M Sun*, T Zhou, G Huang, T Darrell International Conference on Learning Representations (ICLR), 2019, 2019 | 1734 | 2019 |
| Few-shot Object Detection via Feature Reweighting B Kang*, Z Liu*, X Wang, F Yu, J Feng, T Darrell International Conference on Computer Vision (ICCV), 2019, 2019 | 889 | 2019 |
| DSOD: Learning Deeply Supervised Object Detectors from Scratch Z Shen*, Z Liu*, J Li, YG Jiang, Y Chen, X Xue International Conference on Computer Vision (ICCV), 2017, 2017 | 879* | 2017 |
| Test-time Training with Self-supervision for Generalization under Distribution Shifts Y Sun, X Wang, Z Liu, J Miller, A Efros, M Hardt International Conference on Machine Learning (ICML), 2020, 2020 | 803 | 2020 |
| Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning Y Chen, Z Liu, H Xu, T Darrell, X Wang International Conference on Computer Vision (ICCV), 2021, 2021 | 682* | 2021 |
| Imagebind: One Embedding Space to Bind Them All R Girdhar*, A El-Nouby*, Z Liu, M Singh, KV Alwala, A Joulin, I Misra* Computer Vision and Pattern Recognition (CVPR), 2023, 2023 | 665 | 2023 |
| ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders S Woo, S Debnath, R Hu, X Chen, Z Liu, IS Kweon, S Xie Computer Vision and Pattern Recognition (CVPR), 2023, 2023 | 633* | 2023 |
| A Simple and Effective Pruning Approach for Large Language Models M Sun*, Z Liu*, A Bair, JZ Kolter International Conference on Learning Representations (ICLR), 2024, 2024 | 268 | 2024 |
| MSeg: A Composite Dataset for Multi-domain Semantic Segmentation J Lambert*, Z Liu*, O Sener, J Hayes, V Koltun Computer Vision and Pattern Recognition (CVPR), 2020, 2020 | 207 | 2020 |
| Few Sample Knowledge Distillation for Efficient Network Compression T Li, J Li, Z Liu, C Zhang Computer Vision and Pattern Recognition (CVPR), 2020, 2020 | 177* | 2020 |
| Un-mix: Rethinking Image Mixtures for Unsupervised Visual Representation Learning Z Shen, Z Liu, Z Liu, M Savvides, T Darrell, E Xing AAAI Conference on Artificial Intelligence (AAAI), 2022, 2022 | 128 | 2022 |
| Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs S Tong, Z Liu, Y Zhai, Y Ma, Y LeCun, S Xie Computer Vision and Pattern Recognition (CVPR), 2024, 2024 | 118 | 2024 |
| Regularization Matters in Policy Optimization--An Empirical Study on Continuous Control Z Liu*, X Li*, B Kang, T Darrell International Conference on Learning Representations (ICLR), 2021, 2021 | 83* | 2021 |
| Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space A Chavan*, Z Shen*, Z Liu, Z Liu, KT Cheng, E Xing Computer Vision and Pattern Recognition (CVPR), 2022, 2022 | 74 | 2022 |
| One-for-all: Generalized LoRA for Parameter-Efficient Fine-Tuning A Chavan, Z Liu, D Gupta, E Xing, Z Shen arXiv preprint arXiv:2306.07967, 2023 | 59 | 2023 |
| Dropout Reduces Underfitting Z Liu*, Z Xu*, J Jin, Z Shen, T Darrell International Conference on Machine Learning (ICML), 2023, 2023 | 44 | 2023 |
Kilian WeinbergerCornell University在 cornell.edu 的电子邮件经过验证
