Zhuang Liu

OpenReview

papers

11,738

total citations

papers (14)

Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space

CVPR 2022arXiv

citations

A Decade's Battle on Dataset Bias: Are We There Yet?

ICLR 2025arXiv

citations

Scaling Language-Free Visual Representation Learning

ICCV 2025arXiv

citations

ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy

ICML 2024arXiv

citations

Idiosyncrasies in Large Language Models

ICML 2025arXiv

citations

Few Sample Knowledge Distillation for Efficient Network Compression

CVPR 2020arXiv

citations

Zhuang Liu

papers (14)

A ConvNet for the 2020s

ConvNeXt V2: Co-Designing and Scaling ConvNets With Masked Autoencoders

ImageBind: One Embedding Space To Bind Them All

Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs

Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning

MSeg: A Composite Dataset for Multi-Domain Semantic Segmentation

MetaMorph: Multimodal Understanding and Generation via Instruction Tuning

Transformers without Normalization

Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space

A Decade's Battle on Dataset Bias: Are We There Yet?

Scaling Language-Free Visual Representation Learning

ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy

Idiosyncrasies in Large Language Models

Few Sample Knowledge Distillation for Efficient Network Compression

papers (14)

A ConvNet for the 2020s

ConvNeXt V2: Co-Designing and Scaling ConvNets With Masked Autoencoders

ImageBind: One Embedding Space To Bind Them All

Eyes Wide Shut? Exploring the Visual Shortcomings of Multimodal LLMs

Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning

MSeg: A Composite Dataset for Multi-Domain Semantic Segmentation

MetaMorph: Multimodal Understanding and Generation via Instruction Tuning

Transformers without Normalization

Vision Transformer Slimming: Multi-Dimension Searching in Continuous Optimization Space

A Decade's Battle on Dataset Bias: Are We There Yet?

Scaling Language-Free Visual Representation Learning

ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy

Idiosyncrasies in Large Language Models

Few Sample Knowledge Distillation for Efficient Network Compression