Alternatives and similar repositories for understand_bias

Users that are interested in understand_bias are comparing it to the libraries listed below

• UCSC-VLAA / CLIPS
  An Enhanced CLIP Framework for Learning with Synthetic Captions
  ☆37Updated 6 months ago
• ChengHan111 / VPT-or-FT
  Official Pytorch implementation of 'Facing the Elephant in the Room: Visual Prompt Tuning or Full Finetuning'? (ICLR2024)
  ☆13Updated last year
• showlab / datacentric.vlp
  Compress conventional Vision-Language Pre-training data
  ☆52Updated 2 years ago
• Hritikbansal / generative-robustness
  Create generated datasets and train robust classifiers
  ☆36Updated 2 years ago
• ExplainableML / WaffleCLIP
  Official repository for the ICCV 2023 paper: "Waffling around for Performance: Visual Classification with Random Words and Broad Concepts…
  ☆59Updated 2 years ago
• chenshuang-zhang / imagenet_d
  [CVPR 2024 Highlight] ImageNet-D
  ☆44Updated last year
• lisadunlap / ALIA
  Augmenting with Language-guided Image Augmentation (ALIA)
  ☆81Updated last year
• SivanDoveh / TSVLC
  Repository for the paper: Teaching Structured Vision & Language Concepts to Vision & Language Models
  ☆47Updated 2 years ago
• cvlab-columbia / DoubleRight
  ☆27Updated last year
• hammoudhasan / DiversitySSL
  Original code base for On Pretraining Data Diversity for Self-Supervised Learning
  ☆14Updated 9 months ago
• TencentARC / pi-Tuning
  Official code for "pi-Tuning: Transferring Multimodal Foundation Models with Optimal Multi-task Interpolation", ICML 2023.
  ☆33Updated 2 years ago
• ggjy / vision_weak_to_strong
  ☆37Updated last year
• codezakh / LilT
  [ICLR 23] Contrastive Aligned of Vision to Language Through Parameter-Efficient Transfer Learning
  ☆40Updated 2 years ago
• tripletclip / TripletCLIP
  [NeurIPS 2024] Official PyTorch implementation of "Improving Compositional Reasoning of CLIP via Synthetic Vision-Language Negatives"
  ☆44Updated 10 months ago
• arijitray1993 / COLA
  COLA: Evaluate how well your vision-language model can Compose Objects Localized with Attributes!
  ☆24Updated 11 months ago
• naver-ai / prolip
  ☆53Updated 2 months ago
• TencentARC / TaCA
  Official code for the paper, "TaCA: Upgrading Your Visual Foundation Model with Task-agnostic Compatible Adapter".
  ☆16Updated 2 years ago
• fengyuli-dev / distribution-normalization
  Test-Time Distribution Normalization For Contrastively Learned Vision-language Models
  ☆27Updated last year
• iancovert / locality-alignment
  ☆53Updated 9 months ago
• orrzohar / LOVM
  [NeurIPS 2023] Official Pytorch code for LOVM: Language-Only Vision Model Selection
  ☆21Updated last year
• modestyachts / ImageNetV2_pytorch
  ImageNetV2 Pytorch Dataset
  ☆41Updated 2 years ago
• brendel-group / clip-ood
  Official code for the paper "Does CLIP's Generalization Performance Mainly Stem from High Train-Test Similarity?" (ICLR 2024)
  ☆10Updated last year
• facebookresearch / CiT
  Code for the paper titled "CiT Curation in Training for Effective Vision-Language Data".
  ☆78Updated 2 years ago
• zycheiheihei / Transferable-Visual-Prompting
  [CVPR2024 Highlight] Official implementation for Transferable Visual Prompting. The paper "Exploring the Transferability of Visual Prompt…
  ☆44Updated 10 months ago
• hammoudhasan / SynthCLIP
  Code base of SynthCLIP: CLIP training with purely synthetic text-image pairs from LLMs and TTIs.
  ☆100Updated 7 months ago
• liuzhuang13 / bias
  ☆112Updated last year
• CVMI-Lab / clip-beyond-tail
  (NeurIPS 2024) What Makes CLIP More Robust to Long-Tailed Pre-Training Data? A Controlled Study for Transferable Insights
  ☆28Updated 11 months ago
• tonychenxyz / vit-interpret
  Official implementation of "Interpreting and Controlling Vision Foundation Models via Text Explanations"
  ☆13Updated last year
• TencentARC / FLM
  Accelerating Vision-Language Pretraining with Free Language Modeling (CVPR 2023)
  ☆32Updated 2 years ago
• AtsuMiyai / UPD
  [ACL2025] Unsolvable Problem Detection: Robust Understanding Evaluation for Large Multimodal Models
  ☆78Updated 4 months ago