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1. Transformer-Explainability Transformer-Explainability Public

   [CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.

   Jupyter Notebook 2k 260

2. Transformer-MM-Explainability Transformer-MM-Explainability Public

   [ICCV 2021- Oral] Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-…

   Jupyter Notebook 914 118

3. black-forest-labs/Self-Flow black-forest-labs/Self-Flow Public

   [ICML'26] Code and website for Self-Flow: Self-Supervised Flow Matching for Scalable Multi-Modal Synthesis

   Python 770 26

4. yuval-alaluf/Attend-and-Excite yuval-alaluf/Attend-and-Excite Public

   Official Implementation for "Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Models" (SIGGRAPH 2023)

   Jupyter Notebook 769 63

5. TargetCLIP TargetCLIP Public

   [ECCV 2022] Official PyTorch implementation of the paper Image-Based CLIP-Guided Essence Transfer.

   Jupyter Notebook 231 27

6. RobustViT RobustViT Public

   [NeurIPS 2022] Official PyTorch implementation of Optimizing Relevance Maps of Vision Transformers Improves Robustness. This code allows to finetune the explainability maps of Vision Transformers t…

   Jupyter Notebook 134 14