Hila Chefer

Orcid: 0000-0003-1585-8782

According to our database1, Hila Chefer authored at least 15 papers between 2021 and 2025.

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Bibliography

2025
Revisiting LRP: Positional Attribution as the Missing Ingredient for Transformer Explainability.
CoRR, June, 2025

FlowMo: Variance-Based Flow Guidance for Coherent Motion in Video Generation.
CoRR, June, 2025

VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models.
CoRR, February, 2025

A Meaningful Perturbation Metric for Evaluating Explainability Methods.
Proceedings of the Image Analysis - 23rd Scandinavian Conference, 2025

2024
Still-Moving: Customized Video Generation without Customized Video Data.
ACM Trans. Graph., December, 2024

Lumiere: A Space-Time Diffusion Model for Video Generation.
Proceedings of the SIGGRAPH Asia 2024 Conference Papers, 2024

The Hidden Language of Diffusion Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
Attend-and-Excite: Attention-Based Semantic Guidance for Text-to-Image Diffusion Models.
ACM Trans. Graph., August, 2023

Discriminative Class Tokens for Text-to-Image Diffusion Models.
CoRR, 2023

Discriminative Class Tokens for Text-to-Image Diffusion Models.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Optimizing Relevance Maps of Vision Transformers Improves Robustness.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

No Token Left Behind: Explainability-Aided Image Classification and Generation.
Proceedings of the Computer Vision - ECCV 2022, 2022

Image-Based CLIP-Guided Essence Transfer.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Transformer Interpretability Beyond Attention Visualization.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021


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