Scholar
Hila Chefer
Google Scholar ID: B8sA9JoAAAAJ
PhD student at Tel Aviv University, Meta
Deep Learning
Computer Vision
NLP
Explainable AI
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Homepage
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Google Scholar
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Citations & Impact
All-time
Citations
2,800
H-index
11
i10-index
11
Publications
14
Co-authors
16
list available
Contact
Email
hilach70@gmail.com
Twitter
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GitHub
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Publications
6 items
Self-Supervised Flow Matching for Scalable Multi-Modal Synthesis
2026
Cited
0
Revisiting LRP: Positional Attribution as the Missing Ingredient for Transformer Explainability
2025
Cited
0
FlowMo: Variance-Based Flow Guidance for Coherent Motion in Video Generation
2025
Cited
0
A Meaningful Perturbation Metric for Evaluating Explainability Methods
2025
Cited
0
VideoJAM: Joint Appearance-Motion Representations for Enhanced Motion Generation in Video Models
2025
Cited
0
Discriminative Class Tokens for Text-to-Image Diffusion Models
IEEE International Conference on Computer Vision · 2023
Cited
5
Resume (English only)
Academic Achievements
Work covered by The Verge, ZDNET, Two Minute Papers, Analytics India Magazine, etc.
Pioneered Transformer explainability methods for single and multi-modality
Developed Attend-and-Excite: inference-time semantic guidance for diffusion models
Co-developed Lumiere: a foundation model for efficient text-to-video generation (with Google Research)
Led VideoJAM: a novel training framework achieving SOTA motion and physics understanding in video generation (with Meta AI)
Two papers accepted to NeurIPS 2025 (FlowMo and Revisiting LRP)
VideoJAM accepted as oral presentation at ICML'25 (top ~1%)
Delivering two keynotes and co-organizing two workshops at ICCV'25
Co-authors
16 total
Lior Wolf
The School of Computer Science at Tel Aviv University
Co-author 2
Inbar Mosseri
Google DeepMind
Shiran Zada
Computer vision researcher at Google DeepMind
Ariel Ephrat
Google DeepMind
Tomer Michaeli
Associate Professor, ECE, Technion; Visiting Researcher, Google DeepMind
Omer Tov
Google
Michael Rubinstein
Google DeepMind
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