Ismail Ben Ayed

Venues

Frequent coauthors

Papers

1. Histopath-C: Towards Realistic Domain Shifts for Histopathology Vision-Language Adaptation
   WACV 2026 ·

   Mehrdad Noori

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2. Revisiting Layer Normalization for Point Cloud Test Time Adaptation
   WACV 2026 ·

   Moslem Yazdanpanah

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3. AttackBench: Evaluating Gradient-based Attacks for Adversarial Examples
   AAAI 2025 ·

   Antonio Emanuele Cinà

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4. CLIPArTT: Adaptation of CLIP to New Domains at Test Time
   WACV 2025 ·

   Gustavo Adolfo Vargas Hakim

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5. Conformal Prediction for Zero-Shot Models
   CVPR 2025 ·

   Julio Silva-Rodríguez

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6. FDS: Feedback-Guided Domain Synthesis with Multi-Source Conditional Diffusion Models for Domain Generalization
   WACV 2025 ·

   Ali Bahri

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7. Few-Shot, Now for Real: Medical VLMs Adaptation Without Balanced Sets or Validation
   MICCAI 2025 ·

   Julio Silva-Rodríguez

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8. Learning Task-Agnostic Representations through Multi-Teacher Distillation
   NeurIPS 2025 ·

   Philippe Formont

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9. Pay Attention to Your Neighbours: Training-Free Open-Vocabulary Semantic Segmentation
   WACV 2025 ·

   Sina Hajimiri

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10. Purge-Gate: Backpropagation-Free Test-Time Adaptation for Point Clouds Classification via Token Purging
    ICCV 2025 ·

    Moslem Yazdanpanah

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11. Realistic Test-Time Adaptation of Vision-Language Models
    CVPR 2025 ·

    Maxime Zanella

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12. Reflect: Rectified Flows for Efficient Brain Anomaly Correction Transport
    MICCAI 2025 ·

    Farzad Beizaee

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13. Regularized Low-Rank Adaptation for Few-Shot Organ Segmentation
    MICCAI 2025 ·

    Ghassen Baklouti

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14. SMART-PC: Skeletal Model Adaptation for Robust Test-Time Training in Point Clouds
    ICML 2025 ·

    Ali Bahri

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15. Sparsity Outperforms Low-Rank Projections in Few-Shot Adaptation
    ICCV 2025 ·

    Nairouz Mrabah

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16. Spectral Informed Mamba for Robust Point Cloud Processing
    CVPR 2025 ·

    Ali Bahri

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17. TRUST: Test-Time Refinement using Uncertainty-Guided SSM Traverses
    NeurIPS 2025 ·

    Sahar Dastani

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18. Test-Time Adaptation in Point Clouds: Leveraging Sampling Variation with Weight Averaging
    WACV 2025 ·

    Ali Bahri

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19. Test-Time Adaptation of Medical Vision-Language Models
    MICCAI 2025 ·

    Fereshteh Shakeri

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20. Test-Time Adaptation of Vision-Language Models for Open-Vocabulary Semantic Segmentation
    NeurIPS 2025 ·

    Mehrdad Noori

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21. Trustworthy Few-Shot Transfer of Medical VLMs Through Split Conformal Prediction
    MICCAI 2025 ·

    Julio Silva-Rodríguez

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22. UNEM: UNrolled Generalized EM for Transductive Few-Shot Learning
    CVPR 2025 ·

    Long Zhou

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23. ViLU: Learning Vision-Language Uncertainties for Failure Prediction
    ICCV 2025 ·

    Marc Lafon

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24. Vocabulary-free few-shot learning for vision-language models
    CVPR 2025 ·

    Maxime Zanella

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25. A Closer Look at the Few-Shot Adaptation of Large Vision-Language Models
    CVPR 2024 ·

    Julio Silva-Rodríguez

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26. Boosting Vision-Language Models for Histopathology Classification: Predict All at Once
    MICCAI 2024 ·

    Maxime Zanella

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27. Boosting Vision-Language Models with Transduction
    NeurIPS 2024 ·

    Maxime Zanella

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28. Class and Region-Adaptive Constraints for Network Calibration
    MICCAI 2024 ·

    Balamurali Murugesan

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29. Few-Shot Adaptation of Medical Vision-Language Models
    MICCAI 2024 ·

    Fereshteh Shakeri

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30. LP++: A Surprisingly Strong Linear Probe for Few-Shot CLIP
    CVPR 2024 ·

    Yunshi Huang

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31. Low-Rank Few-Shot Adaptation of Vision-Language Models
    CVPR 2024 ·

    Maxime Zanella

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32. NC-TTT: A Noise Constrastive Approach for Test-Time Training
    CVPR 2024 ·

    David Osowiechi

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33. On the Test-Time Zero-Shot Generalization of Vision-Language Models: Do we Really need Prompt Learning?
    CVPR 2024 ·

    Maxime Zanella

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34. Robust Calibration of Large Vision-Language Adapters
    ECCV 2024 ·

    Balamurali Murugesan

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35. Transductive Zero-Shot and Few-Shot CLIP
    CVPR 2024 ·

    Ségolène Martin

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36. WATT: Weight Average Test Time Adaptation of CLIP
    NeurIPS 2024 ·

    David Osowiechi

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37. When is an Embedding Model More Promising than Another?
    NeurIPS 2024 ·

    Maxime Darrin

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