65 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre National de la Recherche ScientifiqueFR3 papers
- Laboratoire de Mathématiques Blaise PascalFR2 papers
- Laboratoire de Mathématiques et Modélisation d'ÉvryFR2 papers
- Assistance Publique – Hôpitaux de ParisFR1 paper
- Bicêtre HospitalFR1 paper
- École Centrale de NantesFR1 paper
- École Nationale Supérieure d’Informatique pour l’Industrie et l’EntrepriseFR1 paper
- Equipes Traitement de l'Information et SystèmesFR1 paper
- Hôpital Antoine-BéclèreFR1 paper
- Hôpitaux Universitaires de StrasbourgFR1 paper
- InsermFR1 paper
- Institut National Polytechnique de ToulouseFR1 paper
5 papers · 1 filter
PixelBytes: Catching Unified Embedding for Multimodal Generation
Fabien Furfaro
This report introduces PixelBytes Embedding, a novel approach for unified multimodal representation learning. Our method captures diverse inputs in a single, cohesive representatio…
PixelBytes: Catching Unified Representation for Multimodal Generation
Fabien Furfaro
This report presents PixelBytes, an approach for unified multimodal representation learning. Drawing inspiration from sequence models like Image Transformers, PixelCNN, and Mamba-B…
Long-Range Reading of Multiple Chipless Sensors from the Isoline Processing of 3D Radar Images
A. Hadj Djilani, Dominique Henry, A. El Sayed Ahmad +2
In this paper, we report the long-range and wireless interrogation of multiple chipless sensors from the isoline processing of three-dimensional polarimetric radar images. A Freque…
Towards Universal and Black-Box Query-Response Only Attack on LLMs with QROA
Hussein Jawad, Yassine Chenik, Nicolas J. -B. Brunel
The rapid adoption of Large Language Models (LLMs) has exposed critical security and ethical vulnerabilities, particularly their susceptibility to adversarial manipulations. This p…
Detection Transformer for Teeth Detection, Segmentation, and Numbering in Oral Rare Diseases: Focus on Data Augmentation and Inpainting Techniques
Hocine Kadi, Théo Sourget, Marzena Kawczynski +3
In this work, we focused on deep learning image processing in the context of oral rare diseases, which pose challenges due to limited data availability. A crucial step involves tee…