activity
20162026
most citedUnderstanding and Improving Fast Adversarial Training

44 citations · 140 across the 27 of their papers we have counts for

collaborators
Showing cs.CVShow all

5 papers · 1 filter

cs.CV2026

On the Adversarial Robustness of Discrete Image Tokenizers

Rishika Bhagwatkar, Irina Rish, Nicolas Flammarion +1

Discrete image tokenizers encode visual inputs as sequences of tokens from a finite vocabulary and are gaining popularity in multimodal systems, including encoder-only, encoder-dec…

cs.CV2025

FuseLIP: Multimodal Embeddings via Early Fusion of Discrete Tokens

Christian Schlarmann, Francesco Croce, Nicolas Flammarion +1

Contrastive language-image pre-training aligns features of text-image pairs in a common latent space via distinct encoders for each modality. While this approach achieves impressiv…

cs.CV2025

Chain-of-Frames: Advancing Video Understanding in Multimodal LLMs via Frame-Aware Reasoning

Sara Ghazanfari, Francesco Croce, Nicolas Flammarion +3

Recent work has shown that eliciting Large Language Models (LLMs) to generate reasoning traces in natural language before answering the user's request can significantly improve the…

cs.CV2024

Towards Unified Benchmark and Models for Multi-Modal Perceptual Metrics

Sara Ghazanfari, Siddharth Garg, Nicolas Flammarion +3

Human perception of similarity across uni- and multimodal inputs is highly complex, making it challenging to develop automated metrics that accurately mimic it. General purpose vis…

cs.CV2022

ARIA: Adversarially Robust Image Attribution for Content Provenance

Maksym Andriushchenko, Xiaoyang Rebecca Li, Geoffrey Oxholm +4

Image attribution -- matching an image back to a trusted source -- is an emerging tool in the fight against online misinformation. Deep visual fingerprinting models have recently b…