4 papers · 1 filter
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…
CAVE: Detecting and Explaining Commonsense Anomalies in Visual Environments
Rishika Bhagwatkar, Syrielle Montariol, Angelika Romanou +3
Humans can naturally identify, reason about, and explain anomalies in their environment. In computer vision, this long-standing challenge remains limited to industrial defects or u…
CHIRP: A Fine-Grained Benchmark for Open-Ended Response Evaluation in Vision-Language Models
Alexis Roger, Prateek Humane, Daniel Z. Kaplan +7
The proliferation of Vision-Language Models (VLMs) in the past several years calls for rigorous and comprehensive evaluation methods and benchmarks. This work analyzes existing VLM…
Towards Adversarially Robust Vision-Language Models: Insights from Design Choices and Prompt Formatting Techniques
Rishika Bhagwatkar, Shravan Nayak, Reza Bayat +4
Vision-Language Models (VLMs) have witnessed a surge in both research and real-world applications. However, as they are becoming increasingly prevalent, ensuring their robustness a…