Unveiling Typographic Deceptions: Typographic Vulnerability in LVLMs
Date: 2024-02
Affected: GPT-4V, Claude-3, LLaVA, large VLMs
Attack vector: adversarial-input
Category: research
Severity: Medium

Cheng et al. introduce the TypoD benchmark and analyze why large vision-language models (Claude-3, GPT-4V, LLaVA) are deceived by typographic injection, showing the role of prompt formulation.


Mitigations:

Architectural layers (MAESTRO):