Cross-Modal Attention Acts as a Frequency Filter: Why Verbose Prompts Improve Robustness in Vision-Language Models
Vision-language models (VLMs) are fragile under image corruption. We find that the wording of the question affects VLMs in two opposite ways. Verbose questions make VLMs substantially more robust---e.g., rephrasing"Is there a cat?"into"Please look carefully and answer: is there a cat?". Conversely, VLMs become more fra...
Farooq Ahmad Wani, Maria Sofia Bucarelli, Mujtaba Hussain Mirza et al.
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