Are Prompt Optimizers Blind? Cross-Modal Visual Feedback for Automatic Prompt Optimization
Automatic prompt optimization (APO) has been widely adopted to adapt vision-language models (VLMs) to downstream tasks without weight updates, yielding promising results. However, on multimodal tasks, the effectiveness of APO is fundamentally bottlenecked by a blind feedback channel: the optimizer reads the question, the prediction, and the gold answer, but never the input image on which the model failed, and therefore cannot diagnose visually grounded errors. As a remedy, we introduce Cross-Mod
Record details
Published: 27 July 2026
Source: arXiv cs.AI
Category: Research
Topics: Healthcare
Retrieved: 28 July 2026
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ethics.ai (27 July 2026), “Are Prompt Optimizers Blind? Cross-Modal Visual Feedback for Automatic Prompt Optimization,” evidence record 14054, https://ethics.ai/record/14054 (originally published by arXiv cs.AI).
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