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Apr, 2023
构建强韧的图像-语言模型提示
Towards Robust Prompts on Vision-Language Models
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Jindong Gu, Ahmad Beirami, Xuezhi Wang, Alex Beutel, Philip Torr...
TL;DR
本研究通过将多尺度图像特征集成到提示中，提出了一种对于分布偏移具有鲁棒性的提示学习方法，实验结果表明，这种方法在多个基准测试数据集上的鲁棒性和性能有所提高。
Abstract
With the advent of
vision-language models
(VLMs) that can perform in-context and
prompt-based learning
, how can we design prompting approaches that robustly generalize to
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