SAGE: Spuriousness-Aware Guided Prompt Exploration for Mitigating Multimodal Bias

Wenqian Ye; Di Wang; Guangtao Zheng; Bohan Liu; Aidong Zhang

AAAI 2026technical0 citations

SAGE: Spuriousness-Aware Guided Prompt Exploration for Mitigating Multimodal Bias

Wenqian Ye, Di Wang, Guangtao Zheng, Bohan Liu, Aidong Zhang

Abstract

Large vision-language models such as CLIP have shown strong zero-shot classification performance by aligning images and text in a shared embedding space. However, CLIP models often develop multimodal spurious biases, the undesirable tendency to rely on spurious features. For example, CLIP may infer object types in images based on frequently co-occurring backgrounds rather than the object

BibTeX

@inproceedings{aaai2026_sagespuriousness,
  title = {SAGE: Spuriousness-Aware Guided Prompt Exploration for Mitigating Multimodal Bias},
  author = {Wenqian Ye and Di Wang and Guangtao Zheng and Bohan Liu and Aidong Zhang},
  booktitle = {AAAI 2026},
  year = {2026}
}