Escaping the SpuriVerse: Can Large Vision-Language Models Generalize Beyond Seen Spurious Correlations?
Sep 1, 2025·
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1 min read
Yiwei Yang
Equal contribution
,Chung Peng Lee
Equal contribution
,Shangbin Feng
Dora Zhao
Bingbing Wen
Anthony Z. Liu
Yulia Tsvetkov
Bill Howe
Abstract
We study whether large vision-language models can generalize beyond spurious correlations observed during training, introducing a benchmark to probe robustness to spurious signals.
Type
Publication
NeurIPS 2025 Datasets and Benchmarks
We introduce a benchmark to evaluate whether large vision-language models can move beyond spurious correlations and generalize robustly to distribution shifts that break shortcut cues.
