SnapBench shows image noise cripples mobile snap-and-ask multimodal retrieval
Zirong Chen · hf · 2026-09-03
SnapBench is a new benchmark for mobile snap-and-ask multimodal retrieval. It introduces paired corruption benchmarks — clean vs. noisy screenshots of the same mobile interactions — revealing that image noise severely degrades multimodal retrieval, meaning lab-grade screenshot retrieval models may fail badly on real user snaps. The authors propose an adaptive fusion method that calibrates modality reliability to mitigate the degradation. Directly relevant for building mobile multimodal assistants.
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