SOURCE-LINKED INTELLIGENCE
SnapBench: Benchmarking Snap-and-Ask Multimodal Retrieval for Mobile Interactions
Mobile AI acts as a visual oracle, empowering users to snap a picture of something and ask for information. Snap-and-ask retrieval is now one of the most common entry points for mobile AI, yet photos are often blurry, while text questions may be short or mistyped. Existing benchmarks only test on clean inputs or do not isolate paired robustness in snap-and-ask retrieval. Therefore, we introduce SnapBench, the first paired benchmark for robust snap-and-ask multimodal retrieval, spanning 1,145 queries, 9,085 gallery items under 53 controlled corruption conditions with human annotations. We evalu
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-30T06:56:11.000Z
First collected: 2026-09-21T07:31:56.984Z. This is not the publication date.