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WearableQA: A Benchmark for Health Reasoning over Real-World Wearable Data research paper by Meta, 2026

Meta · Sep 4, 2026 · Agents and evaluation · 0 citations · 43 upvotes · unverified

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What it shows

WearableQA is a benchmark of multiple-choice questions derived from real longitudinal wearable data that evaluates large language model reasoning across data and health dimensions.

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Authors
Ji Soo Lee, Xilun Chen, Pierce Chuang and 5 more
arXiv
2609.05405 · PDF
Citations
0, 0 influential · Semantic Scholar
Upvotes
43 · Hugging Face
Code
github.com/facebookresearch/WearableQA
Lab
Meta · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
Upvotes30 to 43 (+13)Sep 25, 2026
Influential citationsfirst count: 0Sep 25, 2026
Citationsfirst count: 0Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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