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WearableQA: A Benchmark for Health Reasoning over Real-World Wearable Data

Paper recorded by Signals 4 on 2026-09-04 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07

Category: cs.CL · 自然语言处理 · first seen 2026-09-07

Abstract

Recent advances in wearable sensing enable continuous monitoring of physiological and behavioral signals, yet existing benchmarks rarely evaluate whether AI systems can reason over a real user's longitudinal wearable record. We introduce WearableQA, a benchmark comprising 4,084 10-option multiple-choice questions constructed from the wearable time series, blood biomarkers, and demographics of 200

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#100 most recent of 186 cs.CL papers we have recorded · ↑ newer: Evaluating and Improving Evidence-Grounded Fact-Checking in LLMs via M · ↓ older: Same Trajectory, Contradictory Rewards (ROBORMBENCH): Paraphrase Fragi
Cite this page: WearableQA: A Benchmark for Health Reasoning over Real-World Wearable Data: the #100 most recent of 186 cs.CL papers we have recorded (as of 2026-09-04). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/wearableqa-a-benchmark-for-health-reasoning-over-real-world-wearable-data.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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