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Pierce Chuang

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Articles

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

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By Ji Soo Lee, Xilun Chen, Pierce Chuang
| huggingface.co
Published on Sep 4 · Submitted by Ji Soo Lee on Sep 10 · Meta Abstract 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. 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.
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Computer Science > Computation and Language

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By Ji Soo, Xilun Chen, Pierce Chuang
| arXiv
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 real users, each with up to 500 days of daily measurements.
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Now It Sounds Like You: Learning Personalized Vocabulary On Device

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By Ashish Shenoy, Pierce Chuang, John Nguyen
| arXiv
arXiv:2305.03584 (cs) [Submitted on 5 May 2023 (v1), last revised 13 Feb 2024 (this version, v3)] Download PDF HTML (experimental) Comments: Subjects: Computation and Language (cs.CL); Artificial Intelligence (cs.AI) Cite as: arXiv:2305.03584 [cs.CL] (or arXiv:2305.03584v3 [cs.CL] for this version) https://doi.org/10.48550/arXiv.2305.03584 Submission history From: Ashish Shenoy [ view email] [v1] Fri, 5 May 2023 14:44:20 UTC (14,102 KB) [v2] Thu, 5 Oct 2023 20:45:46 UTC (7,050 KB) [v3] Tue,...
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