Article

Benchmarking System Configurations for Rubric-Constrained Personalized Exercise Planning

2026-08-20

Abstract excerpt

Agentic Large Language Model (LLM) systems that turn wearable streams into daily workout plans need matched-backbone tests with shared post-processing. We compare four system configurations for daily workout generation—Baseline-LLM (raw chart, no precompute), Single Agent, Multi-Agent, and ReAct—on N = 50 matched user-days (5 users × 10 days) from longitudinal wearable data. Four blind LLM judges (claude-opus-4-5,...

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Literature Corpus work: 4b70988b-b846-55fd-a240-a9290898f689
DOI: 10.20944/preprints202608.1437.v1

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