May 8, 2024, 4:43 a.m. | Yonchanok Khaokaew, Kaixin Ji, Thuc Hanh Nguyen, Hiruni Kegalle, Marwah Alaofi, Hao Xue, Flora D. Salim

cs.LG updates on arXiv.org arxiv.org

arXiv:2310.16242v2 Announce Type: replace
Abstract: This paper explores the intersection of technology and sleep pattern comprehension, presenting a cutting-edge two-stage framework that harnesses the power of Large Language Models (LLMs). The primary objective is to deliver precise sleep predictions paired with actionable feedback, addressing the limitations of existing solutions. This innovative approach involves leveraging the GLOBEM dataset alongside synthetic data generated by LLMs. The results highlight significant improvements, underlining the efficacy of merging advanced machine-learning techniques with a user-centric design …

abstract arxiv cs.cl cs.lg edge feedback framework gpt interactive intersection language language models large language large language models limitations llms paper pattern power predictions presenting quality sleep solutions stage technology type

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