arXiv · cs.AI · Viju Sudhi, Giulio Billi, Andreea Scrob, Regina Stodden, Philipp Cimiano · 9 小时前模型评分33
Tug of Watts：大语言模型在医疗问答任务中的能耗与准确率权衡研究
Tug of Watts: A study on the Energy - Accuracy Trade-off of Large Language Models on Medical Question Answering Tasks
导读
一项研究考察了 OpenMedical-LLM 榜单上 3 个模型家族共 13 个大语言模型（LLM，Large Language Model）在医疗问答任务中的能耗与准确率权衡，参数量覆盖 270M 至 14B。研究指出，单独报告能耗和准确率指标不足以评估权衡，还需系统构建并解读联合权衡指标，帮助从业者选用更高效的模型。
分类置信度
中 · 待人工复核
- 只有单一媒体来源，需要人工复核。
来源级别：媒体与个人
应用领域：医疗与生命科学
事件类型：研究发布
证据摘录
- “In this study, we demonstrate how practitioners can estimate energy consumption and arrive at reliable emission estimates for medical QA tasks available in the OpenMedical-LLM leaderboard by investigating 13 LLMs from 3 model families ranging from 270M to 14B parameters.”
来源：arXiv · cs.AI · arxiv.org