OASIS：基于量规与大语言模型的多模态评估平台
原标题：OASIS: A Rubric-Based Multimodal Assessment Platform Using Large Language Models
AI 摘要
UT Southwestern 等机构的研究者发布 OASIS，一个基于评分量规（rubric）的多模态评估平台，可用大语言模型对视频、音频和文本进行结构化打分。平台提供命令行工具与集成栈，支持托管 API 或通过 Ollama、vLLM 等自托管开源模型，并具备量规版本管理、执行溯源和人工复核状态。该系统自 2023 年秋季起在 UT Southwestern 医学中心生产使用，已处理超过 7000 次评估，架构不限于医学教育领域。
正文节选
captionstableheading OASIS: A Rubric-Based Multimodal Assessment Platform Using Large Language Models Abstract OASIS (Open Assessment and Scoring Infrastructure Stack) is a systems platform for rubric-based grading of video, audio, and text with large language models. Scoring one artifact with an LLM is straightforward; deploying assessment at scale requires encounter management, rubric versioning, modality-aware execution, provenance capture, and human review. OASIS pairs a standalone command-l