CLJul 31, 2024

A Course Shared Task on Evaluating LLM Output for Clinical Questions

arXiv:2408.00122v126 citationsh-index: 16
Originality Synthesis-oriented
AI Analysis

This work addresses the need for practical educational tools in NLP for instructors, though it is incremental as it builds on existing shared task formats for teaching purposes.

The paper presents a shared task organized in a university course to evaluate Large Language Models (LLMs) in generating harmful answers to clinical questions, reporting feedback from students and aiming to assist instructors in NLP course design.

This paper presents a shared task that we organized at the Foundations of Language Technology (FoLT) course in 2023/2024 at the Technical University of Darmstadt, which focuses on evaluating the output of Large Language Models (LLMs) in generating harmful answers to health-related clinical questions. We describe the task design considerations and report the feedback we received from the students. We expect the task and the findings reported in this paper to be relevant for instructors teaching natural language processing (NLP) and designing course assignments.

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The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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