2025
ACL
ACL 2025
KR Labs at ArchEHR-QA 2025: A Verbatim Approach for Evidence-Based Question Answering
Abstract
AbstractWe present a lightweight, domain‐agnostic verbatim pipeline for evidence‐grounded question answering. Our pipeline operates in two steps: first, a sentence-level extractor flags relevant note sentences using either zero-shot LLM prompts or supervised ModernBERT classifiers. Next, an LLM drafts a question-specific template, which is filled verbatim with sentences from the extraction step. This prevents hallucinations and ensures traceability. In the ArchEHR‐QA 2025 shared task, our system scored 42.01%, ranking top‐10 in core metrics and outperforming the organiser’s 70B‐parameter Llama‐3.3 baseline. We publicly release our code and inference scripts under an MIT license.
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Keyword Pioneer
— evidence-based question answering
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Cross-Pollinator
— Artificial Intelligence, Machine Learning, Natural Language Processing
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Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning and Healthcare & Medicine and Machine Learning and Natural Language Processing
Authors
Topics
Machine Learning > Learning Types > Zero-Shot Learning
Natural Language Processing > Applications > Machine Reading Comprehension
Natural Language Processing > Applications > Question Answering
Healthcare & Medicine > Clinical > Clinical NLP
Healthcare & Medicine > Clinical > Medical AI
Deep Learning > Learning Types > Zero-Shot Learning
Artificial Intelligence > Core AI > Natural Language Processing