Razreshili at ArchEHR-QA 2026: Evidence Alignment via LLM Prompting and Cross-Encoder Fine-tuning
Year: 2026
Type: conference-paper
Abstract: We describe our system for Subtask 4 (Evidence Alignment) of the ArchEHR-QA 2026 shared task, which requires aligning each sentence of a clinician-authored answer to the supporting sentence(s) in a clinical note excerpt derived from MIMIC (Johnson et al., 2016).The task is challenging due to many-to-many alignment structure, answer sentences with no note support, and the semantic gap between clinical note language and answer paraphrases.We explore two approaches: few-shot chain-of-thought prompting with Qwen2.5-7B-Instruct and LoRA fine-tuning of a cross-encoder with combined InfoNCE and BCE loss.Our best system achieves a micro F1 of 67.93 on the test set.
Author: Arina Zemchyk
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7166506679