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Razreshili at ArchEHR-QA 2026: Evidence Alignment via LLM Prompting and Cross-Encoder Fine-tuning
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Razreshili at ArchEHR-QA 2026: Evidence Alignment via LLM Prompting and Cross-Encoder Fine-tuning
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. 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.
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