Papers with ICR

3 papers
ICR: Iterative Clarification and Rewriting for Conversational Search (2025.emnlp-main)

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Challenge: Conversational Query Rewriting (CQR) is a key step in conversational question answering . it aims to rewrite vague queries into de-contextualized queries, thereby promoting conversational search.
Approach: They propose an iterative rewriting scheme that pivots on clarification questions . they propose to rewrite queries into de-contextualized queries to promote conversational search .
Outcome: The proposed framework improves retrieval performance on two popular datasets.
Can’t Remember Details in Long Documents? You Need Some R&R (2024.findings-emnlp)

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Challenge: Long-context large language models miss important information in the middle of context documents . a recent study shows that LLMs can be used for document-based QA tasks .
Approach: They propose a prompt-based method called *reprompting* and *in-context retrieval* to alleviate this effect in document-based QA.
Outcome: The proposed method improves QA accuracy on documents up to 80k tokens in length.
Strong Reasoning Isn’t Enough: Evaluating Evidence Elicitation in Interactive Diagnosis (2026.findings-acl)

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Challenge: Existing evaluations of medical consultation are static or outcome-centric, neglecting the evidence-gathering process.
Approach: They propose an interactive evaluation framework that explicitly models the consultation process using a simulated patient and a measurement module grounded in atomic evidences.
Outcome: The proposed evaluation framework outperforms baseline evaluation methods in medical consultation settings.

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