Papers with binary classification of irrelevant passages

1 papers
The Distracting Effect: Understanding Irrelevant Passages in RAG (2025.acl-long)

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Challenge: Existing methods to detect and use hard distracting passages in RAG can cause problems . retrieved passages contain irrelevant but semantically related information that may mislead the LLM .
Approach: They propose a method to identify and use hard distracting passages to improve RAG . they find that adding retrieved passages is found to ground the LLM response .
Outcome: The proposed method achieves up to 7.5% increase in answering accuracy compared to fine-tuned datasets.

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