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20182026
most citedMaking Retrieval-Augmented Language Models Robust to Irrelevant Context

21 citations · 51 across the 12 of their papers we have counts for

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2 papers · 1 filter

cs.IR2026

SAGE: Structure Aware Graph Expansion for Retrieval of Heterogeneous Data

Prasham Titiya, Rohit Khoja, Tomer Wolfson +2

Retrieval-augmented question answering over heterogeneous corpora requires connected evidence across text, tables, and graph nodes. While entity-level knowledge graphs support stru…

cs.CL2026

Decomposed Prompting Does Not Fix Knowledge Gaps, But Helps Models Say "I Don't Know"

Dhruv Madhwal, Lyuxin David Zhang, Dan Roth +2

Large language models often struggle to recognize their knowledge limits in closed-book question answering, leading to confident hallucinations. While decomposed prompting is typic…