Papers by Enes Kutay Isgorur

1 papers
T2-RAGBench: Text-and-Table Benchmark for Evaluating Retrieval-Augmented Generation (2026.eacl-long)

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Challenge: Existing QA datasets containing text-and-table data typically contain context-dependent questions, which may yield multiple correct answers depending on the provided context.
Approach: They propose a benchmark to evaluate RAG methods on text-and-table data.
Outcome: The proposed method evaluates RAG methods on real-world text-and-table data.

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