mlsanityData to 14 Oct 2026

CompMix: A Benchmark for Heterogeneous Question Answering

arXiv 2306.12235 ↗First posted 21 Jun 2023cs.IRcited by 12

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Abstract (arXiv)

Fact-centric question answering (QA) often requires access to multiple, heterogeneous, information sources. By jointly considering several sources like a knowledge base (KB), a text collection, and tables from the web, QA systems can enhance their answer coverage and confidence. However, existing QA benchmarks are mostly constructed with a single source of knowledge in mind. This limits capabilities of these benchmarks to fairly evaluate QA systems that can tap into more than one information repository. To bridge this gap, we release CompMix, a crowdsourced QA benchmark which naturally demands the integration of a mixture of input sources. CompMix has a total of 9,410 questions, and features several complex intents like joins and temporal conditions. Evaluation of a range of QA systems on CompMix highlights the need for further research on leveraging information from heterogeneous sources.

Key facts. Cited by 12 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Jun 2023.

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Citing papers per year: 2023: 1; 2024: 5; 2025: 4; 2026: 2.

12 papers.