Datasets › CompMix-IR

CompMix-IR

Introduced by Dehai Min et al. in UniHGKR: Unified Instruction-aware Heterogeneous Knowledge Retrievers26 Oct 2024 archive 2025-07-28

CompMix-IR Dataset Overview:

Characteristics: CompMix-IR is a heterogeneous knowledge retrieval benchmark dataset, featuring four knowledge types (text, knowledge graphs, tables, and infoboxes), 9,400+ QA pairs, and a corpus of 10 million entries. It supports two retrieval scenarios: retrieving across all knowledge types or retrieving specific types based on user instructions.

Motivation: It addresses the limitations of existing benchmarks by providing a more comprehensive and realistic dataset that reflects real-world retrieval needs with diverse knowledge sources and user intents.

Potential Use Cases: Ideal for developing and evaluating heterogeneous IR models, instruction-aware retrieval systems, and open-domain QA systems. It can also be used for benchmarking, cross-domain IR research, and enhancing the adaptability and robustness of retrieval models.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 1 paper for it but never published that list.

Dataset loaders archive 2025-07-28

No loader listed in the archive.

Tasks archive 2025-07-28

License archive 2025-07-28

cc-by-4.0

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • CompMix-IR

1 variant name, as the archive lists them.

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