Datasets › CompMix-IR
CompMix-IR
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.
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections