Datasets › R1-Onevision

R1-Onevision

Introduced by Yi Yang* et al. in R1-Onevision:An Open-Source Multimodal Large Language Model Capable of Deep Reasoning24 Feb 2025 archive 2025-07-28

The R1-Onevision dataset is a meticulously crafted resource designed to empower models with advanced multimodal reasoning capabilities. Aimed at bridging the gap between visual and textual understanding, this dataset provides rich, context-aware reasoning tasks across diverse domains, including natural scenes, science, mathematical problems, OCR-based content, and complex charts.

It combines high-quality data from LLaVA-OneVision with domain-specific datasets, each carefully selected and filtered to provide a solid foundation for complex visual reasoning tasks. With a focus on enabling deep reasoning and accurate model predictions, R1-Onevision equips models to handle a variety of visual and textual inputs, tackling intricate reasoning challenges with precision.

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

apache-2.0

Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • R1-Onevision

1 variant name, as the archive lists them.

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