Datasets › MIMIC-IT

MIMIC-IT

Introduced by Bo Li et al. in Otter: A Multi-Modal Model with In-Context Instruction Tuning5 May 2023 archive 2025-07-28

MultI-Modal In-Context Instruction Tuning (MIMIC-IT) is a dataset for instruction tuning into multi-modal models, motivated by the Flamingo model's upstream interleaved format pretraining dataset. The data sample consists of a queried image-instruction-answer triplet, with the instruction-answer tailored to the image, and context. The context contains a series of image-instruction-answer triplets that contextually correlate with the queried triplet, emulating the relationship between the context and the queried image-text pair found in the MMC4 dataset.

Source: Otter: A Multi-Modal Model with In-Context Instruction Tuning

Image Source: Otter: A Multi-Modal Model with In-Context Instruction Tuning

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 11 papers 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

MIT license

Modalities archive 2025-07-28

Languages archive 2025-07-28

No language tagged.

Variants archive 2025-07-28

  • MIMIC-IT

1 variant name, as the archive lists them.

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