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WaltonFuture/MMR1-in-context-synthesizing

Dataset

This dataset is designed for unsupervised post-training of Multi-Modal Large Language Models (MLLMs) focusing on enhancing reasoning capabilities. It contains image-problem-answer triplets, where the problem requires multimodal reasoning to derive the correct answer from the provided image. The dataset is intended for use with the MM-UPT framework described in the accompanying paper.

0

5 commits

1 linked in READMEs

updated Jun 2, 2025

See the code

README

This dataset is designed for unsupervised post-training of Multi-Modal Large Language Models (MLLMs) focusing on enhancing reasoning capabilities. It contains image-problem-answer triplets, where the problem requires multimodal reasoning to derive the correct answer from the provided image. The dataset is intended for use with the MM-UPT framework described in the accompanying paper.

multimodal
post-training
reasoning
unsupervised-learning

Contributors

WaltonFuture

4 commits

nielsr

1 commits

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WaltonFuture/MMR1-in-context-synthesizing

Dataset

This dataset is designed for unsupervised post-training of Multi-Modal Large Language Models (MLLMs) focusing on enhancing reasoning capabilities. It contains image-problem-answer triplets, where the problem requires multimodal reasoning to derive the correct answer from the provided image. The dataset is intended for use with the MM-UPT framework described in the accompanying paper.

0

5 commits

1 linked in READMEs

updated Jun 2, 2025

See the code

README

This dataset is designed for unsupervised post-training of Multi-Modal Large Language Models (MLLMs) focusing on enhancing reasoning capabilities. It contains image-problem-answer triplets, where the problem requires multimodal reasoning to derive the correct answer from the provided image. The dataset is intended for use with the MM-UPT framework described in the accompanying paper.

multimodal
post-training
reasoning
unsupervised-learning

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Contributors

WaltonFuture

4 commits

nielsr

1 commits