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Alleviating Attention Bias for Visual-Informed Text Generation

Training Dataset for Allegator finetuning.

The dataset consists of a subset of LLaVA-Instruct-150k and a subset of Flickr30k, with 99,883 and 31,783 samples from each, respectively.

In detail, LLaVA-Instruct-150K contains 158k language-image instruction following samples, including 58k conversations, 23k descriptions, and 77k complex, 182 reasoning. We augment LLaVA-Instruct-150K with Flickr30K, which has relatively short captions, to enrich visual and textual diversity.

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