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README.md

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 # Altogether-FT
 
-(EMNLP 2024) Altogether-FT is an annotated fine-tuning dataset that re-aligns alt-texts into dense captions. It powers altogether captioner to transform Internet-scale quality alt-texts into dense captions, instead of captioning from scratch as naive captions (e.g, "a dog is walking in the park.").
-It contains 15448 examples for training and 500 examples for evaluation from WIT and DataComp.
+(EMNLP 2024) Altogether-FT is a dataset that transforms/re-aligns Internet-scale alt-texts into dense captions. It does not caption images from scratch and generate naive captions that provide little value to an average user (e.g., "a dog is walking in the park" offer minimal utility to users not blind). Instead, it complements and completes alt-texts into dense captions, while preserving supervisions in alt-texts by expert human/agents around the world (that describe the images an average annotators do not understand).  
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+It contains 15448 examples for training and 500 examples for evaluation from [WIT](https://arxiv.org/abs/2103.01913) and [DataComp](https://arxiv.org/abs/2304.14108).  
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+We use this re-aligned captions to train MetaCLIPv2.  
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 ![Altogether](altogether.png)