TAT-DQA is a large-scale Document VQA dataset, which is constructed by extending the TAT-QA. It aims to stimulate the progress of QA research over more complex and realistic visually-rich documents with rich tabular and textual content, especially those requiring numerical reasoning.
The unique features of TAT-DQA include:
The documents in TAT-DQA dataset are sampled from real-world high-quality financial… See the full description on the dataset page:
https://huggingface.co/datasets/next-tat/TAT-DQA.
