GitHub - nttmdlab-nlp/VisualMRC: VisualMRC: Machine Reading Comprehension on Document Images (AAAI2021) (original) (raw)

VisualMRC

VisualMRC is a visual machine reading comprehension dataset that proposes a task: given a question and a document image, a model produces an abstractive answer.

You can find more details, analyses, and baseline results in our paper. You can cite it as follows:

@inproceedings{VisualMRC2021, author = {Ryota Tanaka and Kyosuke Nishida and Sen Yoshida}, title = {VisualMRC: Machine Reading Comprehension on Document Images}, booktitle = {AAAI}, year = {2021} }

📢 News

• [2025.03.27] Our VisualMRC dataset is available on 🤗HuggingFace.

Download

• 🤗VisualMRC

Statistics

• 10,197 images
• 30,562 QA pairs
• 10.53 average question tokens (tokenizing with NLTK tokenizer)
• 9.53 average answer tokens (tokenizing wit NLTK tokenizer)
• 151.46 average OCR tokens (tokenizing with NLTK tokenizer)