QASPER is a dataset for question answering on scientific research papers. It consists of 5,049 questions over 1,585 Natural Language Processing papers. Each question is written by an NLP practitioner who read only the title and abstract of the corresponding paper, and the question seeks information present in the full text. The questions are then answered by a separate set of NLP practitioners who also provide supporting evidence to answers.
Variants: QASPER
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Question Answering | Longformer Encoder Decoder (base) | A Dataset of Information-Seeking Questions … | 2021-05-07 |
Recent papers with results on this dataset: