Textbook Question Answering
The TextbookQuestionAnswering (TQA) dataset is drawn from middle school science curricula. It consists of 1,076 lessons from Life Science, Earth Science and Physical Science textbooks. This includes 26,260 questions, including 12,567 that have an accompanying diagram.
The TQA dataset encourages work on the task of Multi-Modal Machine Comprehension (M3C) task. The M3C task builds on the popular Visual Question Answering (VQA) and Machine Comprehension (MC) paradigms by framing question answering as a machine comprehension task, where the context needed to answer questions is provided and composed of both text and images. The dataset constructed to showcase this task has been built from a middle school science curriculum that pairs a given question to a limited span of knowledge needed to answer it.
Source: Allen Institute for AI
Variants: TQA
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Open-Domain Question Answering | BPR (linear scan; l=1000) | Efficient Passage Retrieval with Hashing … | 2021-06-02 |
| Open-Domain Question Answering | UniK-QA | UniK-QA: Unified Representations of Structured … | 2020-12-29 |
Recent papers with results on this dataset: