ISAAQ - Mastering Textbook Questions with Pre-trained Transformers and Bottom-Up and Top-Down Attention

Jose Manuel Gomez-Perez, Raúl Ortega


Abstract
Textbook Question Answering is a complex task in the intersection of Machine Comprehension and Visual Question Answering that requires reasoning with multimodal information from text and diagrams. For the first time, this paper taps on the potential of transformer language models and bottom-up and top-down attention to tackle the language and visual understanding challenges this task entails. Rather than training a language-visual transformer from scratch we rely on pre-trained transformers, fine-tuning and ensembling. We add bottom-up and top-down attention to identify regions of interest corresponding to diagram constituents and their relationships, improving the selection of relevant visual information for each question and answer options. Our system ISAAQ reports unprecedented success in all TQA question types, with accuracies of 81.36%, 71.11% and 55.12% on true/false, text-only and diagram multiple choice questions. ISAAQ also demonstrates its broad applicability, obtaining state-of-the-art results in other demanding datasets.
Anthology ID:
2020.emnlp-main.441
Volume:
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Month:
November
Year:
2020
Address:
Online
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
5469–5479
Language:
URL:
https://aclanthology.org/2020.emnlp-main.441
DOI:
10.18653/v1/2020.emnlp-main.441
Bibkey:
Cite (ACL):
Jose Manuel Gomez-Perez and Raúl Ortega. 2020. ISAAQ - Mastering Textbook Questions with Pre-trained Transformers and Bottom-Up and Top-Down Attention. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 5469–5479, Online. Association for Computational Linguistics.
Cite (Informal):
ISAAQ - Mastering Textbook Questions with Pre-trained Transformers and Bottom-Up and Top-Down Attention (Gomez-Perez & Ortega, EMNLP 2020)
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PDF:
https://aclanthology.org/2020.emnlp-main.441.pdf
Video:
 https://slideslive.com/38939054