Answering questions by learning to rank - Learning to rank by answering questions

George Sebastian Pirtoaca, Traian Rebedea, Stefan Ruseti

Abstract
Answering multiple-choice questions in a setting in which no supporting documents are explicitly provided continues to stand as a core problem in natural language processing. The contribution of this article is two-fold. First, it describes a method which can be used to semantically rank documents extracted from Wikipedia or similar natural language corpora. Second, we propose a model employing the semantic ranking that holds the first place in two of the most popular leaderboards for answering multiple-choice questions: ARC Easy and Challenge. To achieve this, we introduce a self-attention based neural network that latently learns to rank documents by their importance related to a given question, whilst optimizing the objective of predicting the correct answer. These documents are considered relevant contexts for the underlying question. We have published the ranked documents so that they can be used off-the-shelf to improve downstream decision models.
Anthology ID:
D19-1256
Volume:
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)
Month:
November
Year:
2019
Address:
Hong Kong, China
Editors:
Kentaro Inui, Jing Jiang, Vincent Ng, Xiaojun Wan
Venues:
EMNLP | IJCNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
2531–2540
Language:
URL:
https://aclanthology.org/D19-1256
DOI:
10.18653/v1/D19-1256
Bibkey:
Cite (ACL):
George Sebastian Pirtoaca, Traian Rebedea, and Stefan Ruseti. 2019. Answering questions by learning to rank - Learning to rank by answering questions. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), pages 2531–2540, Hong Kong, China. Association for Computational Linguistics.
Cite (Informal):
Answering questions by learning to rank - Learning to rank by answering questions (Pirtoaca et al., EMNLP-IJCNLP 2019)
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https://preview.aclanthology.org/ingest-acl-2023-videos/D19-1256.pdf
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