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2024 | OriginalPaper | Chapter

MbAbI: A Benchmark Dataset for Malayalam Text Understanding and Reasoning

Authors : K. Reji Rahmath, P. C. Reghu Raj, P. C. Rafeeque

Published in: Proceedings of Third International Conference on Computing and Communication Networks

Publisher: Springer Nature Singapore

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Abstract

This paper proposes a Malayalam Dataset containing 40000 instances, intended to assist the researchers working on Question Answering systems. This data set is the first of its kind. The Facebook bAbI dataset was translated to create this Malayalam bAbI (or, MbAbI) dataset. It comprises 20 different tasks of varying complexity. The tasks include simple supporting facts to complex path finding tasks. We have machine translated these tasks from English to Malayalam and tested the baseline QA models on these datasets. We have obtained state-of-the-art results with MbAbI dataset using deep learning and transformer models. In order to benefit the low-resource Malayalam research community we have made this dataset publicly available.

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previous chapter Improving Network Intrusion Detection with Convolutional Neural Networks and Data Balancing Techniques

next chapter A Novel Approach to Image Restoration and Image Enhancement

https://github.com/rahmathrejik/Question-Answering-Malayalam/tree/MbAbI.

https://research.fb.com/downloads/babi/.

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Title: MbAbI: A Benchmark Dataset for Malayalam Text Understanding and Reasoning
Authors: K. Reji Rahmath
P. C. Reghu Raj
P. C. Rafeeque
Publisher: Springer Nature Singapore
Book: Proceedings of Third International Conference on Computing and Communication Networks
Print ISBN: 978-981-9708-91-8

Electronic ISBN: 978-981-9708-92-5

Copyright Year: 2024
DOI: https://doi.org/10.1007/978-981-97-0892-5_54

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