Conversational Machine Comprehension: a Literature Review

Somil Gupta, Bhanu Pratap Singh Rawat, Hong Yu


Abstract
Conversational Machine Comprehension (CMC), a research track in conversational AI, expects the machine to understand an open-domain natural language text and thereafter engage in a multi-turn conversation to answer questions related to the text. While most of the research in Machine Reading Comprehension (MRC) revolves around single-turn question answering (QA), multi-turn CMC has recently gained prominence, thanks to the advancement in natural language understanding via neural language models such as BERT and the introduction of large-scale conversational datasets such as CoQA and QuAC. The rise in interest has, however, led to a flurry of concurrent publications, each with a different yet structurally similar modeling approach and an inconsistent view of the surrounding literature. With the volume of model submissions to conversational datasets increasing every year, there exists a need to consolidate the scattered knowledge in this domain to streamline future research. This literature review attempts at providing a holistic overview of CMC with an emphasis on the common trends across recently published models, specifically in their approach to tackling conversational history. The review synthesizes a generic framework for CMC models while highlighting the differences in recent approaches and intends to serve as a compendium of CMC for future researchers.
Anthology ID:
2020.coling-main.247
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Editors:
Donia Scott, Nuria Bel, Chengqing Zong
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
2739–2753
Language:
URL:
https://aclanthology.org/2020.coling-main.247
DOI:
10.18653/v1/2020.coling-main.247
Bibkey:
Cite (ACL):
Somil Gupta, Bhanu Pratap Singh Rawat, and Hong Yu. 2020. Conversational Machine Comprehension: a Literature Review. In Proceedings of the 28th International Conference on Computational Linguistics, pages 2739–2753, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
Conversational Machine Comprehension: a Literature Review (Gupta et al., COLING 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.coling-main.247.pdf
Data
CoQAQuAC