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
- 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)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.coling-main.247.pdf
- Data
- CoQA, QuAC