Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading

Yifan Gao, Chien-Sheng Wu, Shafiq Joty, Caiming Xiong, Richard Socher, Irwin King, Michael Lyu, Steven C.H. Hoi


Abstract
The goal of conversational machine reading is to answer user questions given a knowledge base text which may require asking clarification questions. Existing approaches are limited in their decision making due to struggles in extracting question-related rules and reasoning about them. In this paper, we present a new framework of conversational machine reading that comprises a novel Explicit Memory Tracker (EMT) to track whether conditions listed in the rule text have already been satisfied to make a decision. Moreover, our framework generates clarification questions by adopting a coarse-to-fine reasoning strategy, utilizing sentence-level entailment scores to weight token-level distributions. On the ShARC benchmark (blind, held-out) testset, EMT achieves new state-of-the-art results of 74.6% micro-averaged decision accuracy and 49.5 BLEU4. We also show that EMT is more interpretable by visualizing the entailment-oriented reasoning process as the conversation flows. Code and models are released at https://github.com/Yifan-Gao/explicit_memory_tracker.
Anthology ID:
2020.acl-main.88
Volume:
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
Month:
July
Year:
2020
Address:
Online
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
935–945
Language:
URL:
https://aclanthology.org/2020.acl-main.88
DOI:
10.18653/v1/2020.acl-main.88
Bibkey:
Cite (ACL):
Yifan Gao, Chien-Sheng Wu, Shafiq Joty, Caiming Xiong, Richard Socher, Irwin King, Michael Lyu, and Steven C.H. Hoi. 2020. Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 935–945, Online. Association for Computational Linguistics.
Cite (Informal):
Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading (Gao et al., ACL 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.acl-main.88.pdf
Video:
 http://slideslive.com/38928988
Code
 Yifan-Gao/explicit_memory_tracker