To facilitate the study of profile consistency identification, we create a large-scale human-annotated dataset with over 110K single-turn conversations and.

Sep 21, 2020 · Abstract:Maintaining a consistent attribute profile is crucial for dialogue agents to naturally converse with humans.

We also propose a key-value structure information enriched BERT model to identify the profile consistency, and it gained improvements over strong baselines.

This repository contains resources for EMNLP-20 main conference paper: Profile Consistency Identification for Open-domain Dialogue Agents.

Profile Consistency Identification for Open-domain Dialogue Agents. Haoyu Song, Yan Wang, Wei-Nan Zhang, Zhengyu Zhao, Ting Liu, Xiaojiang Liu. Abstract Paper ...

May 17, 2021 · In this work, we introduce a large-scale annotated dataset to facilitate the study of profile consistency identification in open-domain ...

Profile consistency identification for open-domain dialogue agents. H Song, Y Wang, WN Zhang, Z Zhao, T Liu, X Liu. In Proceedings of EMNLP 2020, 2020. 30, 2020.

Profile Consistency Identification for Open-domain Dialogue Agents. Yan Wang, Haoyu Song, Zhengyu Zhao, Ting Liu, Xiaojiang Liu, Wei-Nan Zhang. 20 Sep 2020. 48.

Maintaining a consistent attribute profile is crucial for dialogue agents to naturally converse with humans. Existing studies on improving attribute consistency ...

KvPI Public. The resources for EMNLP-20 paper 'Profile Consistency Identification for Open-domain Dialogue Agents'. Python 48 5 · RCDG RCDG Public. Source code ...