The NOESIS II challenge, as the Track 2 of the 8th Dialogue System Technology Challenges (DSTC 8), is the extension of DSTC 7. This track incorporates new elements that are vital for the creation of a deployed task-oriented dialogue system. This paper describes our systems that are evaluated on all subtasks under this challenge. We study the problem of employing pre-trained attention-based network for multi-turn dialogue systems. Meanwhile, several adaptation methods are proposed to adapt the pre-trained language models for multi-turn dialogue systems, in order to keep the intrinsic property of dialogue systems. In the released evaluation results of Track 2 of DSTC 8, our proposed models ranked fourth in subtask 1, third in subtask 2, and first in subtask 3 and subtask 4 respectively.
@article{arxiv.2004.01940,
title = {Pre-Trained and Attention-Based Neural Networks for Building Noetic Task-Oriented Dialogue Systems},
author = {Jia-Chen Gu and Tianda Li and Quan Liu and Xiaodan Zhu and Zhen-Hua Ling and Yu-Ping Ruan},
journal= {arXiv preprint arXiv:2004.01940},
year = {2020}
}