Title
TIAGE - A Benchmark for Topic-Shift Aware Dialog Modeling.
Abstract
Human conversations naturally evolve around different topics and fluently move between them. In research on dialog systems, the ability to actively and smoothly transition to new topics is often ignored. In this paper we introduce TIAGE, a new topic-shift aware dialog benchmark constructed utilizing human annotations on topic shifts. Based on TIAGE, we introduce three tasks to investigate different scenarios of topic-shift modeling in dialog settings: topic-shift detection, topic-shift triggered response generation and topic-aware dialog generation. Experiments on these tasks show that the topic-shift signals in TIAGE are useful for topic-shift response generation. On the other hand, dialog systems still struggle to decide when to change topic. This indicates further research is needed in topic-shift aware dialog modeling.
Year
Venue
DocType
2021
EMNLP
Conference
Volume
Citations 
PageRank 
2021.findings-emnlp
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Huiyuan Xie100.34
Zhenghao Liu200.34
Chen-Yan Xiong340530.82
Zhiyuan Liu42037123.68
Ann Copestake500.34