most citedTime to Transfer: Predicting and Evaluating Machine-Human Chatting Handoff

2 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2021

Adjacency List Oriented Relational Fact Extraction via Adaptive Multi-task Learning

Fubang Zhao, Zhuoren Jiang, Yangyang Kang +2

Relational fact extraction aims to extract semantic triplets from unstructured text. In this work, we show that all of the relational fact extraction models can be organized accord…

cs.CL20202 cited

Time to Transfer: Predicting and Evaluating Machine-Human Chatting Handoff

Jiawei Liu, Zhe Gao, Yangyang Kang +5

Is chatbot able to completely replace the human agent? The short answer could be - "it depends...". For some challenging cases, e.g., dialogue's topical spectrum spreads beyond the…

cs.CL2020

Topic-Oriented Spoken Dialogue Summarization for Customer Service with Saliency-Aware Topic Modeling

Yicheng Zou, Lujun Zhao, Yangyang Kang +7

In a customer service system, dialogue summarization can boost service efficiency by automatically creating summaries for long spoken dialogues in which customers and agents try to…

cs.CL2020

Unsupervised Summarization for Chat Logs with Topic-Oriented Ranking and Context-Aware Auto-Encoders

Yicheng Zou, Jun Lin, Lujun Zhao +6

Automatic chat summarization can help people quickly grasp important information from numerous chat messages. Unlike conventional documents, chat logs usually have fragmented and e…

cs.CL2020

Read Beyond the Lines: Understanding the Implied Textual Meaning via a Skim and Intensive Reading Model

Guoxiu He, Zhe Gao, Zhuoren Jiang +4

The nonliteral interpretation of a text is hard to be understood by machine models due to its high context-sensitivity and heavy usage of figurative language. In this study, inspir…