Mind the Gap! Injecting Commonsense Knowledge for Abstractive Dialogue Summarization

• URL: http://arxiv.org/abs/2209.00930v1
• Date: Fri, 2 Sep 2022 10:08:28 GMT
• Title: Mind the Gap! Injecting Commonsense Knowledge for Abstractive Dialogue Summarization
• Authors: Seungone Kim, Se June Joo, Hyungjoo Chae, Chaehyeong Kim, Seung-won Hwang, Jinyoung Yeo
• Abstract summary: We present SICK, a framework that uses commonsense inferences as additional context. With injected commonsense knowledge, our framework generates more informative and consistent summaries than existing methods.
• Score: 13.863545975204019
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: In this paper, we propose to leverage the unique characteristics of dialogues sharing commonsense knowledge across participants, to resolve the difficulties in summarizing them. We present SICK, a framework that uses commonsense inferences as additional context. Compared to previous work that solely relies on the input dialogue, SICK uses an external knowledge model to generate a rich set of commonsense inferences and selects the most probable one with a similarity-based selection method. Built upon SICK, SICK++ utilizes commonsense as supervision, where the task of generating commonsense inferences is added upon summarizing the dialogue in a multi-task learning setting. Experimental results show that with injected commonsense knowledge, our framework generates more informative and consistent summaries than existing methods.

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