Coreference-Aware Dialogue Summarization
Summarizing conversations via neural approaches has been gaining research traction lately, yet it is still challenging to obtain practical solutions. Examples of such challenges include unstructured information exchange in dialogues, informal interactions between speakers, and dynamic role changes of speakers as the dialogue evolves. Many of such challenges result in complex coreference links. Therefore, in this work, we investigate different approaches to explicitly incorporate coreference information in neural abstractive dialogue summarization models to tackle the aforementioned challenges. Experimental results show that the proposed approaches achieve state-of-the-art performance, implying it is useful to utilize coreference information in dialogue summarization. Evaluation results on factual correctness suggest such coreference-aware models are better at tracing the information flow among interlocutors and associating accurate status/actions with the corresponding interlocutors and person mentions.
Code (1)
Tasks
Abstractive Dialogue SummarizationSimilar Papers 제목 키워드 기반
Picking the Underused Heads: A Network Pruning Perspective of Attention Head Selection for Fusing Dialogue Coreference Information
The Transformer-based models with the multi-head self-attention mechanism are widely used in natural language processing, and provide state-of-the-art results. While the pre-trained language backbones are shown to implic…
Network PruningDialogSum Challenge: Summarizing Real-Life Scenario Dialogues
We propose a shared task on summarizing real-life scenario dialogues, DialogSum Challenge, to encourage researchers to address challenges in dialogue summarization, which has been less studied by the summarization commun…
Common Sense ReasoningRepresentation LearningDialogSum: A Real-Life Scenario Dialogue Summarization Dataset
Proposal of large-scale datasets has facilitated research on deep neural models for news summarization. Deep learning can also be potentially useful for spoken dialogue summarization, which can benefit a range of real-li…
Abstractive Dialogue SummarizationCommon Sense ReasoningManagementRepresentation Learning+1He Said, She Said: Style Transfer for Shifting the Perspective of Dialogues
In this work, we define a new style transfer task: perspective shift, which reframes a dialogue from informal first person to a formal third person rephrasing of the text. This task requires challenging coreference resol…
coreference-resolutionCoreference ResolutionNews SummarizationStyle TransferWhat You See is What You Get: Visual Pronoun Coreference Resolution in Dialogues
Grounding a pronoun to a visual object it refers to requires complex reasoning from various information sources, especially in conversational scenarios. For example, when people in a conversation talk about something all…
coreference-resolutionCoreference ResolutionNatural Language Understanding