Abstractive dialogue summarization is the task of distilling conversations into informative
and concise summaries. Although focused reviews have been conducted on this topic, there …

Abstractive dialogue summarization generates a concise and fluent summary covering the
salient information in a dialogue among two or more interlocutors. It has attracted significant …

Dialogue, the most fundamental and specially privileged arena of language, gains
increasing ubiquity across the Web in recent years. Quickly going through the long dialogue …

Applications that could benefit from automatic understanding of human-human
conversations often come with challenges associated with private information in real-world …

Dialogue summarization is abstractive in nature, making it suffer from factual errors. The
factual correctness of summaries has the highest priority before practical applications. Many …

Conventional dialogue summarization methods directly generate summaries and do not
consider user's specific interests. This poses challenges in cases where the users are more …

The most advanced abstractive dialogue summarizers lack generalization ability on new
domains and the existing researches for domain adaptation in summarization generally rely …

To mitigate the lack of diverse dialogue summarization datasets in academia, we present
methods to utilize non-dialogue summarization data for enhancing dialogue summarization …

Information overloading requires the need for summarizers to extract salient information from
the text. Currently, there is an overload of dialogue data due to the rise of virtual …

Task-oriented dialogue systems (TOD) are blossoming with the advances in pre-trained
language models (PrLM). Recently, research on PrLM-based multi-domain TOD has arisen …