Dialogue summarization aims to condense the original dialogue into a shorter version
covering salient information, which is a crucial way to reduce dialogue data overload …

The task of resolving repeated objects in natural languages is known as coreference
resolution, and it is an important part of modern natural language processing. It is classified …

Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …

Factual inconsistencies in generated summaries severely limit the practical applications of
abstractive dialogue summarization. Although significant progress has been achieved by …

In this paper, we propose a controllable neural generation framework that can flexibly guide
dialogue summarization with personal named entity planning. The conditional sequences …

Recently, there has been a growing interest in designing text generation systems from a
discourse coherence perspective, eg, modeling the interdependence between sentences …

Longform spoken dialog delivers rich streams of informative content through podcasts,
interviews, debates, and meetings. While production of this medium has grown …

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 …

We introduce DocTime-a novel temporal dependency graph (TDG) parser that takes as input
a text document and produces a temporal dependency graph. It outperforms previous BERT …

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 …