Multi-document summarization (MDS) is an effective tool for information aggregation that
generates an informative and concise summary from a cluster of topic-related documents …

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 …

Medical imaging plays a significant role in clinical practice of medical diagnosis, where the
text reports of the images are essential in understanding them and facilitating later …

Syntactic information, especially dependency trees, has been widely used by existing
studies to improve relation extraction with better semantic guidance for analyzing the context …

Existing conversational recommendation (CR) systems usually suffer from insufficient item
information when conducted on short dialogue history and unfamiliar items. Incorporating …

Background Comprehensive session summaries enable effective continuity in mental health
counseling, facilitating informed therapy planning. However, manual summarization …

Dialogue summarization is an important task that requires to generate highlights for a
conversation from different aspects (eg, content of various speakers). While several studies …

Relation extraction is an important task in information extraction and retrieval that aims to
extract relations among the given entities from running texts. To achieve a good …

Aspect-level sentiment analysis (ASA) has received much attention in recent years. Most
existing approaches tried to leverage syntactic information, such as the dependency parsing …

Radiology report generation (RRG) aims to automatically generate free-text descriptions
from clinical radiographs, eg, chest X-Ray images. RRG plays an essential role in promoting …