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 …

In this paper, we propose to enhance the pair-wise aspect and opinion terms extraction
(PAOTE) task by incorporating rich syntactic knowledge. We first build a syntax fusion …

Medical images are widely used in clinical decision-making, where writing radiology reports
is a potential application that can be enhanced by automatic solutions to alleviate …

Unified opinion role labeling (ORL) aims to detect all possible opinion structures of'opinion-
holder-target'in one shot, given a text. The existing transition-based unified method …

The pre-training of text encoders normally processes text as a sequence of tokens
corresponding to small text units, such as word pieces in English and characters in Chinese …

Neural abstractive summarization models are prone to generate summaries which are
factually inconsistent with their source documents. Previous work has introduced the task of …

Named entity recognition (NER) isa preliminary task in natural language processing (NLP).
Recognizing Chinese named entities from unstructured texts is challenging due to the lack …

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 …

Recently, Flat-LAttice Transformer (FLAT) has achieved great success in Chinese Named
Entity Recognition (NER). FLAT performs lexical enhancement by constructing flat lattices …