Biomedical information extraction (BioIE) is an important task. The aim is to analyze
biomedical texts and extract structured information such as named entities and semantic …

To accelerate biomedical research process, deep-learning systems are developed to
automatically acquire knowledge about molecule entities by reading large-scale biomedical …

Numerous important events happen everyday and everywhere but are reported in different
media sources with different narrative styles. How to detect whether real-world events have …

We propose a new task, Text2Mol, to retrieve molecules using natural language descriptions
as queries. Natural language and molecules encode information in very different ways …

To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant
biomedical knowledge in scientific literature to understand the disease mechanism and …

Event extraction (EE) is a crucial research task for promptly apprehending event information
from massive textual data. With the rapid development of deep learning, EE based on deep …

Abstract The tasks of Rich Semantic Parsing, such as Abstract Meaning Representation
(AMR), share similar goals with Information Extraction (IE) to convert natural language texts …

Compared to the general news domain, information extraction (IE) from biomedical text
requires much broader domain knowledge. However, many previous IE methods do not …

Entity Recognition (NER) is the first step for knowledge acquisition when we deal with an
unknown corpus of texts. Having received these entities, we have an opportunity to form …

Biomedical event extraction is critical in understanding biomolecular interactions described
in scientific corpus. One of the main challenges is to identify nested structured events that …