Generative Knowledge Graph Construction (KGC) refers to those methods that leverage the
sequence-to-sequence framework for building knowledge graphs, which is flexible and can …

Social media is used to categorise products or services, but analysing vast comments is time-
consuming. Researchers use sentiment analysis via natural language processing …

Self-supervised protein language models have proved their effectiveness in learning the
proteins representations. With the increasing computational power, current protein language …

The field of machine learning (ML) has gained widespread adoption, leading to significant
demand for adapting ML to specific scenarios, which is yet expensive and non-trivial. The …

Geological reports aid in understanding exploration by providing valuable information on
rock formation, evolution and the geological environment in which deposits formed …

In this paper, the problem of joint communication and computation design for probability
graph-based semantic communication over wireless networks is investigated. In the …

Knowledge graphs (KGs) are widely used in the education domain to offer learners a
semantic representation of domain concepts from educational content and their relations …

Event understanding aims at understanding the content and relationship of events within
texts, which covers multiple complicated information extraction tasks: event detection, event …

Knowledge base population (KBP) from texts involves the extraction and organization of
information from unstructured textual data to enhance or create a structured knowledge …

Cross-domain NER is a challenging task to address the low-resource problem in practical
scenarios. Previous typical solutions mainly obtain a NER model by pre-trained language …