Abstract Knowledge extraction is meant by acquiring relevant information from the
unstructured document in natural language and representing them in a structured form …

In the clinical and healthcare domains, medical images play a critical role. A mature medical
visual question answering system (VQA) can improve diagnosis by answering clinical …

Textual documents serve as representations of discussions on a variety of subjects. These
discussions can vary in length and may encompass a range of events or factual information …

Fine-tuning transformer models after unsupervised pre-training reaches a very high
performance on many different natural language processing tasks. Unfortunately …

Fake news has evolved into a pervasive issue in the era of information overload, influencing
public opinion and challenging the credibility of news sources. While various approaches …

Relation extraction (RE) has recently moved from the sentence-level to document-level,
which requires aggregating document information and using entities and mentions for …

Camera-captured document images usually suffer from various appearance degradations,
which hamper the clarity of content and preclude subsequent analysis and recognition …

Identifying chemical-induced disease (CID) semantic relations in the biomedical literature,
including both intra-and inter-sentence interactions, has significant implications for various …

Enhancing learning effectiveness requires one to define suitable learning outcomes and
align assessment constructs with these outcomes. We present a quad-faceted feature-based …

The task of relation extraction in natural language processing is to identify the relation
between two specified entities in a sentence. However, the existing model methods do not …