Pre-trained models for natural language processing: A survey
Recently, the emergence of pre-trained models (PTMs) has brought natural language
processing (NLP) to a new era. In this survey, we provide a comprehensive review of PTMs …
processing (NLP) to a new era. In this survey, we provide a comprehensive review of PTMs …
[HTML][HTML] A survey of multimodal information fusion for smart healthcare: Map** the journey from data to wisdom
Multimodal medical data fusion has emerged as a transformative approach in smart
healthcare, enabling a comprehensive understanding of patient health and personalized …
healthcare, enabling a comprehensive understanding of patient health and personalized …
[HTML][HTML] AMMU: a survey of transformer-based biomedical pretrained language models
Transformer-based pretrained language models (PLMs) have started a new era in modern
natural language processing (NLP). These models combine the power of transformers …
natural language processing (NLP). These models combine the power of transformers …
Pre-training methods in information retrieval
The core of information retrieval (IR) is to identify relevant information from large-scale
resources and return it as a ranked list to respond to user's information need. In recent years …
resources and return it as a ranked list to respond to user's information need. In recent years …
A comparative study of using pre-trained language models for toxic comment classification
As user-generated contents thrive, so does the spread of toxic comment. Therefore,
detecting toxic comment becomes an active research area, and it is often handled as a text …
detecting toxic comment becomes an active research area, and it is often handled as a text …
[HTML][HTML] A review on Natural Language Processing Models for COVID-19 research
This survey paper reviews Natural Language Processing Models and their use in COVID-19
research in two main areas. Firstly, a range of transformer-based biomedical pretrained …
research in two main areas. Firstly, a range of transformer-based biomedical pretrained …
Short-text semantic similarity (stss): Techniques, challenges and future perspectives
In natural language processing, short-text semantic similarity (STSS) is a very prominent
field. It has a significant impact on a broad range of applications, such as question …
field. It has a significant impact on a broad range of applications, such as question …
Phraseformer: Multimodal key-phrase extraction using transformer and graph embedding
Background: Keyword extraction is a popular research topic in the field of natural language
processing. Keywords are terms that describe the most relevant information in a document …
processing. Keywords are terms that describe the most relevant information in a document …
Detecting emerging technologies and their evolution using deep learning and weak signal analysis
Emerging technologies can have major economic impacts and affect strategic stability. Yet,
early identification of emerging technologies remains challenging. In order to identify …
early identification of emerging technologies remains challenging. In order to identify …
Current status and future directions of deep learning applications for safety management in construction
The application of deep learning (DL) for solving construction safety issues has achieved
remarkable results in recent years that are superior to traditional methods. However, there is …
remarkable results in recent years that are superior to traditional methods. However, there is …