A comprehensive survey on pretrained foundation models: A history from bert to chatgpt
Abstract Pretrained Foundation Models (PFMs) are regarded as the foundation for various
downstream tasks across different data modalities. A PFM (eg, BERT, ChatGPT, GPT-4) is …
downstream tasks across different data modalities. A PFM (eg, BERT, ChatGPT, GPT-4) is …
When large language models meet personalization: Perspectives of challenges and opportunities
The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …
intelligence. With the unprecedented scale of training and model parameters, the capability …
ChatGPT chemistry assistant for text mining and the prediction of MOF synthesis
We use prompt engineering to guide ChatGPT in the automation of text mining of metal–
organic framework (MOF) synthesis conditions from diverse formats and styles of the …
organic framework (MOF) synthesis conditions from diverse formats and styles of the …
BERTopic: Neural topic modeling with a class-based TF-IDF procedure
M Grootendorst - arXiv preprint arXiv:2203.05794, 2022 - arxiv.org
Topic models can be useful tools to discover latent topics in collections of documents.
Recent studies have shown the feasibility of approach topic modeling as a clustering task …
Recent studies have shown the feasibility of approach topic modeling as a clustering task …
Glam: Efficient scaling of language models with mixture-of-experts
Scaling language models with more data, compute and parameters has driven significant
progress in natural language processing. For example, thanks to scaling, GPT-3 was able to …
progress in natural language processing. For example, thanks to scaling, GPT-3 was able to …
A review on sentiment analysis and emotion detection from text
P Nandwani, R Verma - Social network analysis and mining, 2021 - Springer
Social networking platforms have become an essential means for communicating feelings to
the entire world due to rapid expansion in the Internet era. Several people use textual …
the entire world due to rapid expansion in the Internet era. Several people use textual …
A survey on text classification: From traditional to deep learning
Text classification is the most fundamental and essential task in natural language
processing. The last decade has seen a surge of research in this area due to the …
processing. The last decade has seen a surge of research in this area due to the …
A comprehensive survey on sentiment analysis: Approaches, challenges and trends
Sentiment analysis (SA), also called Opinion Mining (OM) is the task of extracting and
analyzing people's opinions, sentiments, attitudes, perceptions, etc., toward different entities …
analyzing people's opinions, sentiments, attitudes, perceptions, etc., toward different entities …
An introduction to deep learning in natural language processing: Models, techniques, and tools
Abstract Natural Language Processing (NLP) is a branch of artificial intelligence that
involves the design and implementation of systems and algorithms able to interact through …
involves the design and implementation of systems and algorithms able to interact through …
Learning transferable visual models from natural language supervision
State-of-the-art computer vision systems are trained to predict a fixed set of predetermined
object categories. This restricted form of supervision limits their generality and usability since …
object categories. This restricted form of supervision limits their generality and usability since …