The discipline of Automatic Text Summarization (ATS), which is expanding quickly, intends
to automatically create summaries of enormous amounts of text so that readers can save …

An accident database is an excellent data source if appropriately leveraged along with
domain expertise. However, a proper framework and tools are required to extract data from a …

Hallucinations in large language models (LLMs) refer to the phenomenon of LLMs
producing responses that are coherent yet factually inaccurate. This issue undermines the …

Information extraction (IE) approaches often play a pivotal role in text analysis and require
significant human intervention. Therefore, a deeper understanding of existing IE practices …

This study analyzed fact-check stories (N= 1,530) published in four legacy news media
organizations in the United States–The Associated Press, CNN, The New York Times, and …

Annotation quality and quantity positively affect the learning performance of sequence
labeling, a vital task in Natural Language Processing. Hiring domain experts to annotate a …

Dynamic retrieval augmented generation (RAG) paradigm actively decides when and what
to retrieve during the text generation process of Large Language Models (LLMs). There are …

Official gazettes are documents published by governments to publicize their actions,
spanning long periods of time and making an important transparency mechanism. These …

Sentiment analysis, is commonly known as opinion mining, is a vital field in natural
language processing (NLP) that claims to find out the sentiment or emotion expressed in a …

This study focuses on predicting the popularity of a product based on its overall rating score.
Unlike previous studies that focus on predicting the review rating based on sentiment …