GENAIDOC: Generative AI for Textual Document Analysis  


                

1st International Workshop, in conjunction with FLLM 2024, from November 26 to November 29, 2024 Dubai, UAE


Context


Nowadays, the volume of textual data being generated is unprecedented. From social media posts, news articles, and academic papers to customer reviews, emails, and business documents, the sheer quantity of text data is growing exponentially. Traditional methods of analyzing this vast amount of data often fall short in terms of scalability, accuracy, and efficiency.


In this context, Generative AI (GenAI) is revolutionizing the field of Natural Language Processing (NLP) by enabling the creation of highly sophisticated Large Language Models (LLMs) that can generate, understand, and manipulate human language. GenAI models like GPT-4 and BERT are at the forefront of these advancements from chatbots to automated content creation. This workshop aims to provide participants with a deep understanding of LLMs, its applications in NLP, and the ethical considerations involved. GenAI models are designed to handle and process enormous datasets, making them ideal for textual document analysis. These models leverage advanced machine learning techniques to understand, interpret, and generate human-like text, allowing for more nuanced and comprehensive analysis. By using LLMs, we can uncover insights and patterns that would be impossible to detect using conventional methods.


Objective 


This workshop is designed to provide a comprehensive understanding of how LLMs can be leveraged for textual document analysis. Participants will gain hands-on experience and theoretical knowledge about the applications, capabilities, and limitations of GenAI models in the context of analyzing textual data. The workshop will cover various techniques and tools, practical implementation, and the latest advancements in the field.


The GENAIDOC workshop aims to bring together an area for experts from industry, science, and academia to exchange ideas and discuss ongoing research in natural language processing and GenAI for textual document analysis.