As part of the 2nd International Conference on Foundation and Large Language Models (FLLM2024)
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.
Topics of interests
This workshop invites submissions with high-quality works that are related, but are not limited, to the topics below:
Text classification
Automatic document summarization
Automatic machine translation
Sentiment analysis
Text generation
Deep learning for NLP
Reinforcement Learning for NLP
Unsupervised Learning for NLP
Speaker identification
Speech recognition
Speech to Text
Text detection and recognition from images
Question Answering systems
Transfer Learning for NLP
Active Learning for NLP
Real-life and industrially relevant NLP applications
Submission:
Papers submitted for review should conform to IEEE specifications. Manuscript templates can be downloaded from IEEE website. The maximum length of papers is 8 pages. All the papers will go through the double-blind peer review process. Authors’ names and affiliations should not appear in the submitted paper. Authors’ prior work should be cited in the third person. Authors should also avoid revealing their identities and/or institutions in the text, figures, links, etc.
Authors should also ensure that their identity is not revealed indirectly by citing their previous work in the third person and omitting acknowledgments until the camera-ready version. Papers have to be submitted via the workshop's EasyChair submission page.
Please include in the paper title "Full paper: Title" or "Short paper: Title" to precise the contribution type. At least one author of each accepted paper must register for the workshop, in order to present the paper. For further instructions, please refer to the FLLM 2024 page.
Important dates:
Submission Deadline: September 10, 2024
Decisions Announced: October 05, 2024
Camera Ready Deadline: October 25, 2024
Workshop: To be announced
Publication:
Accepted papers will be submitted to IEEEXplore for possible publication.