DLNLP

DLNLP 2024 is a workshop at the AICCSA/IEEE International Conference on Computer Systems and Applications (AICCSA’24), that aims to consolidate the latest advancements in Deep Learning architectures adapted to NLP applications such as machine translation, sentiment analysis, question-answering, summarization, etc. 

Natural Language Processing (NLP) poses a significant challenge within computational linguistics due to the intricate grammatical structures, intricate morphologies, and orthographic ambiguities found in numerous languages. These diverse linguistic characteristics heighten the complexity of NLP tasks, necessitating the development of effective approaches. Over the past decade, deep learning approaches have demonstrated remarkable performance across a wide array of NLP tasks. 

This workshop provides an opportunity to present cutting-edge NLP research that relies on deep learning methods, including but not limited to, pre-train or fine-tuned large language models, information extraction, sentiment analysis, named entity recognition and disambiguation, text classification and summarization, text simplification, text generation, social media analytics, optical character recognition, speech synthesis, machine translation, pattern recognition, syntactic analysis, part-of-speech tagging, dialect identification, dialect translation, fake news detection, financial NLP, healthcare NLP, plagiarism detection, authorship identification and verification,  etc. 

PUBLICATION

Papers accepted for presentation will be published by IEEE Computer Society Press as proceedings of the AICCSA Conference Publishing Services and be submitted to IEEE Xplore for inclusion.