{"id":2115,"date":"2024-05-17T14:05:08","date_gmt":"2024-05-17T21:05:08","guid":{"rendered":"https:\/\/aiccsa.net\/AICCSA2024\/?page_id=2115"},"modified":"2024-06-14T10:19:50","modified_gmt":"2024-06-14T17:19:50","slug":"dlnlp-2024","status":"publish","type":"page","link":"https:\/\/aiccsa.net\/AICCSA2024\/dlnlp-2024\/","title":{"rendered":"DLNLP 2024"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-page\" data-elementor-id=\"2115\" class=\"elementor elementor-2115\" data-elementor-post-type=\"page\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-ae51883 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"ae51883\" data-element_type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-0fa9b53\" data-id=\"0fa9b53\" data-element_type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-80fea41 elementor-widget elementor-widget-text-editor\" data-id=\"80fea41\" data-element_type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<p style=\"text-align: center;\"><strong><span style=\"color: #0000ff;\">Deep Learning for Natural Language Processing<\/span><\/strong><\/p><p style=\"text-align: center;\"><a href=\"https:\/\/sites.google.com\/view\/dlnlp2024-at-aiccsa\/home\"><strong><span style=\"color: #0000ff;\">https:\/\/sites.google.com\/view\/dlnlp2024-at-aiccsa\/home<\/span><\/strong><\/a><\/p><p><strong><span style=\"color: #000000;\">ORGANIZING COMMITTEE:<\/span><\/strong><\/p><ul><li><span style=\"color: #000000;\"><strong>Lamia Hadrich Belguith<\/strong> (ANLP Research Group, MIRACL Lab., FSEG, University of Sfax,<\/span><span style=\"color: #000000;\">Tunisia)<\/span><\/li><li><span style=\"color: #000000;\"><strong>Maher Jaoua<\/strong> (ANLP Research Group, MIRACL Lab., FSEG, University Of Sfax, Tunisia)<\/span><\/li><li><span style=\"color: #000000;\"><strong>Samira Ellouze<\/strong> (ANLP Research Group, MIRACL Lab., ISIMG, University of Gabes,<\/span><span style=\"color: #000000;\">Tunisia)<\/span><\/li><\/ul><p><strong><span style=\"color: #000000;\">Overview:<\/span><\/strong><\/p><p><span style=\"color: #000000;\">Natural Language Processing (NLP) presents a significant challenge within computational <\/span><span style=\"color: #000000;\">linguistics due to the intricate grammatical structures, intricate morphologies, and orthographic <\/span><span style=\"color: #000000;\">ambiguities found in numerous languages. These diverse linguistic characteristics amplify the <\/span><span style=\"color: #000000;\">complexity of NLP tasks, necessitating the development of robust methodologies. We need to <\/span><span style=\"color: #000000;\">think about innovative methods that can deal with the linguistic complexity.<\/span><br \/><span style=\"color: #000000;\">Deep learning techniques have demonstrated remarkable performance across a wide array of <\/span><span style=\"color: #000000;\">NLP tasks. Deep Learning for Natural Language Processing workshop aims to explore the <\/span><span style=\"color: #000000;\">recent advancements in deep learning architectures and techniques that can be used to resolve <\/span><span style=\"color: #000000;\">the complexity of language phenomena encountered in various NLP applications such as <\/span><span style=\"color: #000000;\">machine translation, sentiment analysis, chatbots, and more.<\/span><br \/><span style=\"color: #000000;\">This workshop serves as a platform for researchers and practitioners actively involved in the <\/span><span style=\"color: #000000;\">development of NLP applications. Participants will have the opportunity to present and discuss <\/span><span style=\"color: #000000;\">the recent fundamental and applied research works, providing novel solutions to emerging <\/span><span style=\"color: #000000;\">challenges in different NLP fields.<\/span><br \/><span style=\"color: #000000;\">Topics <\/span><span style=\"color: #000000;\">The Deep Learning for Natural Language Processing workshop will explore a wide range of <\/span><span style=\"color: #000000;\">applications and techniques, including but not limited to:<\/span><\/p><ul><li><span style=\"color: #000000;\">Pre-training or fine-tuning large language models,<\/span><\/li><li><span style=\"color: #000000;\">Information extraction,<\/span><\/li><li><span style=\"color: #000000;\">Sentiment analysis,<\/span><\/li><li><span style=\"color: #000000;\">Named entity recognition and disambiguation,<\/span><\/li><li><span style=\"color: #000000;\">Text classification, text generation, text summarization and text simplification,<\/span><\/li><li><span style=\"color: #000000;\">Social media analytics,<\/span><\/li><li><span style=\"color: #000000;\">Optical character recognition,<\/span><\/li><li><span style=\"color: #000000;\">Speech synthesis,<\/span><\/li><li><span style=\"color: #000000;\">Machine translation,<\/span><\/li><li><span style=\"color: #000000;\">Pattern recognition,<\/span><\/li><li><span style=\"color: #000000;\">Syntactic analysis,<\/span><\/li><li><span style=\"color: #000000;\">Part-of-speech tagging,<\/span><\/li><li><span style=\"color: #000000;\">Dialect identification,<\/span><\/li><li><span style=\"color: #000000;\">Dialect translation,<\/span><\/li><li><span style=\"color: #000000;\">Fake news detection,<\/span><\/li><li><span style=\"color: #000000;\">Financial NLP,<\/span><\/li><li><span style=\"color: #000000;\">Healthcare NLP,<\/span><\/li><li><span style=\"color: #000000;\">Plagiarism detection,<\/span><\/li><li><span style=\"color: #000000;\">Authorship identification and verification<\/span><\/li><\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Deep Learning for Natural Language Processing https:\/\/sites.google.com\/view\/dlnlp2024-at-aiccsa\/home ORGANIZING COMMITTEE: Lamia Hadrich Belguith (ANLP Research Group, MIRACL Lab., FSEG, University of Sfax,Tunisia) Maher Jaoua (ANLP Research Group, MIRACL Lab., FSEG, University Of Sfax, Tunisia) Samira Ellouze (ANLP Research Group, MIRACL Lab., ISIMG, University of Gabes,Tunisia) Overview: Natural Language Processing (NLP) presents a significant challenge within computational 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