Special Issue: Advances in Natural Language Processing
Natural Language Processing (NLP) has become a transformative area in artificial intelligence and computational linguistics, significantly influencing fields such as machine translation, sentiment analysis, information retrieval, and human-computer interaction. Recent breakthroughs in deep learning, transformer architectures, and large-scale language models have propelled NLP to new heights, yet challenges remain in areas such as explainability, low-resource language processing, bias mitigation, and domain adaptation.
This Special Issue aims to showcase state-of-the-art research and innovative contributions in NLP, fostering discussions on theoretical advancements, practical applications, and emerging trends. We welcome high-quality original research papers, comprehensive reviews, and case studies addressing both fundamental and applied aspects of NLP.
This Special Issue invites contributions on, but not limited to, the following topics:
- Transformer models and their applications (BERT, GPT, T5, etc.)
- Few-shot, zero-shot, and self-supervised learning for NLP
- Explainability, interpretability, and trustworthiness in NLP models
- Low-resource language processing and multilingual NLP
- Sentiment analysis, opinion mining, and emotion detection
- Text summarization, information extraction, and question-answering
- Machine translation and cross-lingual understanding
- Fairness, ethics, and bias mitigation in NLP systems
- Conversational AI, dialogue systems, and chatbot development
- NLP applications in domains such as healthcare, finance, and education
Guest Editor: Dr. Engr. Mohammad Aman Ullah, SMIEEE
Chairman & Associate professor
Department of Computer science and engineering
International Islamic University Chittagong
Contact: +88-01815641524
Email: aman_cse@iiuc.ac.bd
weblink: https://www.iiuc.ac.bd/profile/view/amanullah
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For any inquiries about this Special Issue, please contact the Editors via editorial-cm@wiserpub.com