Natural Language Processing Based on Neural Networks and Large Language Models
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".
Deadline for manuscript submissions: 15 August 2025 | Viewed by 487
Special Issue Editors
Interests: deep learning; machine learning; natural language processing; computational linguistics; multimedia
Special Issues, Collections and Topics in MDPI journals
Interests: deep-learning-based research for human behavious recognition; human counting and density estimation; tiny object detection; biomedical applications; saliency detection; natural language processing; cybersecurity; face and face expression recognition; road sign detection; license plate recognition
Special Issue Information
Dear Colleagues,
We are excited to announce the launch of a new Special Issue entitled ‘Natural Language Processing Based on Neural Networks and Large Language Models’ in the journal Electronics. This Special Issue aims to explore the transformative impact of neural networks (NNs) and large language models (LLMs) on the field of natural language processing (NLP), highlighting advancements that are redefining the way machines understand and generate human language.
Natural language processing (NLP) has experienced a revolutionary shift with the advent of neural networks (NNs) and large language models (LLMs). These technologies enable advanced applications such as machine translation, sentiment analysis, and conversational agents. This Special Issue focuses on the latest advancements in NN- and LLM-based NLP, addressing challenges in scalability, efficiency, and ethical use, while showcasing innovative methodologies and real-world applications.
This Special Issue will delve into cutting-edge applications and methodologies leveraging NNs and LLMs for NLP, covering topics such as machine translation, conversational AI, sentiment analysis, text generation, and beyond.
We welcome original research, review articles, and case studies that explore the theoretical foundations, algorithmic innovations, and practical implementations of NNs and LLMs in NLP. Special emphasis will be placed on topics such as improving model efficiency, scalability, interpretability, and ethical concerns in AI development.
This Special Issue seeks to bridge gaps in the existing literature by providing a platform for novel ideas and multidisciplinary approaches to NLP. With rapid advancements in NN and LLM technologies, this collection will offer a timely and comprehensive perspective on their evolving role in solving complex linguistic challenges across diverse domains.
While existing research has extensively explored traditional NLP approaches, the rapid development of NN and LLM technologies introduces new challenges and opportunities. This Special Issue will provide an invaluable supplement to the current literature by achieving the following:
- Showcasing innovative methods that address the limitations of earlier NLP techniques.
- Discussing the practical implications of NN- and LLM-based solutions in real-world applications.
- Addressing ethical and societal considerations that arise with the deployment of large-scale language models.
We invite you to submit your latest research to contribute to this exciting field.
Dr. Krzysztof Wolk
Prof. Dr. Xiangjian He
Guest Editors
Manuscript Submission Information
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Keywords
- natural language processing (NLP)
- neural networks (NN)
- large language models (LLM)
- machine translation
- sentiment analysis
- conversational artificial intelligence
- deep learning
- ethical artificial intelligence
- text generation
- computational linguistics
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