Emerging Theory and Applications in Natural Language Processing, 2nd Edition
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Artificial Intelligence".
Deadline for manuscript submissions: 15 June 2025 | Viewed by 19
Special Issue Editors
Interests: knowledge graph; natural language processing; multimodal
Special Issues, Collections and Topics in MDPI journals
Interests: natural language processing; knowledge graph; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: information retrieval; question answering and dialogue; natural language processing; biomedical literature-based knowledge discovery
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues
In recent years, natural language processing (NLP) has been transformed by groundbreaking advancements in deep learning and the emergence of large language models (LLMs). The integration of LLMs with adaptation tuning methods has significantly increased the generalization capabilities of NLP models, potentially enabling the development of general artificial intelligence systems. Recognizing the significance of this progress, it is crucial to explore their potential and understand their relationship with classical methods in shaping the future of NLP and its real-world applications. The aim of this Special Issue is to showcase cutting-edge research in NLP, highlighting novel theories, methods, and applications that advance the state of the art, while also promoting interdisciplinary research.
The scope of this Special Issue includes, but is not limited to, the following topics:
- Novel NLP theory, architectures, and algorithms;
- Theoretical foundations of LLMs: emergent abilities, scaling effects, etc.;
- Model training and utilization strategies;
- Efficiency and scalability of language models;
- Integration of NLP with other AI technologies;
- Interpretability of NLP and LLM;
- Evaluating large language models: capabilities and limitations;
- Ethical considerations and fairness;
- Safety and alignment in LLMs;
- Domain-specific NLP applications;
- Other emerging topics in NLP and LLM research.
Dr. Linmei Hu
Dr. Jian Liu
Dr. Bo Xu
Guest Editors
Manuscript Submission Information
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Keywords
- natural language processing
- large language models
- NLP theory and application
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