Special Issue:  Advanced Machine Learning for Natural Language Processing: Methods and Applications

Journal: CMC (Computer, Materials and Continua), Editorial: Tech Science Press, JCR  Q3

Submission Deadline:  30 November 2026

Summary

Rapid advancements in machine learning have transformed natural language processing (NLP), enabling unprecedented progress in understanding, generation, and interaction with human language.

This Special Issue aims to collect high-quality research on advanced machine learning methods that push the state of the art in Natural Language Processing, as well as innovative real-world applications. We welcome contributions addressing novel architectures, training paradigms, efficient and scalable learning strategies, interpretability, robustness, multimodal integration, and domain adaptation. Both theoretical advancements and applied research that provide empirical validation, benchmarks, or reproducible methodologies are strongly encouraged.

Suggested themes:
· Foundation models, large language models, and parameter-efficient adaptation
· Robustness, bias mitigation, and responsible AI in language technologies
· Multilingual and cross-lingual NLP methods
· Transfer learning and domain adaptation in NLP
· Explainable and ethical NLP systems
· Evaluation methodologies and benchmarks for NLP performance

More information at: https://www.techscience.com/cmc/special_detail/natural-language-processing