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Dejun Zhang, Mingbo Hong, Lu Zou, Fei Han et al. • International Journal of Computational Intelligence Systems
Recurrent neural network (RNN) is one of the most popular architectures for addressing variable sequence text, and it shows outstanding results in many natural language processing (NLP) tasks and remarkable performance in capturing long-ter...
DOAJ
Open Access (DOAJ)
DOI: 10.2991/ijcis.d.190710.001
Muhammad Shoaib Farooq, Syed Muhammad Asadullah Gilani, Muhammad Faraz Manzoor, Momina Shaheen • Information
(2025)
Fake news is false or misleading information that looks like real news and spreads through traditional and social media. It has a big impact on our social lives, especially in politics. In Pakistan, where Urdu is the main language, finding ...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/info16070595
Xinhui Liu, Jifa Chen, Qiubo Huang • Applied Sciences
(2025)
With the explosion of information, the amount of text data has increased significantly, making text categorization a central area of research in natural language processing (NLP). Traditional machine learning methods are effective, but deep...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app15084236
Yasir Abdelgadir Mohamed, Abdul Hakim H. M. Mohamed, Akbar Khanan, Mohamed Bashir et al. • IEEE Access
(2024)
This review examines the ethical, social, and technical challenges posed by AI-generated text tools, focusing on their rapid advancement and widespread adoption. An exhaustive literature search across many databases, strict inclusion/exclus...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2024.3521945
Ye Wang, Yaling Deng, Ge Wang, Tong Li et al. • Computers in Human Behavior: Artificial Humans
(2025)
Modern Large Language Models (LLMs) exhibit complexity and granularity similar to humans in the field of natural language processing, challenging the boundaries between humans and machines in language understanding and creativity. However, ...
DOAJ
Open Access (DOAJ)
DOI: 10.1016/j.chbah.2024.100103
Amirsina Torfi, Rouzbeh A. Shirvani, Yaser Keneshloo, Nader Tavaf et al. • arXiv (Cornell University)
(2020)
Natural Language Processing (NLP) helps empower intelligent machines by enhancing a better understanding of the human language for linguistic-based human-computer communication. Recent developments in computational power and the advent of l...
OPENALEX
Open Access
DOI: https://doi.org/10.48550/arxiv.2003.01200
V. Vishnuprabha, Lino Murali, Daleesha M Viswanathan • Apple Academic Press eBooks
(2021)
Understanding and processing human language has always been a complicated task in computational theory. Natural language processing, a combination of artificial intelligence and computational linguistics, employs computational techniques to...
OPENALEX
DOI: https://doi.org/10.1201/9781003082033-19
Lei Zhang, Yiru Huang, Leiming Yan, Jinghao Ge et al. • Advanced Intelligent Systems
(2024)
Making computers automatically extract latent scientific knowledge from literature is highly desired for future materials and chemical research in the artificial intelligence era. Herein, the natural language processing (NLP)‐based machine ...
DOAJ
Open Access (DOAJ)
DOI: 10.1002/aisy.202300678
Aditi S. Krishnapriyan, Joseph Montoya, Maciej Haranczyk, Jens Hummelshøj et al. • Scientific Reports
(2021)
Abstract Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an ...
DOAJ
Open Access (DOAJ)
DOI: 10.1038/s41598-021-88027-8
Charaf Ouaddi, Lamya Benaddi, Adnane Souha, Hamza Abdelmalek et al. • IEEE Access
(2025)
Conversational agents are intelligent, ubiquitous software applications widely used across various sectors, such as commerce, tourism, and more. Their key benefits include automating tasks, improving customer service, and ensuring service a...
DOAJ
Open Access (DOAJ)
DOI: 10.1109/ACCESS.2025.3574641
Lihua Han • Discover Artificial Intelligence
(2026)
Abstract Retrieval-augmented few-shot recognition supplements sparsely annotated target classes with external visual samples, but open retrieval results may exhibit unstable quality, semantic mismatch, and cross-domain feature shifts. Direc...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44163-026-02341-6
Maria Frasca, Davide La Torre, Gabriella Pravettoni, Ilaria Cutica • Discover Artificial Intelligence
(2024)
Abstract This review aims to explore the growing impact of machine learning and deep learning algorithms in the medical field, with a specific focus on the critical issues of explainability and interpretability associated with black-box alg...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44163-024-00114-7
Danielle Ryder • Discover Artificial Intelligence
(2026)
Abstract This paper proposes a hierarchy of epistemic betrayal that distinguishes deceptive behaviors in large language models (LLMs) by the depth at which the infrastructure for epistemic correction is compromised. Drawing on Park et al.’s...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44163-026-01438-2
Adam L. Berger, Vincent J. Della Pietra, Stephen A. Della Pietra (1996)
The concept of maximum entropy can be traced back along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statisti...
OPENALEX
DOI: https://doi.org/10.5555/234285.234289
Sebastian Ruder • Arrow@dit (Dublin Institute of Technology)
(2019)
The current generation of neural network-based natural language processing models excels at learning from large amounts of labelled data. Given these capabilities, natural language processing is increasingly applied to new tasks, new domain...
OPENALEX
Open Access
DOI: https://doi.org/10.13025/17598
Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo et al. • Foundations and Trends® in Machine Learning
(2023)
Deep learning has become the dominant approach in addressing various tasks in Natural Language Processing (NLP). Although text inputs are typically represented as a sequence of tokens, there is a rich variety of NLP problems that can be bes...
OPENALEX
Open Access
DOI: https://doi.org/10.1561/2200000096
Palash Goyal, Sumit Kumar Pandey, Karan Jain • Apress eBooks
(2018)
Discover the concepts of deep learning used for natural language processing (NLP) in this practical book, with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2...
OPENALEX
DOI: https://doi.org/10.1007/978-1-4842-3685-7
Pu Jiao, Limin Ran • Discover Artificial Intelligence
(2025)
Abstract With the rapid development of science and technology, augmented reality technology provides intelligent and application services. The research is based on imaging techniques using augmented reality technology and camera image captu...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44163-025-00399-2
Fangyan Huo, Yihua Li • Discover Artificial Intelligence
(2026)
Abstract This study presents a Data Fusion + Random Forest (RF) framework to predict adult learners’ educational outcomes, such as dropout risk and course completion. Adult lifelong learning is crucial for personal and professional growth, ...
DOAJ
Open Access (DOAJ)
DOI: 10.1007/s44163-026-01962-1
Miloš Bogdanović, Milena Frtunić Gligorijević, Jelena Kocić, Leonid Stoimenov • Applied Sciences
(2025)
Various areas of natural language processing (NLP) have greatly benefited from the development of large language models in recent years. This research addresses the challenge of developing efficient tokenizers for transformer-based domain-s...
DOAJ
Open Access (DOAJ)
DOI: 10.3390/app15137491