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An Analysis of the Training Data Impact for Domain-Adapted Tokenizer Performances—The Case of Serbian Legal Domain Adaptation

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

A Survey of the State of Explainable AI for Natural Language Processing

Marina Danilevsky, Kun Qian, Ranit Aharonov, Yannis Katsis et al. • Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the International Joint Conference on Natural Language Processing (AACL-IJCNLP) (2020)

Marina Danilevsky, Kun Qian, Ranit Aharonov, Yannis Katsis, Ban Kawas, Prithviraj Sen. Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conferenc...

OPENALEX cc-by DOI: https://doi.org/10.18653/v1/2020.aacl-main.46

Five sources of bias in natural language processing

Dirk Hovy, Shrimai Prabhumoye • Language and Linguistics Compass (2021)

Recently, there has been an increased interest in demographically grounded bias in natural language processing (NLP) applications. Much of the recent work has focused on describing bias and providing an overview of bias in a larger context....

OPENALEX cc-by-nc DOI: https://doi.org/10.1111/lnc3.12432 PMC: 9285808

Datasets: A Community Library for Natural Language Processing

Quentin Lhoest, A. Villanova del Moral, Yacine Jernite, Abhishek Thakur et al. • Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP) (2021)

Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite, Abhishek Thakur, Patrick von Platen, Suraj Patil, Julien Chaumond, Mariama Drame, Julien Plu, Lewis Tunstall, Joe Davison, Mario Šaško, Gunjan Chhablani, Bhavitvya Malik, Simon Bra...

OPENALEX cc-by DOI: https://doi.org/10.18653/v1/2021.emnlp-demo.21

Natural Language Processing

Abhimanyu Chopra, Abhinav Prashar, Chandresh Sain • Natural language processing (2013)

ABSTRACT: Language is way of communicating your words Language helps in understanding the world,we get a better insight of the world. Language helps speakers to be as vague or as precise as they like. NLP Stands for natural language process...

OPENALEX DOI: https://doi.org/10.1075/nlp

Natural Language Processing for Smart Healthcare

Binggui Zhou, Guanghua Yang, Zheng Shi, Shaodan Ma • IEEE Reviews in Biomedical Engineering (2022)

Smart healthcare has achieved significant progress in recent years. Emerging artificial intelligence (AI) technologies enable various smart applications across various healthcare scenarios. As an essential technology powered by AI, natural ...

OPENALEX Open Access DOI: https://doi.org/10.1109/rbme.2022.3210270

Natural Language Processing

Aravind K. Joshi • Science (1991)

Natural language processing (NLP) is the study of mathematical and computational modeling of various aspects of language and the development of a wide range of systems. These include spoken language systems that integrate speech and natural...

OPENALEX DOI: https://doi.org/10.1126/science.253.5025.1242

Arabic Natural Language Processing

Ali Farghaly, Khaled F. Shaalan • ACM Transactions on Asian Language Information Processing (2009)

The Arabic language presents researchers and developers of natural language processing (NLP) applications for Arabic text and speech with serious challenges. The purpose of this article is to describe some of these challenges and to present...

OPENALEX DOI: https://doi.org/10.1145/1644879.1644881

Natural Language Processing for Requirements Engineering

Liping Zhao, Waad Alhoshan, Alessio Ferrari, Keletso J. Letsholo et al. • ACM Computing Surveys (2021)

Natural Language Processing for Requirements Engineering (NLP4RE) is an area of research and development that seeks to apply natural language processing (NLP) techniques, tools, and resources to the requirements engineering (RE) process, to...

OPENALEX Open Access DOI: https://doi.org/10.1145/3444689

Transfer Learning in Natural Language Processing

Sebastian Ruder, Matthew E. Peters, Swabha Swayamdipta, Thomas Wolf (2019)

The classic supervised machine learning paradigm is based on learning in isolation, a single predictive model for a task using a single dataset. This approach requires a large number of training examples and performs best for well-defined a...

OPENALEX cc-by DOI: https://doi.org/10.18653/v1/n19-5004

Handbook of Natural Language Processing

Robert Dale, Hermann L. Moisl, HAROLD L. SOMERS • Computational Linguistics (2001)

Symbolic approaches to natural language processing tokenisation and sentence segmentation lexical analysis parsing techniques semantic analysis discourse structure and intention recognition natural language generation intelligent writing as...

OPENALEX Open Access DOI: https://doi.org/10.1162/coli.2000.27.4.602

Natural Language Processing in Oncology

Wen-wai Yim, Meliha Yetişgen, William Proctor Harris, Sharon W. Kwan • JAMA Oncology (2016)

IMPORTANCE: Natural language processing (NLP) has the potential to accelerate translation of cancer treatments from the laboratory to the clinic and will be a powerful tool in the era of personalized medicine. This technology can harvest im...

OPENALEX DOI: https://doi.org/10.1001/jamaoncol.2016.0213

Transformers: State-of-the-Art Natural Language Processing

Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond et al. • Conference on Empirical Methods in Natural Language Processing: System Demonstrations (EMNLP) (2020)

Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu...

OPENALEX cc-by DOI: https://doi.org/10.18653/v1/2020.emnlp-demos.6

Natural language processing

Gobinda G Chowdhury • Annual Review of Information Science and Technology (2003)

Previous ARIST chapters (Haas, 1996;Warner, 1987) described a number of theoretical developments that have influenced research in NLP.The most recent theoretical developments can be grouped into four classes: (i) statistical and corpus-base...

OPENALEX Open Access DOI: https://doi.org/10.1002/aris.1440370103

Natural language processing: an introduction

Prakash M. Nadkarni, Lucila Ohno-machado A, Wendy W. Chapman • Journal of the American Medical Informatics Association (2011)

OBJECTIVES: To provide an overview and tutorial of natural language processing (NLP) and modern NLP-system design. TARGET AUDIENCE: This tutorial targets the medical informatics generalist who has limited acquaintance with the principles be...

OPENALEX Open Access DOI: https://doi.org/10.1136/amiajnl-2011-000464 PMC: 3168328

Transformer in Computer Vision

Jiarui Bi, Zengliang Zhu, Qinglong Meng • International Conference on Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI) (2021)

Transformer is widely used in Natural Language Processing (NLP), in which numerous papers have been proposed. Recently, the transformer has been borrowed for many computer vision tasks. However, there are few papers to give a comprehensive ...

OPENALEX DOI: https://doi.org/10.1109/cei52496.2021.9574462