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Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)

Mariya Toneva, Leila Wehbe • arXiv (Cornell University) (2019)

Neural networks models for NLP are typically implemented without the explicit encoding of language rules and yet they are able to break one performance record after another. This has generated a lot of research interest in interpreting the ...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1905.11833

Detecting Fake News in Urdu Language Using Machine Learning, Deep Learning, and Large Language Model-Based Approaches

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

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

Natural Language Processing (almost) from Scratch

Ronan Collobert, Jason Weston, Léon Bottou, Michael Karlen et al. • arXiv (Cornell University) (2011)

We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including: part-of-speech tagging, chunking, named entity recognition, and semantic role labeling. This...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1103.0398

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 (Almost) from Scratch

CollobertRonan, WestonJason, BottouLéon, KarlenMichael et al. • Journal of Machine Learning Research (2011)

We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including part-of-speech tagging, chunking, named entity rec......

OPENALEX DOI: https://doi.org/10.5555/1953048.2078186

A unified architecture for natural language processing

Ronan Collobert, Jason Weston • International Conference on Machine Learning (2008)

We describe a single convolutional neural network architecture that, given a sentence, outputs a host of language processing predictions: part-of-speech tags, chunks, named entity tags, semantic roles, semantically similar words and the lik...

OPENALEX DOI: https://doi.org/10.1145/1390156.1390177

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

The NWRD Dataset: An Open-Source Annotated Segmentation Dataset of Diseased Wheat Crop

Hirra Anwar, Saad Ullah Khan, Muhammad Mohsin Ghaffar, Muhammad Fayyaz et al. • Sensors (2023)

Wheat stripe rust disease (WRD) is extremely detrimental to wheat crop health, and it severely affects the crop yield, increasing the risk of food insecurity. Manual inspection by trained personnel is carried out to inspect the disease spre...

DOAJ Open Access (DOAJ) DOI: 10.3390/s23156942

Vision-Based Autonomous Landing of a Quadrotor on the Perturbed Deck of an Unmanned Surface Vehicle

Riccardo Polvara, Sanjay Sharma, Jian Wan, Andrew Manning et al. • Drones (2018)

Autonomous landing on the deck of an unmanned surface vehicle (USV) is still a major challenge for unmanned aerial vehicles (UAVs). In this paper, a fiducial marker is located on the platform so as to facilitate the task since it is possibl...

DOAJ Open Access (DOAJ) DOI: 10.3390/drones2020015