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Relevant bibliographies by topics / Cross-language re-use detection

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Academic literature on the topic 'Cross-language re-use detection'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "Cross-language re-use detection"

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Flores, Enrique, Alberto Barrón-Cedeño, Lidia Moreno, and Paolo Rosso. "Cross-Language Source Code Re-Use Detection Using Latent Semantic Analysis." JUCS - Journal of Universal Computer Science 21, no. (13) (2015): 1708–25. https://doi.org/10.3217/jucs-021-13-1708.

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Nowadays, Internet is the main source to get information from blogs, encyclopedias, discussion forums, source code repositories, and more resources which are available just one click away. The temptation to re-use these materials is very high. Even source codes are easily available through a simple search on the Web. There is a need of detecting potential instances of source code re-use. Source code re-use detection has usually been approached comparing source codes in their compiled version. When dealing with cross-language source code re-use, traditional approaches can deal only with the pro

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Mohtaj, Salar, and Habibollah Asghari. "A Corpus for Evaluation of Cross Language Text Re-use Detection Systems." Journal of Information Systems and Telecommunication (JIST) 10, no. 39 (2022): 169–79. http://dx.doi.org/10.52547/jist.33583.10.39.169.

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Zhang, Jiang, Qiong Wu, Yiming Xu, Cheng Cao, Zheng Du, and Konstantinos Psounis. "Efficient Toxic Content Detection by Bootstrapping and Distilling Large Language Models." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 19 (2024): 21779–87. http://dx.doi.org/10.1609/aaai.v38i19.30178.

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Toxic content detection is crucial for online services to remove inappropriate content that violates community standards. To automate the detection process, prior works have proposed varieties of machine learning (ML) approaches to train Language Models (LMs) for toxic content detection. However, both their accuracy and transferability across datasets are limited. Recently, Large Language Models (LLMs) have shown promise in toxic content detection due to their superior zero-shot and few-shot in-context learning ability as well as broad transferability on ML tasks. However, efficiently designin

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Dr., K. Sravana Kumar. "MIDDLE CLASS MOVEMENTS." International Journal of Multidisciplinary Research and Modern Education 2, no. 2 (2016): 59–66. https://doi.org/10.5281/zenodo.61810.

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            The middle class is placed between labour and capital. It neither directly awns the means of production that pumps out the surplus generated by wage labour power, nor does it, by its own labour, produce the surplus which has use and exchange value. Broadly speaking, this class consists of the petty bourgeoisie and the white-collar workers. The former are either self-employed or involved in the distribution of commodities and the latter are non-manual office workers, supervisors and professionals. Thus, in terms of occupation, s

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Hong, Gibong, Veronica Hindle, Nadine M. Veasley, Hannah D. Holscher, and Halil Kilicoglu. "DiMB-RE: mining the scientific literature for diet-microbiome associations." Journal of the American Medical Informatics Association, March 27, 2025. https://doi.org/10.1093/jamia/ocaf054.

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Abstract Objectives To develop a corpus annotated for diet-microbiome associations from the biomedical literature and train natural language processing (NLP) models to identify these associations, thereby improving the understanding of their role in health and disease, and supporting personalized nutrition strategies. Materials and Methods We constructed DiMB-RE, a comprehensive corpus annotated with 15 entity types (eg, Nutrient, Microorganism) and 13 relation types (eg, increases, improves) capturing diet-microbiome associations. We fine-tuned and evaluated state-of-the-art NLP models for na

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Van Eecke, Paul, Katrien Beuls, Jérôme Botoko Ekila, and Roxana Rădulescu. "Language games meet multi-agent reinforcement learning: A case study for the naming game." Journal of Language Evolution, April 18, 2023. http://dx.doi.org/10.1093/jole/lzad001.

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Abstract Today, computational models of emergent communication in populations of autonomous agents are studied through two main methodological paradigms: multi-agent reinforcement learning (MARL) and the language game paradigm. While both paradigms share their main objectives and employ strikingly similar methods, the interaction between both communities has so far been surprisingly limited. This can to a large extent be ascribed to the use of different terminologies and experimental designs, which sometimes hinder the detection and interpretation of one another’s results and progress. Through

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Ernest-Okonofua, Excel Onajite, Zainab Abdullahi Zubairu, Malik Olatunde Oduoye, et al. "Harnessing Artificial Intelligence and Innovative Vaccines for Mpox Diagnosis and Control: A Comprehensive Narrative Review." Journal of Primary Care & Community Health 16 (July 2025). https://doi.org/10.1177/21501319251357701.

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Background: The re-emergence of monkeypox (mpox) has triggered a global alert and galvanized efforts toward a scientific reappraisal of the disease. Aim: This study aims to provide a review of the use of Artificial Intelligence (AI) and novel vaccines in reducing the burden of mpox. Methodology: A narrative review was conducted according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines through electronic databases including PubMed, Google Scholar, ResearchGate, and Web of Science (WOS), using keywords such as Mpox, machine learning, deep learning, diagn

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Mogili, Poojitha. "Blockchain Fault Transaction Detection using ML & Solidity." April 9, 2025. https://doi.org/10.5281/zenodo.15179713.

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<strong>Blockchain Fault Transaction Detection Using ML & Solidity</strong> <strong>Mr. G. Rajesh</strong> Assistant Professor, PBR VITS, Kavali, Nellore – 524201 <strong>MVN Poojitha</strong>, <strong>CVSL Bhavana</strong>, <strong>P Prathyusha</strong>, <strong>G Manospandana</strong> UG Students, Department of CSE, PBR VITS, Kavali, Nellore – 524201 <strong>Abstract</strong> This paper proposes an intelligent and secure solution for detecting fraudulent transactions in blockchain networks by combining machine learning (ML) algorithms with blockchain technology. The system in

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Koolvisoot, Ajchara, and Sasamon Chumjang. "Prevalence of cognitive impairment and cognitive improvement in patients with systemic lupus erythematosus during a 6-month follow-up study." Lupus, August 17, 2023. http://dx.doi.org/10.1177/09612033231196215.

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Objectives The Montreal Cognitive Assessment (MoCA) is a simple and reliable screening tool for early detection for cognitive impairment in systemic lupus erythematosus (SLE). Most previous studies were cross-sectional with small samples. Research on long-term cognitive changes and reversibility is limited. This study aimed to establish the prevalence of cognitive impairment and changes in SLE patients after 6 months and the associated factors. Methods A prospective study was conducted in 200 patients with SLE between April 2021 and March 2022. Demographic data, disease activity, and medicatio

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V.Lakshmi, chaitanya, Nafisa Afreen S., Veena K., Gayathri P., Pavitra S., and Aparna M. "Plagiarism detection process using AI." April 25, 2023. https://doi.org/10.5281/zenodo.7894600.

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ISSN (Print): 2395-4752 Plagiarism Detection Process Using AI <strong>Lakshmi Chaitanya, S. Nafisa Afreen, K. Veena, P. Gayathri, S. Pavitra , M. Aparna</strong> Department of Computer Science & Engineering Santhiram Engineering College, India   <strong>Abstract- Plagiarism relates to the act of taking information or ideas of someone else and demands it as your own. Basically, it reproduces the existing information in modified format. In every field of education, it becomes a serious issue. Various techniques and tools are derived these days to detect plagiarism.</strong> <strong>Vari

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Dissertations / Theses on the topic "Cross-language re-use detection"

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Barrón, Cedeño Luis Alberto. "On the Mono- and Cross-Language Detection of Text Re-Use and Plagiarism." Doctoral thesis, Universitat Politècnica de València, 2012. http://hdl.handle.net/10251/16012.

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Barrón Cedeño, LA. (2012). On the Mono- and Cross-Language Detection of Text Re-Use and Plagiarism [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/16012<br>Palancia

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Book chapters on the topic "Cross-language re-use detection"

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Barròn-Cedeño, Alberto, Paolo Rosso, Sobha Lalitha Devi, Paul Clough, and Mark Stevenson. "PAN@FIRE: Overview of the Cross-Language !ndian Text Re-Use Detection Competition." In Multilingual Information Access in South Asian Languages. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40087-2_6.

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