The increasing complexity of how humans interact with and process information has demonstrated significant advancements in Natural Language Processing (NLP), transitioning from task-specific architectures to generalized frameworks applicable across multiple tasks. Despite their success, challenges persist in specialized domains such as translation, where instruction tuning may prioritize fluency over accuracy. Against this backdrop, the present study conducts a comparative evaluation of ChatGPT-Plus and DeepSeek (R1) on a high-fidelity bilingual retrieval-and-translation task. A single standardize prompt directs each model to access the Arabic-language news section of the College of Medicine, University of Baghdad, retrieve the three most recent articles, and translate them into English. ChatGPT-Plus fulfilled the prompt successfully, extracting authentic Arabic content and delivering fluent, semantically accurate English translations. DeepSeek (R1), by contrast, failed to retrieve the requested articles and instead produced only generic procedural advice – evidence of its lack of real-time web access and a retrieval-augmented generation (RAG) mechanism.
(1)
(1)
DBNRAAK Mohammed, International Journal of Research in Social Sciences and Humanities, 2020
(1)
This study is dedicated to one of the most difficult topics in Russian - this is the science of idioms. A feature of the Russian speech application in recent decades has been the effective change in the lexical composition of the Russian language. This article illustrates the semantic, grammatical and stylistic structural characteristics of the linguistic units that appeared in Russian at the end of the 20th century - the beginning of the twenty-first century. This work defines these terms : terminology, linguistic unity, and terms that are used as synonyms. In this research , we will adhere to the conciliatory view of the problem and include not only the terminology in the language units, but also the terminological compositions, saying
... Show More
Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.
In this paper we have been focus for the comparison between three forms for classification data belongs
... Show More
A new two-way nesting technique is presented for a multiple nested-grid ocean modelling system. The new technique uses explicit center finite difference and leapfrog schemes to exchange information between the different subcomponents of the nested-grid system. The performance of the different nesting techniques is compared, using two independent nested-grid modelling systems. In this paper, a new nesting algorithm is described and some preliminary results are demonstrated. The validity of the nesting method is shown in some problems for the depth averaged of 2D linear shallow water equation.
DBN Rashid, International Journal of English Linguistics, 2019 - Cited by 2
(2)