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95 results for “Language Models”
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Research ArticleOpen accessIn the keywordsContext Tamil Llama-QA: A Question and Answering Framework for Semantic Information Retrieval Using Tamil Large Language ModelJeevit Davidson S., M. MuraliThe Question Answering System (QA) is essential for effectively retrieving and providing relevant information, and its performance is heavily reliant on the efficiency of information retrieval mechanisms. As the volume of information within the corpus continues to grow, the complexity of generating accurate and pertinent answers also increases substantially. This challenge is particularly significant when designing QA systems for regional … …Journal of Computer Science, Vol. 22, Issue 10 · 7 Oct 2026 · 442 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Conceptual Framework for Efficient and Sustainable Pruning Techniques in Deep Learning ModelsNyalalani Smarts, Rajalakshm Selvaraj, Venumadhav KuthadiThis research paper proposes a conceptual framework and optimization algorithm for pruning techniques in deep learning models, its focus is on key challenges such as model size, computational efficiency, inference speed and sustainable technology development. The aim of the framework is to transition from large neural networks to sparse, efficient models, indicating the benefits of pruning in improving model scalability … …Journal of Computer Science, Vol. 21, Issue 5 · 26 Apr 2025 · 5,268 accessesView PDFCite
Research ArticleOpen accessIn the abstractAddressing Emergency Communication Challenges: Deep Learning Solutions for the Speech and Hearing- ImpairedPoornima B V, Srinath S et al.Emergency communication plays a very important role in ensuring that help reaches people promptly and safely in case of any emergency. However, the biggest problem faced by those who cannot speak and hear properly is to convey their message clearly and understand others. In this regard, the proposed research work focuses on recognizing emergency gestures made in the Indian Sign … …Journal of Computer Science, Vol. 22, Issue 5 · 1 Jun 2026 · 1,063 accessesView PDFCite
Research ArticleOpen accessIn the abstractHindi Poetry Translation Using Neural Machine TranslationPragya Tewari, Anurag Singh BaghelNeural Machine Translation (NMT) has become an essential tool in Natural Language Processing (NLP), enabling the automatic translation of text across languages. However, translating poetry remains a relatively unexplored and complex task. Unlike general text, poetry carries multiple layers of meaning, emotion, rhythm, and cultural nuance, making it difficult to capture in another language through standard translation techniques. This study … …Journal of Computer Science, Vol. 22, Issue 1 · 16 Feb 2026 · 1,773 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassifcation of Social Media Posts X For Mental Health Symptoms Identification Using NLP Techniques and Transformers ModelAndika Dwi Asmoro Wicaksono, RojaliThe increasing use of social media has enabled large-scale analysis of user-generated content to monitor mental health trends. This study focuses on sentiment prediction of mental health-related posts on platform X using transformer-based models, specifically IndoBERT, DistilBERT, and IndoRoBERTa. The goal is to evaluate the effectiveness of these models in classifying social media posts into positive, negative, and neutral sentiment … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,851 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluating Machine Translation for Domain Specific Low-Resource Nepali-English Language Pairs: The Impact of Tokenization on Statistical and Neural TechniquesAmit Kumar Roy, Bipul Syam PurkayasthaIn the modern era, the field of Machine Translation (MT) has seen a significant shift towards Neural Machine Translation (NMT) techniques, which have surpassed traditional Statistical Machine Translation (SMT) models in terms of the quality of translation. Despite this, the efficacy of these techniques may differ based on the language combination in consideration. While SMT is somewhat more flexible in … …Journal of Computer Science, Vol. 21, Issue 12 · 24 Jan 2026 · 1,920 accessesView PDFCite
Research ArticleOpen accessIn the abstractRecognizing Sign Language Gestures Using a Hybrid Spatio-Temporal Deep Learning ModelMeryem Cherrate, My Abdelouahed Sabri, Ali Yahyaouy, Abdellah AarabRecognizing gestures in American Sign Language (ASL) from video data presents significant challenges due to the intricate combination of hand gestures, facial cues, and body motion. In this work, we introduce a hybrid deep learning framework that integrates Convolutional Neural Networks (CNNs) for extracting spatial characteristics with Long Short-Term Memory (LSTM) networks for capturing temporal sequences. The model was trained … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,048 accessesView PDFCite
Research ArticleOpen accessIn the abstractFew-shot Fine-tuning of BERT Multilingual for Hindi Word Sense DisambiguationShailendra Kumar Patel, Rakesh Kumar, Anuj Kumar SirohiWord Sense Disambiguation (WSD) is a fundamental task in Natural Language Processing (NLP), addressing the challenge of identifying correct word meanings in context. This task is particularly complex for morphologically rich and resource-limited languages like Hindi, which exhibit significant lexical ambiguity compounded by limited availability of annotated corpora. To address these challenges, we propose a supervised approach combining the multilingual … …Journal of Computer Science, Vol. 21, Issue 11 · 26 Dec 2025 · 2,250 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Deep Learning Approach for Telugu Domain Identification with Multichannel LSTM-CNNBuddha Hari Kumar, Chitra Perumal, Inakoti Ramesh Raja et al.The vast growth of textual data has ushered into the limelight, a plethora of applications in information retrieval and natural language processing (NLP). Proper extraction of information from text is heavily dependent on recognizing the thematic content, which becomes crucial in the tasks of document summarization, information extraction, question answering, machine translation, and sentiment analysis. The great complexity of this … …Journal of Computer Science, Vol. 21, Issue 9 · 26 Nov 2025 · 2,395 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybridized BERT-Based Approach for Crime News Collection and Classification from Online NewspapersAshour Ali, Shahrul Azman Mohd Noah, Lailatul Qadri Zakaria, Saeed Amer Al AmeriCrime news analysis is crucial for understanding criminal activity, enhancing public safety, and informing policy decisions. The exponential growth and unstructured nature of online news articles, however, present significant challenges for efficient and accurate information extraction. This study aims to enhance the efficiency and accuracy of crime news data collection and classification through advanced Natural Language Processing (NLP) techniques and … …Journal of Computer Science, Vol. 21, Issue 9 · 16 Oct 2025 · 2,288 accessesView PDFCite