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9 articles for “large language models”
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Understanding Sentiment Trends Through Zero-Shot and Few-Shot Learning Models
Abstract: The requirement for large, manually labeled datasets is one of the main barriers to applying sentiment analysis algorithms in specialized or rapidly evolving disciplines in the present natural language processing (NLP) landscape. This work investigates a paradigm shift from traditional fully supervised learning to data-efficient methods, specifically zero-shot learning (ZSL) and few-shot learning (FSL). This study uses the advanced capabilities of instruction-tuned large language models (LLMs), like GPT-4, to assess …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 01–08 Read article
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LLM-based Chatbot for Course-based Question Answering
Abstract: The “LLM-based Chatbot for Course-Based Question Answering” project addresses the pressing need for tailored and efficient learning tools in education. By using a state-of-the-art Large Language Model (LLM) with a diverse dataset, including textbooks, professor slides, and web scraping data, the chatbot offers accurate and contextually enriched responses to students' course-related queries. Using recent advances in language modeling, this work presents a Longformer-based Language Model (LLM) for constructing a smart …
Published in International Journal of Electronics Automation · Vol. 1, Issue 2, 2023 · pp. 30–41 Read article
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Agentic AI: Architectures, Types, Capabilities, Mathematical Equations and Governance in the Era of Autonomous Intelligence
Abstract: Agentic Artificial Intelligence (Agentic AI) represents a major advancement in the evolution of intelligent systems by enabling autonomous planning, decision-making, and action execution. Unlike traditional AI models, which are primarily reactive and designed to respond to predefined inputs, Agentic AI systems possess capabilities such as memory, reasoning, goal-oriented planning, tool integration, and dynamic adaptation to changing environments. These characteristics allow them to perform complex, multi-step tasks with minimal human intervention, …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 Read article
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Enhancing ABET Summative Direct Assessment with AI and Blockchain: A Framework for Personalized Learning and Secure Evaluation
Abstract: Accreditation Board for Engineering and Technology (ABET) emphasizes the achievement of specific measurable learning outcomes. However, conventional assessment methods often find it challenging to accurately capture the complexities of student learning and program effectiveness within the ABET framework. This study proposes a novel framework that enhances ABET summative direct assessment by integrating a carefully structured, weighted assessment system with the transformative potential of artificial intelligence (AI) and blockchain technologies. The …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 1, 2024 · pp. 28–42 Read article
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AI-News 4.0: Most Suitable LLM for UPSC Aspirants
Abstract: In recent years, the domain of interactive artificial intelligence (AI) has experienced a significant surge with large language models (LLMs) at the forefront of this evolution. AI systems, including those based on the GPT-3.5 framework, have been engineered to address various tasks such as responding to intricate inquiries, participating in conversations, and executing sophisticated natural language processing (NLP) operations. A prominent LLM, known for its adaptability, prompts an essential inquiry: …
Published in International Journal of Computer Science Languages · Vol. 2, Issue 2, 2024 · pp. 47–53 Read article
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Ethical Risks of Generative AI in Education: Challenges, Implications, and a Responsible Use Framework
Abstract: The rapid diffusion of generative artificial intelligence (AI) technologies in educational settings is reshaping how teaching, learning, and assessment are designed and enacted. Large language models and related generative systems offer powerful capabilities for content creation, personalized feedback, and instructional support, promising gains in efficiency and learner engagement. However, their growing use also introduces a complex set of ethical risks that challenge foundational educational values such as integrity, equity, transparency, …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 23–30 Read article
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Comprehensive Review of Moebius Syndrome: Clinical Landscape, Etiology, and Therapeutic Challenges
Abstract: Moebius syndrome, a rare congenital neuromuscular disorder, presents with non-progressive facial weakness, limited eye abduction, and diverse manifestations affecting cranial nerves. This comprehensive review explores its clinical landscape, emphasizing the need for extensive investigations into its elusive etiology and genetic underpinnings. The estimated prevalence is 1 in 250,000 live births, with sporadic cases prevailing. Initial symptoms, evident from birth, encompass difficulties in sucking, and feeding, and absent facial expressiveness. Beyond …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 1, 2024 · pp. 27–38 Read article
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Cyberattack Detection and Prevention Using Empowering AI Tools
Abstract: With more organizations entering the digital transformation sphere, the opportunities and risks in cyberspace have increased and gone up in levels of sophistication and occurrence. Many of these developments are attributed to the limits of existing cyber security solutions where addressing new threats requires advanced detection technologies and techniques. Cyber threats gained a new meaning and dimension with artificial intelligence (AI) coming into play in ways that supplement security systems …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Python's Applications in the Profession of Data Science
Abstract: Because of its ease of use, adaptability, and huge ecosystem of libraries, Python has become one of the most influential programming languages in the field of data science. Python is highly valued for its straightforward and versatile nature. This study delves into its various uses in data science, including tasks like data preprocessing, exploratory data analysis (EDA), statistical modeling, machine learning, and creating visualizations. Libraries like Pandas and NumPy make …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 23–30 Read article