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72 articles for “Large Language Models”
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Challenges, Risks, and Limitations of Vibe Coding in AI-Assisted Software Development
Abstract: Vibe coding is a new way of programming driven by LLMs (large language models). It helps developers write code from natural language. Developers can use prompts with artificial intelligence (AI) for code generation. AI assistants generate software directly through text. They can now perform tasks and understand user requirements. This process makes software development faster and easier for developers, but vibe coding has some drawbacks. Sometimes, it leads to security …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 · pp. 43–48 Read article
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Enhancing MRO Documentation Through Automated Translation of Non-Standard English to Simplified Technical English Using Offline LLMS
Abstract: Maintenance, Repair, and Overhaul (MRO) operations rely heavily on accurate and consistent documentation to ensure operational safety and compliance. However, the presence of non-standard English in technical documents often leads to ambiguity, misinterpretation, and inefficiencies in maintenance processes. This study presents an innovative solution that leverages an offline Large Language Model (LLM) to automatically translate non-standard English in MRO documents into standardized and technically precise language. By integrating predefined linguistic …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 9–15 Read article
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AI-Powered Prompt-to-Production Platform for Automated React Application Generation and Cloud Deployment
Abstract: The proliferation of large language models (LLMs) has fundamentally altered the landscape of automated software engineering. However, a significant “deployment chasm” persists between the generation of code artifacts and their realization as production-grade cloud applications. Traditional workflows are marred by the “DevOps Tax”: the high operational overhead of environment configuration, dependency resolution, and infrastructure provisioning. This paper presents a novel, technically adept architecture that bridges this gap through a unified …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 13, Issue 2, 2026 · pp. 1–16 Read article
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The Synthetic Media Threat: Generative AI and Deepfake Technology enabled Synthetic Media as Emerging Vectors of Cyberterrorism
Abstract: Cyberterrorism for most part of its academic and general understanding has been known and studied through conventional way such as a) malware deployment b)denial of essential services c) attacks on critical infrastructure, however with rapid changes in information technology as well as recent swift proliferation of generative artificial intelligence and deep fake technologies a completely new and unexamined dimension of threat vector has emerged, further expanding the threat areas are …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 2, 2025 Read article
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Hyper Personalization Using AI: Elevate Fitness
Abstract: In the modern era, many individuals find it challenging to prioritize their health and well-being due to busy lifestyles filled with work, academic, and personal obligations. Conventional fitness and nutrition programs often apply uniform strategies that overlook individual differences in body type, preferences, and goals. This lack of real-time feedback and contextual customization often leads to poor user engagement and unsatisfactory results over time. Elevate is a comprehensive, AI-powered fitness …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 10–21 Read article
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Shell-Based Agents as Execution Systems: A Survey of Command Generation, Verification, Security, State, and Recovery
Abstract: Shell environments are increasingly becoming interfaces through which AI agents interact with software and operating systems. Unlike conventional command generation systems, shell-based agents can interpret task objectives, plan multi-step actions, invoke terminal tools, observe system state, and adapt subsequent actions. These capabilities support software development, system administration, experimentation, and automated operations, but also introduce reliability and security challenges that cannot be assessed through command generation alone. This survey reviews 57 …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 2, 2026 · pp. 30–54 Read article
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Navigating the Dual Edge: A Comprehensive Technical Survey of Security, Privacy, and Countermeasures in the Era of Artificial Intelligence
Abstract: Artificial intelligence (AI) is seamlessly woven into vital sectors, such as self-driving cars, high-speed trading systems, and defense strategies; it has triggered a counterintuitive development in advanced cyberattacks. This survey paper attempts to perform an in-depth technical analysis of the “AI attack surface.” There are threats across three main vectors. Data integrity attacks focus specifically on examining “clean-label” poisoning and backdoor injection. Model confidentiality breaches discuss the mathematics behind model …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 · pp. 01–06 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 · pp. 01–14 Read article
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AIducate: Your Smart Tutor–A Survey
Abstract: The ongoing “datafication” of our social reality has led directly to the emergence of new data-driven business models across various sectors, including education. As a result, the market for educational services is rapidly expanding. Educational technology (EdTech) companies are at the forefront, offering data-driven pedagogical solutions that are reshaping the landscape of learning. Despite the market's growth, few companies are harnessing the full potential of artificial intelligence (AI) and machine …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 25–30 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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Nyaya-AI ChatBot: AI-Powered Legal Assistance for India
Abstract: In today's fast-paced world, the rise in lifestyle related issues has led to a significant increase in case filings across various sectors, including health, finance, and legal matters. Modern lifestyles, characterized by poor dietary habits, sedentary behavior, and high stress levels, contribute to a myriad of health problems and legal disputes. A chatbot designed to provide legal advice in India could be a valuable resource for individuals unfamiliar with the …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 Read article
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AI Enabled Pharma Supply Chain Market
Abstract: Pharmaceutical supply chains are changing because of artificial intelligence (AI). The pharmaceutical industry has always had to deal with uncertainty. From the start of research to the final delivery of medicines to patients, it faces scientific risks, government rules, and supply chain problems. In recent years, these challenges have gotten worse because there is more drug shortage, political issues are messing up transportation, and regulators are asking for more openness …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 2, 2026 Read article
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TRACE: Tracking the Loss of Memory Provenance in LLM Agents
Abstract: AI agents that carry memory across sessions gain better personalization and decision-making, but this persistence opens a serious security gap. When an agent repeatedly condenses earlier interactions into compact “lessons,” the trail linking each lesson back to the interaction that produced it gradually fades. We term this effect Reflective Attribution Collapse (RAC): the progressive loss of provenance and forensic traceability that results from repeated memory reflection. Under RAC, a malicious …
Published in Journal of Advancements in Robotics · Vol. 13, Issue 2, 2026 · pp. 33–49 Read article
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Automated Math Solver Assist with LLM RAG
Abstract: The challenges of solving complex mathematical problems often hinder efficiency in various scientific and engineering domains. This project proposes an innovative solution to these challenges by integrating automated math solvers with large language model (LLM) retrieval-augmented generation (RAG). The proposed system aims to streamline mathematical problem-solving processes, offering a robust and precise tool for real-time recognition, classification, and solution generation. This work provides a novel method of automating the solution …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 25–30 Read article
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AI – Driven Smart Laboratory for Synthetic Organic Chemistry – A Literature Review
Abstract: The traditional chemistry laboratory is often subjective, time consuming and skill intensive that may lead to inconsistencies in the desired results. The advent of Artificial Intelligence (AI) and its speedy incorporation into the field of chemistry is transforming traditional synthetic laboratories into intelligent, automated systems that combine hardware, software and AI into a unified framework. This paper presents a comprehensive overview of AI – driven laboratory setup for organic synthesis, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 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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Developing Techniques for Controlling Different Aspects of Text Generation Such as Tone and Contents
Abstract: Large Language Models (LLMs) have shown excellent text creation quality in Natural Language Processing (NLP). However, LLMs have to satisfy ever-more-complex standards in real-world applications. LLMs are supposed to meet specific user goals, like as mimicking specific writing styles or producing material with poetic richness, in addition to eliminating inaccurate or objectionable content. Controllable Text Generation (CTG) techniques were developed in response to these diverse demands. They guarantee that outputs …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 34–39 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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Enhanced Sustainable Concrete Mix Design Using LLMs and Advanced Machine Learning Techniques
Abstract: Large Language Models (LLMs) are emerging as transformative tools in materials science, offering human-like reasoning, zero-shot problem solving, and the ability to integrate fuzzy laboratory knowledge with structured data. This study extends and reinterprets the original systematic benchmark for using LLMs in sustainable concrete design, particularly for Alkali-Activated Concrete (AAC). We introduce an enhanced, multi-model framework combining LLM-based inverse design, Random Forest regression, Gaussian Process Regression (GPR), and a lightweight …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 26–33 Read article
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Neuro-Symbolic Agentic AI for Autonomous Scientific Discovery: Integrating Deep Reinforcement Learning, Quantum Simulation, and XAI-Audited LLM Hypothesis Generation in Drug Target Identification
Abstract: The exponential growth of multi-omics data and the increasing complexity of disease-associated protein interactomes have rendered conventional drug target identification pipelines computationally and epistemologically inadequate. This paper presents the Neuro-Symbolic Agentic AI for Scientific Discovery (NS-AASD) framework, a unified architecture that cohesively integrates deep reinforcement learning (DRL) exploration strategies, variational quantum simulation (VQS) of protein conformational dynamics, and XAI-audited large language model (LLM) hypothesis generation within an autonomous scientific discovery …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 · pp. 15–24 Read article