Search
47 articles for “large language models”
-
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 weaved into vital sectors such as self-driving cars, high-speed trading systems, and defense strategies, it has triggered a counterintuitive development in advanced cyber-attacks. This survey paper attempts to perform an in-depth technical analysis on “AI Attack Surface.” There are threats across three main vectors. Data Integrity Attacks focuses specifically examining ‘Clean Label’ poisoning and backdoor injection. Model Confidentiality Breaches is discussing the mathematics behind Model …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 Read article
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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 Read article
-
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 Read article
-
An Automation Detection for Sign Language Using AI
Abstract: Sign language recognition has attracted considerable interest because of its ability to facilitate communication between the deaf community and the public, thereby bridging communication divides. Traditional approaches to sign language recognition often face challenges in accurately interpreting the complex and nuanced gestures inherent in sign languages. However, recent advancements in deep learning techniques have shown promising results in improving the accuracy and robustness of sign language recognition systems. This study …
Published in Recent Trends in Programming languages · Vol. 11, Issue 1, 2024 · pp. 1–14 Read article
-
Database-Driven Energy Management in Electric Vehicles
Abstract: With the growing concern over environmental pollution, there is an increasing demand for sustainable and eco-friendly technologies. Among these, electric vehicles (EVs) have emerged as a promising alternative to conventional fossil-fuel-based transportation. However, as EV adoption accelerates, efficient energy management becomes critical to enhance vehicle performance, extend battery life, and ensure overall system reliability. This research presents a Database-Driven Energy Management System (DBEMS) that leverages real-time data from EV components …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 3, 2025 · pp. 19–24 Read article
-
Exploring Technologies for Extractive Text Summarization: A Review of Transformer and Reinforcement Learning Models
Abstract: In recent years, the size of information on the Internet has increased exponentially. Therefore, a solution is needed to transform large amounts of raw data into useful information the human brain can understand. Automatic Text Summarization (ATS) is a part of Natural Language Processing (NLP) that aims to take long texts and shorten them, keeping the most important information in a clear and easy-to-understand way. This research report explores methods …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 1–6 Read article
-
AI-based Drug Discovery-Revolutionizing Pharmaceutical Research
Abstract: The traditional drug discovery process is often costly, time-consuming, and prone to high failure rates. The advent of Artificial Intelligence (AI) has revolutionized this field by significantly enhancing efficiency, reducing costs, and improving success rates. AI-driven approaches, including machine learning (ML), deep learning (DL), and natural language processing (NLP), have transformed key areas such as drug target identification, molecular screening, lead optimization, and clinical trial design. AI models can analyze …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 30–44 Read article
-
Integrated Qualitative Response Assessment System
Abstract: Examinations for universities and yearboards are traditionally administered offline, with a significant number of students opting for subjective exams. This preference stems from the labor-intensive nature of evaluating subjective responses, which requires considerable time and effort from educators. Additionally, subjective grading can be influenced by the evaluator’s mood, leading to inconsistencies. In contrast, multiple-choice and objective questions are prevalent in entrance and competitive exams due to their ease of automated …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 18–24 Read article
-
Artificial Intelligence in Pharmacovigilance: Improving Drug Safety
Abstract: Artificial intelligence (AI) is revolutionizing pharmacovigilance (PV) by enhancing the detection, assessment, and prevention of adverse drug reactions (ADRs). This review examines how AI technologies – such as machine learning (ML), natural language processing (NLP), and big data analytics – tackle existing challenges in pharmacovigilance (PV), including issues like underreporting, large data volumes, and inefficiencies in data processing. AI improves drug safety by automating data collection, enabling real-time adverse event …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 1–16 Read article
-
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
-
AI-Powered Pharmacovigilance: Revolutionizing Adverse Drug Reaction Detection, Reporting, and Future Perspectives-A Review
Abstract: Pharmacovigilance is very important in drug safety as it monitors, identifies and prevents adverse drug reactions (ADR). Conventional pharmacovigilance systems are usually limited by underreporting and delay in signal detection as well as the inability to scale up. The pharmacovigilance sphere is undergoing a seismic shift with the arrival of AI. The use of AI-driven tools, such as machine learning and natural language processing, is transforming how ADR detection is …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 01–07 Read article
-
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