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28 articles for “Large language models (LLMs)”
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Smart Service Solutions AI: AI-driven Multimodal Search for Home Appliance Support
Abstract: The global home appliance services market is projected to reach USD 1,203.11 billion by 2032, driven by smart household appliances. Essential services like installations, maintenance, and repairs ensure optimal performance and longevity, leading to higher customer satisfaction and loyalty. The service station partner ecosystem is crucial for ongoing support and profitability. However, challenges such as identifying the right manuals, finding relevant parts, and providing accurate instructions must be addressed to …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 27–43 Read article
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MentaLLaMA: Advancing Mental Health Insights with Instruction-Finetuned Large Language Models
Abstract: The growing prevalence of mental health challenges in contemporary society has highlighted the urgent need for advanced, interpretable, and reliable artificial intelligence solutions that can support mental health assessment and intervention. In response to this need, this research introduces a novel collection of open-source, instruction-tuned large language models (LLMs) specifically designed to facilitate transparent and accurate mental health evaluations. Leveraging a newly developed dataset, which integrates multiple tasks and diverse …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 08–15 Read article
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Evaluating the Efficiency of LLMs-SA (Sentiment Analysis) via Social Media Texts
Abstract: Sentiment analysis (SA) is becoming popular in business and scientific communities as the processing of natural language (NLP), computational linguistics, text analytics, image-based processing or video- based processing is used in extracting and mining subjective information in the web, social network, etc. It is able to detect positive, negative or neutral information and can be selected to absorb polarity, sentiments, urgency and goals of mount importance. The majority of the …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 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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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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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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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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Confident but Wrong: A Lifecycle Analysis of Hallucination in Large Language Models Understanding AI's Confidence Problem
Abstract: A Large Language Model (LLM) is likely to produce sentences that are fluent and confident in many instances, but completely wrong. In many cases a Large Language Model (LLM) will produce a fluent and confident sentence that is completely incorrect. This review tries to analyze this phenomenon using the most recent literature regarding natural language generation, computational learning theory and benchmark experiments. The argument is that it is not a …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 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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A Review Study on CPU-Optimized Parameter-Efficient Fine-Tuning for Large Language Models to Increase Accuracy Using LoRA
Abstract: The fast proliferation of large language models (LLMs) has increased the need to optimize the process of fine-tuning, but the existing workflows that require a graphics processing unit (GPU) are still expensive, intensive, and unavailable to most researchers. This paper is driven by the desire to have a more cost-efficient and democratized version by examining a CPU-efficient implementation of parameter-efficient fine-tuning (PEFT) based on low-rank adaptation (LoRA). The major purpose …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 · pp. 32–38 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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Generative Artificial Intelligence with Emphasis on Large Language Models: Review and Current Trends
Abstract: Generative Artificial Intelligence deals with AI systems that generate new content, such as text, and images. It accomplishes this by using data patterns of texts and images that already exist. Generative AI began an era of major advancement in AI, producing more refined and human-like results. Large Language Models, LLMs, is a part of Generative AI with applications in Natural Language Processing such as text generation, translation, summarization, sentiment detection …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 40–46 Read article
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Reward-Aligned Reinforcement Learning from Human Feedback for Emotion-Sensitive Large Language Model Therapists: Balancing Empathetic Engagement, Boundary Safety, and Clinical Accountability
Abstract: The deployment of large language models (LLMs) in mental health therapy contexts introduces a critical alignment challenge: these systems must simultaneously cultivate genuine empathic rapport, observe clinically grounded safety boundaries, and remain auditable under institutional accountability frameworks. Existing reinforcement learning from human feedback (RLHF) pipelines optimize for a scalar reward signal that is demonstrably insufficient for the multi-objective, temporally extended nature of therapeutic conversation. This paper presents RA-RLHF-T (Reward-Aligned RLHF …
Published in International Journal of Tropical Medicines · Vol. 3, Issue 2, 2026 Read article
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LLM Evolution: Secrets and Disadvantages
Abstract: The advancement of large language models (LLMs) has initiated a significant transformation in artificial intelligence, with substantial effects on fields including natural language processing, machine learning, and human-computer interaction. This research examines the diverse improvements in LLMs, emphasizing significant milestones from early models such as GPT-2 to contemporary state-of-the-art designs. The investigation highlights the novel training methodologies, such as unsupervised learning and transfer learning, which have markedly improved the capabilities …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 1, 2025 · pp. 25–36 Read article
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Continuous Learning in Language Models: A Survey of Streaming Data Processing Techniques
Abstract: The integration of continual learning with Large Language Models (LLMs) and Natural Language Processing (NLP) represents a transformative step toward creating adaptive, intelligent systems capable of functioning effectively in ever-changing environments. Traditional LLMs are typically trained on large, pre-collected datasets, which limits their ability to evolve as new information emerges. Continual learning, in contrast, enables models to acquire new knowledge incrementally without the need for complete retraining, thereby supporting long-term …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 23–34 Read article
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Leveraging Large Language Models for Personalized Document Summarization and Question Answering: An Architecture for Stoner-Friendly Chatbots
Abstract: This study presents a detailed framework for developing personalized chatbots that utilize large language models (LLMs) to process and extract information from extensive documents while effectively responding to user inquiries. The proposed system is designed to mitigate information overload by employing advanced natural language processing techniques, leveraging technologies such as OpenAI, LangChain, and Streamlit. By integrating these tools, the framework enhances knowledge retrieval, simplifies document comprehension, and improves overall productivity. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 88–93 Read article
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Mindwell: A Psychological Guide for Well-being
Abstract: Mental health is a crucial aspect of overall well-being, yet access to professional therapy remains a significant challenge for many individuals due to various barriers, including cost, availability, and stigma. This research aims to develop an accessible and effective mental health therapy chatbot, named Mindwell Psychology, leveraging the power of large language models (LLMs) and state-of-the-art natural language processing techniques. The primary objective of this study is to create a …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 63–77 Read article
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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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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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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