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28 articles for “Large language models (LLMs)”
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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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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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RoseRAG-Based Clinical Decision Support System for Precision Medication Safety
Abstract: Medication-related errors remain a major challenge in healthcare, contributing to adverse drug events, increased hospitalization rates, and substantial healthcare costs. Conventional Clinical Decision Support Systems (CDSS) primarily rely on rule-based mechanisms for identifying drug-related problems (DRPs), including drug–drug interactions, contraindications, dosing errors, therapeutic duplication, and medication omissions. Although effective in structured environments, these systems frequently generate excessive context-insensitive alerts, leading to alert fatigue and reduced clinical acceptance. Recent developments in …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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VeriSci—AI-Based Multi-Modal Research Assistant
Abstract: The exponential growth of scientific literature is a major bottleneck for academic researchers who want to efficiently discover, assess, and synthesize relevant scholarly knowledge. Traditional methods of literature review are heavily reliant on manual keyword searching, human screening, and subjective data extraction, making them time-consuming, susceptible to cognitive bias, and less effective as the tidal wave of information continues to grow. To overcome these limitations, this study introduces VeriSci, an …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 2, 2026 · pp. 20–27 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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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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Unmasking Hallucinations in Large Language Models Using Analysis of the LLAMA 2 Model and RAG Intervention
Abstract: The study describes the creation of a chatbot for financial trading called "TradeBot" and how it uses Retrieval Augmented Generation (RAG) to overcome the problem of producing false or unverifiable information, sometimes known as hallucinations. RAG allows the chatbot to refer to an external data source in addition to its taught knowledge, which increases the accuracy of its responses. The NCFM (NSE's Certification in Financial Markets) book was integrated as …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 76–86 Read article
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Methodology for Evaluating Code Synthesis in Large Language Models: ChatGPT and Copilot: A Review
Abstract: The authors introduce a comprehensive framework to assess the code-generation capabilities of large language models, focusing on ChatGPT and Copilot through a benchmark suite of 25 program synthesis tasks. Their main goal was to show why making proper comparisons is important, they did not focus on choosing the newest models, since they keep changing frequently. The critique examines how the methodology addresses both functional and non-functional aspects of code. In …
Published in Recent Trends in Programming languages · Vol. 12, Issue 3, 2025 · pp. 01–07 Read article