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5 articles for “LLM orchestration”
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Agentic AI-Driven Negative Emission Optimization: Large Language Model Orchestration and Quantum Annealing for Real-Time Carbon Capture Policy Simulation Beyond 1.5°C Thresholds
Abstract: The convergence of agentic artificial intelligence, large language model (LLM) orchestration, and quantum annealing presents a transformative paradigm for climate policy computation. This paper introduces Nega Optima a multi-agent computational architecture that integrates LLM-driven policy parsing, quantum annealing-based combinatorial optimization, and real-time integrated assessment model (IAM) feedback loops to simulate negative emission technology (NET) deployment strategies in a post-1.5°C overshoot scenario. Existing carbon capture optimization frameworks suffer from three systemic …
Published in International Journal of Climate Conditions · Vol. 3, Issue 2, 2026 · pp. 7–14 Read article
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Open-Source AI Agent Frameworks: A Comparative Performance Analysis
Abstract: The rapid growth of agentic AI has led to a diverse ecosystem of open-source frameworks for developing LLM-based agents. These frameworks differ in their approaches to state management, multi-agent coordination, tool orchestration, memory, and workflow execution. This paper presents a comparative analysis of prominent open-source AI agent frameworks, including LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, and related systems. The study synthesizes a common architectural model to identify the core components …
Published in Journal of Open Source Developments · Vol. 13, Issue 2, 2026 · pp. 23–33 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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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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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