2024· Swiss Text Analytics Conference· pp. 163· 0 citations
Computer Science
TL;DR
The adesso Intelligent Agent describes a scalable and customizable RAG-Framework that accelerates development and deployment of functioning systems while allowing to rapidly address current and future challenges such as privacy, compliance, and trustworthiness or the expanding needs from business or environment.
An in-depth analysis of the evolution of Naïve RAG to Modular and Advanced RAG models, and the introduction of new innovations, such as self-reflection, dense vector recovery, and the use of different models.
Mallikarjunarao Sunke, S. Gudi, Sriharsha Gudi· International Journal for Re...· 0 citations
Large Language Models (LLMs) have demonstrated remarkable fluency and versatility across natural language tasks but remain fundamentally limited by their static knowledge and susceptibility to hallucinations, especially in domains requiring up to date or attribute grounded information. Retrieval Augmented Generation (R...
Meghana Sunil, V. Shravya, Shravan Venkatraman et al.· 0 citations
This paper presents a Hebrew-first local LLM chat agent that combines Retrieval-Augmented
Generation (RAG), citation-aware document answering, controlled web search, and full right-toleft (RTL) user interaction. Unlike cloud-only assistants, the default response path operates
locally, supporting privacy, predictable op...
Michael Sirkovich, M. Domb· International journal of adv...· 0 citations
Retrieval-Augmented Generation (RAG) is a sophisticated approach employed to enhance the efficiency of Large Language Models (LLMs). Most of the existing LLMs primarily rely on pre-trained data, which can be either obsolete or insufficient at times, hence providing suboptimal outcomes. To mitigate this problem, RAG beg...
Asker Shariff Subahan, S. Khan, Sourav Sarkar et al.· 2026 International Conferenc...· 0 citations
Generative AI is helping organizations tap into their data in new ways, with retrieval-augmented generation (RAG) combining the strengths of large language models (LLMs) with internal data for more intelligent and relevant AI applications. The author harnesses his decade of ML experience in this book to equip you with...
Keith Bourne· 8 citations· ⚡1
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.