Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 56 for “"Retrieval-Augmented Generation"”.
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Efficient retrieval-augmented generation
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-09-16 without embargo terms
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Improving Question Answering Systems with Retrieval Augmented Generation
… high computing resources. On the other hand, retrieval augmentation has been used to tackle knowledge-intensive tasks and proven by recent studies to be effective when coupled with LLMs. In this thesis, we explore Retrieval-Augmented Generation (RAG), a framework to augment generative LLMs …
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Enhancing Retrieval Augmented Generation Through Robust Information Retrieval
Retrieval-Augmented Generation (RAG) is a popular technique for grounding the responses of Large Language Models (LLMs). RAG works by extending Information Retrieval (IR) to incorporate LLMs that generate responses based on retrieved information and a query. RAG is commonly used within the field of …
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Improving speculative retrieval-augmented generation via verifier scoring
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms
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An end-to-end benchmarking framework for retrieval-augmented generation systems
… prototypes to production-grade services, Retrieval-Augmented Generation (RAG) has emerged as the de facto paradigm for mitigating hallucinations and incorporating up-to-date knowledge. While the accuracy of RAG systems has been extensively studied, the system performance—specifically …
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SPIRAL: Iterative Subgraph Expansion for Knowledge-Graph Based Retrieval-Augmented Generation
… prompt fails to anchor them to verifiable facts. Retrieval-augmented generation (RAG) mitigates this risk, yet existing graph-based retrievers either return bloated neighborhoods or incur prohibitive latency on large knowledge graphs (KGs). We introduce SPIRAL—Supervised Prior + Iterative …
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DART-RAG: Dynamic Agentic Replanning for Trustworthy Retrieval-Augmented Generation in Scientific QA
Η Παραγωγή Επαυξημένη με Ανάκτηση (RAG) αποτελεί μια πολλά υποσχόμενη προσέγ- γιση για τη θεμελίωση των Μεγάλων Γλωσσικών Μοντέλων (LLMs) σε εξωτερική γνώση, αλλά τα τρέχοντα πλαίσια συστημάτων με ένα ή πολλαπλούς πράκτορες δυσκολεύονται με επιστημονικά ερωτήματα που απαιτούν συλλογιστική πολλαπλών …
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Retrieval-Augmented Generation for Large Language Models: Enhancing Applied Economic Reasoning and Forecasting
… crucial. This thesis investigates the role of Retrieval-Augmented Generation (RAG) as a scalable solution to these limitations by injecting external knowledge at inference time. RAG enables the integration of dynamic, unstructured data sources to refine predictions and contextualize outputs …
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AI Retrieval-Augmented Generation (RAG) System with Engineering Document Information Extraction for Employee Development
… model (LLM) support systems that utilize retrieval-augmented generation (RAG) to enhance employee effectiveness in trouble-shooting on a manufacturing production line. The RAG-augmented LLM tool is designed to ex-tract relevant data from proprietary engineering documents, including …
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A Large Language Model and Retrieval-Augmented Generation System to Assist with Undergraduate Academic Advising
… hosted large language model leveraging a modern retrieval augmented generation pipeline in order to guarantee the language model generates the correct advising information for each student. Our RAG pipeline uses Qwen3.6:27b as the main LLM to generate responses, and a fine-tuned variant of …
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Integrating Open-Source Retrieval-Augmented Generation with Large Language Models for Business, Market and Responsibility Insights
… investigates the integration of open-source retrieval-augmented generation (RAG) with large language models (LLMs) on the Databricks platform. The aim is to provide advanced insights in the fields of business, market, and responsibility intelligence. The research explores combining RAG and …
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The Illinois Retrieval Benchmark : A scalable framework for characterizing retrieval-augmented generation via automated fact-checking
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms
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A retrieval augmented generation fine-tuned LLM model for refactored code recommendations to mitigate Java lock contention performance faults
… thesis presents a novel approach that combines Retrieval Augmented Generation (RAG) with a fine-tuned LLM model for refactored code recommendation aimed at reducing lock-contention performance faults in Java applications. The RAG-based fine-tuned model combines the strengths of contextual …
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Leveraging Retrieval-Augmented Generation, Prompt Engineering, and Vision Language Models for Surface Defect Classification and Root Cause Analysis in Manufacturing
… the integration of Vision Language Model (VLM)s, Retrieval-Augmented Generation (RAG), and structured prompt-engineering strategies to enhance surface defect classification and Root Cause Analysis (RCA) in manufacturing. The research examines whether generative and multimodal Artificial …
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Analyzing Risks in Voluntary Forest Carbon Offsets Using Open Data: A Hybrid Framework Integrating Retrieval-Augmented Generation in LLMs and Geospatial Analytics
The credibility of voluntary carbon markets hinges on the quality of carbon offset projects, particularly in forestry and land-use sectors where claims of additionality and emissions reductions are often disputed. This paper introduces a novel, open-source approach to evaluating carbon offset …
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Evaluating the Effect of Domain-Specific Large Language Models on Question and Response
… seeks to quantify the benefits of one approach, Retrieval Augmented Generation. The study uses a collection of questions across several topics with known reference answers. The context for these questions is used to assemble a study corpus. Responses are generated by both a standard Large …
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Incorporating LLM-based Interactive Learning Environments in CS Education: Learning Data Structures and Algorithms using the Gurukul platform
… coding platform incorporating dual features - Retrieval Augmented Generation and Guardrails. Gurukul's practice feature provides a hands-on code editor to solve DSA problems with the help of a dynamically Guardrailed LLM to prevent explicit code solutions. On the other hand, Gurukul's Study …
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QuOTE: Question-Oriented Text Embeddings
… Text Embeddings), a novel enhancement to retrieval- augmented generation (RAG) systems, aimed at improving document representation for accurate and nuanced retrieval. Unlike traditional RAG pipelines, which rely on embed- ding raw text chunks, QuOTE augments chunks with hypothetical …
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SensorsConnect: World Wide Web for Internet of Things
… the Large Language Models (LLM) models and Retrieval Augmented Generation (RAG) techniques. It also introduces the IoT-Retrieval Augmented Generation Search Engine (IoT-RAG-SE) and deploys it as an agent within IoT-ASE. Furthermore, it discusses a use-case scenario where IoT-ASE is …
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Augmenting Multi-modal Question Answering Systems with Retrieval Methods
… domain-specific knowledge and mitigating the generation illusion inherent in large language models. This thesis explores the integration of retrieval-augmented generation (RAG) into multi-modal question answering (QA) systems as a solution to these challenges. By leveraging external knowledge …
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