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 35 for “"Prompt Engineering"”.
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Safeguarding sensitive data: prompt engineering for Gen AI
… This dissertation investigates the role of prompt engineering as a strategic intervention to mitigate GenAI's data reconstruction risks. By systematically exploring how tailored prompting techniques can influence AI outputs, this research aims to develop a robust framework for secure GenAI …
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Improving medical report generation and evaluation through prompt engineering
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01
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Study of Output and Behavior of LLMs Using Confidence Framing in Prompt Engineering
<p>While prompt engineering is pivotal for shaping Large Language Model (LLM) outputs, the impact of confidence framing on behavioral calibration remains underexplored. This study investigates the ways in which psychological framing, utilizing techniques such as capability praise, role …
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SAMPLS: A prompt engineering approach using Segment-Anything-Model for PLant Science research
… its zero-shot learning capability and whether prompt engineering can reduce the effort and time consumed in dataset annotation, facilitating a semi-automated training process. Our proposed method improved the detection rate of cells and reduced the error rate as compared to state-of-the-art …
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The Impact of LLMs Usage on Learning Outcomes for Software Development Students: A Focus on Prompt Engineering
… learning outcomes, (2) the influence of prompt engineering skills on this relationship, and (3) instructors' perceptions on these relationships. Quantitative data were collected from 159 students across two Saudi universities using a structured online survey with sections covering …
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Leveraging Retrieval-Augmented Generation, Prompt Engineering, and Vision Language Models for Surface Defect Classification and Root Cause Analysis in Manufacturing
… 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 Intelligence (AI) systems can deliver accurate, explainable, …
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Blueprinting AI Economics: Cost Assessment Framework for Business Stakeholders to Navigate Key Aspects in Prompt Engineering, Prompt Automation, and Fine-tuning LLMs
… the cost implications of fine-tuning, prompt engineering, and prompt automation techniques. By offering a systematic approach to evaluating the trade-offs between performance, cost, and societal impact, this research seeks to advance the practical and sustainable adoption of LLMs across …
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Quantifying Gender Bias in Large Language Models: When ChatGPT Becomes a Hiring Manager
… from their training data and investigate prompt engineering as a bias-mitigation technique. Our findings suggest that for a given resumé, an LLM is more likely to hire a candidate and perceive them as more qualified if the candidate is female, but still recommends lower pay relative to …
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Automating the screenplay : the creative and technical viability of AI in screenwriting.
… framework integrating AI agents, structured prompt engineering, and advanced memory retention techniques is proposed and implemented. Comparative analysis demonstrates that this innovative approach enhances AI's capabilities as an interactive, collaborative storytelling partner, offering …
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Inference of Cyber Threats, Vulnerabilities, and Mitigations to Enhance Cybersecurity Simulations
… and more effectively analyze them. We find that prompt engineering in large language models improves performance in edge classification within BRON. We in addition explore these inferences in practice, by modeling the interaction between cybersecurity attackers and defenders on a given network in …
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Improving Introductory Computer Science Students’ Programming Process When Using a Generative AI Tutor (PyTutor)
… process while using PyTutor? (2) How can prompt engineering of PyTutor’s system prompt be leveraged to improve AI Chat response quality with respect to: (a) reducing the amount of code revealed in the answer, (b) improving the conciseness of responses, and (c) having the AI chat give the …
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Minimalist Approach to End-to-End Vision Language Navigation with Multi-Modal Foundation Model Features
… (VLN) approaches leverage large models, prompt engineering, and/or explicit reasoning for instruction interpretation and agent guidance. We introduce MiniNav, a minimalist framework employing frozen vision-language foundation models as patch-wise feature extractors, avoiding data and …
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Automated goal model generation from user stories using Large Language Models
… goal model generation through multi-step prompt engineering. LLMs extract intentional elements—goals, tasks, actors, and resources—and generate Goal-oriented Requirements Language (GRL) models compatible with tools like jUCMNav. The study evaluates GPT-4, Llama, and Cohere, focusing on …
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Simulating Economic Experiments Using Large Language Models: Design and Development of a Computational Tool
… the impact of parameters such as temperature and prompt engineering to determine their influence on results. The homo silicus library provides researchers with a cost-effective method to iterate on projects without extensive resources or specific participant recruitment. This research contributes …
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Layered Unlearning for Adversarial Relearning
… that makes them easy to bypass through prompt engineering or relearning. Recent results suggest that post-training induces shallow contextdependent “circuits” that suppress specific response patterns. This could be one explanation for the brittleness of post-training. To test this …
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Rethinking the Evaluation of Compositional Reasoning for Modern VLMs
… of attributes, relations, and word order. This prompts a crucial question: have VLMs effectively tackled the CR challenge? Our conjecture suggests that existing CR benchmarks may not adequately push the boundaries of modern VLMs due to their reliance on a negative text generation pipeline. …
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Development and Evaluation of an LLM-Based Tool for Automatically Building Web Applications
… to develop an application through an iterative prompt refinement process. We argue that the case study illustrates the importance of concept-driven prompt engineering and offer guiding principles for designing effective prompts. Furthermore, this thesis contributes improvements to the Kodless …
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Towards an Informative Recommender System
… integrity. Finally, we present Auto-Guided Prompt Refinement (AGP), a dynamic framework that refines user profiles based on ranking feedback without manual prompt engineering. Extensive experiments on multiple real-world datasets validate the effectiveness of the proposed techniques. …
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ResearchBuddy AI: LLM-Powered Assistant
… for structured research paper summarization, prompt engineering for flexible summarization of variable formats of GitHub READMEs, and Retrieval-Augmented Generation (RAG) for context-aware question answering over domain-specific documents. The research explains model selection through …
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Topic Modeling for Heterogeneous Digital Libraries: Tailored Approaches Using Large Language Models
… Language Models (LLMs), such as GPT-4, using prompt engineering to augment traditional topic models, refining and interpreting their outputs without replacing them. The framework was tested on a large corpus of ETD metadata, including through preliminary testing on a small subset. Quantitative …
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