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 48 for “"large language model (LLM)"”.
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All Therapies Are Equal - Unless You’re a Bot: Evaluating the Effectiveness of Four Therapy Schools for AI Chatbot Therapists
This thesis tests two design questions for Large Language Model (LLM) Chatbot Therapists: Which therapeutic school suits an LLM best, and does an explicit Theory-of-Mind (ToM) reflection improve outcomes? We prompted GPT-4.1-mini to act as eight therapists — CBT, Narrative, Psychodynamic, and SFBT, …
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Implicit pen annotation assisted by Large Language Models
… tool with a digital pen. It leverages a Large Language Model (LLM) (1) to infer the underlying purposes of the user’s annotations and (2) automatically generates annotations with the same purpose throughout the document. AnnotateGPT aims to alleviate the burdens of manual annotation, …
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FROM FAMILY INTERACTION TO DYNAMIC FEEDBACK:ADVANCES IN MANDARIN LANGUAGE LEARNING APPLICATIONS
… is vital as Singapore's second most spoken language, but pronunciation training remains underrepresented in learning. This thesis covers two Computer-Assisted Language Learning (CALL) projects enhancing Mandarin acquisition. The first focuses on a tablet app for children and parents, using …
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Toward automated requirements engineering: empirical and architectural foundations for structured parsing and knowledge discovery
… Engineering (RE) relies heavily on natural language, which is often vague, inconsistently structured, and difficult to automate reliably. This thesis presents TRAC-RE, a Traceable, Reliable, Auditable, and Contextual framework for automated requirements engineering. The framework consists of …
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AI Retrieval-Augmented Generation (RAG) System with Engineering Document Information Extraction for Employee Development
This paper explores the implementation of AI large language 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 …
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LLM-powered active learning for cost-effective text classification
This thesis presents an LLM-powered active learning framework for cost-effective text classification, addressing the challenge of potential LLM annotation errors while balancing annotation quality and model accuracy. Our methodology combines human and large language model (LLM) annotations using …
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Adaptive self-prompting in agentic LLM frameworks for embedded code fault detection
… investigates adaptive self-prompting in agentic large language model (LLM) frameworks for code fault detection in embedded systems. Traditional static analysis and existing LLM-based approaches often rely on fixed prompts and exhibit overconfidence, leading to misclassifications. To address these …
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Discovering and Detecting Tax Avoidance Using Natural Language Processing and Coevolutionary Algorithms
… through tax avoidance schemes such as the Installment Bogus Optional Basis strategy (iBOB). This thesis focuses on discovering and detecting iBOB schemes within a tax network by using a coevolutionary framework powered by two large language model (LLM) agents: a tax planner, which generates …
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A question to query LLM as a pipeline replacement in knowledge graph question answering systems
… complexity and costly inference passes over large vocabularies. This thesis presents a drop-in replacement for those modules: a fine-tuned large language model (LLM) that translates a natural-language question directly into an executable SPARQL query. We fine-tune instruction-tuned backbones, …
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The SpaseCroissant Oven: Automatic Metadata Generation For Open-Source Space Weather Datasets
… when attempting to preserve information about large ML-ready datasets, which are often derived from large scientific repositories belonging to organizations such as National Aeronautics and Space Administration (NASA). These major scientific repositories provide their own metadata standards, …
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Layered Unlearning for Adversarial Relearning
… fine-tuning, alignment, and unlearning, modify language model behavior and representations. We are particularly interested in the brittle nature of these modifications that makes them easy to bypass through prompt engineering or relearning. Recent results suggest that post-training induces …
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Rethinking the Evaluation of Compositional Reasoning for Modern VLMs
Recent advancements in modern Vision-Language Models (VLMs), comprising a visual encoder coupled with a Large Language Model (LLM) decoder, have demonstrated remarkable proficiency in Compositional Reasoning (CR). CR entails grasping the significance of attributes, relations, and word order. This …
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Study of Output and Behavior of LLMs Using Confidence Framing in Prompt Engineering
… 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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Preserving Human Autonomy in AI-Mediated Negotiations
… Drawing on datasets from a repository of large language model (LLM) prompts tested in simulated negotiation scenarios, this study employs a mixed-methods approach to evaluating AI’s efficacy in balancing efficiency with ethical imperatives in negotiation. Quantitative metrics (enumerating …
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Design considerations for an AI-prompted “Future-Self” video journaling tool to enhance self-efficacy
… The study aims to gain insights into a Large Language Model (LLM) that should be fine-tuned based on unique experiences, compare different styles of guided approaches, test metrics for self-efficacy and Future self-continuity feedback, and identify pain points for an efficient design. In …
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Understanding LLM Communictaion
The training of modern Large Language Models (LLMs) requires distributed computing across Graphics Processing Unit (GPU) clusters, where network communication efficiency critically impacts performance and cost. Existing profiling tools provide either high-level metrics or low-level timing data, but …
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The Impact of LLMs Usage on Learning Outcomes for Software Development Students: A Focus on Prompt Engineering
<p>This study investigates the impact of large language model (LLM) usage, specifically ChatGPT, on student learning outcomes in programming education. The research adopts a mixed-methods approach, combining quantitative survey data from students and qualitative interviews with instructors. The …
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Mediators: Participatory Collective Intelligence for Multi-Stakeholder Urban Decision-Making
… is abstracted as a multiplayer board game modeling the check-and-balance dynamics among stakeholders with differing values. Players are encouraged to balance short-term interests and long-term resilience, and evaluate the risks and benefits of collaboration. The system is implemented as a …
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Transforming Free-Form Sentences into Sequence of Unambiguous Sentences with Large Language Model
In the realm of natural language programming, translating free-form sentences in natural language into a functional, machine-executable program remains difficult due to the following 4 challenges. First, the inherent ambiguity of natural languages. Second, the high-level verbose nature in user …
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Assessing Bikeability in Virginia: A Comparison of CHATGPT-4o and Traditional Models
… Street View Images (SVIs) and deep learning models to assess street-level features associated with the cycling environment in Virginia. An image segmentation model, PixelLib, was used to extract the proportion of seven features, namely greenery, streetlights, roads, sidewalks, cars, sky, and …
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