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 130 for “"Large Language Model"”.
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Large language model for programming by example
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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Large Language Model Routing with Benchmark Datasets
There is a rapidly growing number of open-source Large Language Models (LLMs) and benchmark datasets to compare them. While some models dominate these benchmarks, no single model typically achieves the best accuracy in all tasks and use cases. With a new dataset, it can be difficult to determine …
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Bail Reform, Large Language Model Risk and Reasoning
… contains three studies. Each asks how rules or language change the choices people and machines make when outcomes are uncertain. The first study, written with Kiran John, evaluates California’s 2020 cashless bail reform. We use propensity score matching on arrestee records from the windows …
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Large Language Model Tools for Project-based Learning
… of artificial intelligence (AI), particularly large language models (LLMs), holds promise for addressing these challenges by en- hancing personalized learning, automating administrative tasks, and providing real-time feed- back. To ensure that these AI tools are sustainable and conducive to …
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Analysis of Memory Access Patterns for Large Language Model Inference
… tasks, while only a few focus on inference for large models. The training and inference workloads for the same type of model are quite different: in training, the task is to continuously update the weights matrices with knowledge gained from each training datum, while in inference, the workload …
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Comparative evaluation of conventional search architectures and large language model-based approaches
… nuance in more complex queries. In contrast, large language model (LLM)-based systems, including Gemini and chat generative pre-trained transformer (ChatGPT) with browsing, employ neural embeddings and generative reasoning to deliver contextualised and conversational outputs. While these …
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Enhancing the verifiability of large language model based medical question answering systems
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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Detect, Explain, Ground: A Sustainable Pipeline for Robust Large Language Model–Powered Agents
Large language models (LLMs) enable fluent dialogue but still suffer from critical breakdowns, such as incoherence, irrelevance, or factual inaccuracies (hallucinations). This thesis develops a sustainable, three-stage pipeline to detect, manage, and ground LLM-powered agents, enhancing their …
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LPC: Lossless parameter compression for deploying large language model inference on edge devices
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-03-28 without embargo terms
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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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A Large Language Model and Retrieval-Augmented Generation System to Assist with Undergraduate Academic Advising
… tackle this problem, we propose a locally 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 …
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On Passive-Scoping as a method for Large Language Model Robustness to Jailbreaks and Adversarial Examples
Artificial Intelligence (AI) and large language models (LLMs) not only present a challenge for adversarial robustness, but also the natural emergence of unwanted capabilities. Current approaches to safeguarding AI and LLMs predominantly rely on explicitly restricting known instances of these. …
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On the Provenance of Software Systems: Automating Software Traceability with Knowledge Graph and Large Language Model Synergy
… these are typically informal, heavy with natural language, and lack structured explainability. This work proposes that each artifact should be attended by a machine-readable, human-interpretable, extensible provenance record, implemented in the form of a knowledge graph, backed by well-established …
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Leveraging large language model embeddings to enhance diversity and mitigate the filter bubble effect in recommender systems
… the filter bubble by enhancing recommendation models using content-based embeddings produced by large language models (LLMs), which encode semantic information about items being recommended. The addition of semantic information — beyond the user interaction data that usually drives recommender …
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Evaluating the Effect of Domain-Specific Large Language Models on Question and Response
<p>Large Language Models have emerged to great fanfare in the Information Technology market. Business and Information Technology leaders are currently exploring ways to apply these models to assist their organizations in executing business processes and generating innovation. Software vendors, …
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Concept for a virtual assistant with an LLMbased multi-agent system to process user input in intralogistics
… virtual assistants that can interpret natural language instructions that are not predefined, understand context, and autonomously perform multi-step tasks across different technical systems. Insights from the literature review led to the hypothesis that such capabilities may be realised through …
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Efficient Knowledge Transfer and Adaptation for Speech and Beyond
… parameter-efficient adaptation, and multimodal modeling. First, we provide a comprehensive framework for class-incremental spoken language understanding, allowing models to incrementally learn new intents and entities while retaining previously acquired knowledge. Using knowledge distillation …
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Efficient LLM training and inference with contextual sparsity
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01
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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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