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 “"Foundation Model"”.
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Robust foundation model for healthcare
… deep learning techniques to clinical predictive modeling, developing robust models for healthcare remains challenging due to several key obstacles: (1) data fragmentation, with patient health records scattered across multiple institutions; (2) data missingness, as records frequently contain gaps …
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Data curation for foundation model training
… the amount of data available for training these models was often limited, research aimed on improving the way these relatively small amounts of data could be used. More recently, this focus has shifted from iteration on the algorithms to iteration on the data itself. Techniques such as data …
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Human-centric trustworthy foundation model reasoning
… Advancements in AI have given rise to language models (LMs) being increasingly adopted in assisting information understanding and communication for different task settings. However, the potential that LMs can serve in supporting human communication is still hindered by important issues. As …
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A Foundation model for the practice of school psychology
1 PDF file (v, 212 pages)
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A Transformer-Based Foundation Model for Human Microbiome Analysis
… limitation, we report on the development of a foundation model pretrained on 13,524 human microbiome metagenomic samples. The model was then fine-tuned to predict the clinical status of the host. Our model was able to differentiate between healthy and diseased samples in 10-fold …
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Towards a foundation model for multi-modal and hyperspectral geospatial data
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-08-01
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Minimalist Approach to End-to-End Vision Language Navigation with Multi-Modal Foundation Model Features
… navigation (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 …
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Long-range Genomics Benchmark Technology and More
… bottleneck. With the goal of creating a genomics foundation model (FM), this paper aims to address challenges associated long range dependencies in genomics. Our survey encompasses modifications to the attention mechanism, the creation of a genomics long range benchmark (GLRB), and the evaluation …
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Bazinių mašininio mokymo modelių taikymas kvantinės chemijos duomenų analizei /
… it, this research explores the application of foundation machine learning models to analyze quantum chemistry data, specifically focusing on predicting molecular energy states accurately without sacrificing computational efficiency. The main problem addressed by this research is the accurate …
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Resource-Efficient Collaborative Training and Inference of Foundation Models in Edge-AI
… of Edge Artificial Intelligence (Edge-AI) and foundation models marks a transformative paradigm shift in the design of intelligent systems. Edge-AI enables computation to be performed closer to data sources and across distributed network edges, offering significant benefits in latency …
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In-Situ Testing of a Carbon/Epoxy IsoTruss Reinforced Concrete Foundation Pile
… computer program called Lpile; 2) a Winkler foundation model; and, 3) a simple analysis based on fundamental mechanics of materials principles. Both Lpile and Winkler foundation model predictions concluded that the IRC pile should hold approximately twice the load of the SRC pile. Applying …
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Composing Foundation Models for Decision Making
Recent advancements in conditional generative modeling have enabled models like DALLE and GPT-4 to generate high-resolution images and coherent text from brief prompts. However, developing a foundation model for decision-making is hindered by the scarcity and expense of collecting paired visual, …
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Biomolecular Simulations with Machine Learning Potentials
Computational modelling has become a key component of the drug discovery toolbox. Typically, these tools are driven by empirical forcefields, which are computationally efficient but approximate representations of the true quantum mechanical potential energy surface. Over the last several years, …
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Enhancing RNA Foundation Models via Secondary Structure Modelling
Genomic Foundation Models (GFMs) are reshaping our understanding of the code of life, yet their application to Ribonucleic Acid (RNA) is uniquely challenged by its functional dependence on complex structure. Modelling this intricate sequence-structure-function relationship represents a vital …
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Effects of Surface Microstructure on the Strength of Adhesively Bonded Structures
… geometry based on a ""beam on an elastic foundation"" model. The experimental observations established a direct relationship between the surface roughness of aluminum substrates and the fracture resistance of the aluminum-epoxy interface. This relationship provides guidance to tailor …
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Toward effective and generalisable machine learning for biosignal time series
… to real-world data. Moreover, most existing models for biosignal time series are developed and evaluated in-domain, where both training and testing are conducted on the same dataset or under the same data collection protocol. Therefore, such models often fail to generalise to new scenarios in …
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EFFORTS TOWARD TRUSTWORTHY MACHINE LEARNING: MITIGATING OVERCONFIDENCE, HALLUCINATION, AND MODALITY BIAS
… high-stakes domains. Despite strong performance, models remain prone to reliability issues such as overconfidence, hallucinations, and modality bias. This thesis addresses these challenges through post-hoc methods and targeted fine-tuning strategies. First, we mitigate overconfidence in …
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Grounding Time Series in Language: Interpretable Reasoning with Large Language Models
Can large language models (LLMs) classify time-series data by reasoning like a domain expert—if given the right language? We propose a method that expresses statistical time-series features in natural language, enabling LLMs to perform classification with structured, interpretable reasoning. By …
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Foundation Models for Protein Phenotype Prediction
… states, and perturbations. We present ProCyon, a foundation model for modeling, generating, and predicting protein phenotypes across five interrelated knowledge domains: molecular functions, therapeutic mechanisms, disease associations, functional protein domains, and molecular interactions. To …
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Exploring the Role of Foundation Models for Training Generalist Robot Learning Policies
… robot learning policies using large-scale foundation models. The first approach aims to use a video foundation model to generate task-conditioned synthetic demonstrations at scale from a single expert demonstration. The objective is to leverage these synthetic demonstrations as proxy for …
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