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 6 of 6 for “"Data-centric AI"”.
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Visual Representation Learning from Synthetic Data
… largely depends on the quality and quantity of data. Synthetic data presents unique advantages in terms of flexibility, scalability, and controllability. Recent advances in generative modeling have enabled the synthesis of photorealistic images and high-quality text, drastically increasing the …
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From data to model behaviour: A causal and empirical analysis of how data shapes the behaviour of language models
… remarkable capabilities, yet their behaviour remains difficult to predict and understand. A central challenge is that these models are shaped not only by their architectures or training algorithms, but fundamentally by their training data---what examples they see, how those examples are …
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Scalable Data Paradigms for Steering General-Purpose Language Models
Pretrained Language Models (LMs) have demonstrated remarkable general-purpose capabilities by encoding vast amounts of knowledge from the internet. However, effectively steering these models to serve diverse downstream applications, such as following instructions, chatting with users, using tools, …
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TOWARDS RELIABLE AI UNDER DISTRIBUTION SHIFTS: A DATA-CENTRIC PERSPECTIVE
… often rely on spurious correlations in the training data, leading to performance degradation and unreliability when processing inputs under distribution shifts. This thesis systematically studies the robustness to distribution shifts for ML models from a data-centric perspective. First, we …
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USING ARTIFICIAL INTELLIGENCE FOR DETECTING DISCRIMINATORY LANGUAGE
The rapid expansion of generative AI and large language models (LLM) has transformed how individuals and institutions communicate online. While these systems offer powerful capabilities for understanding natural language and generating natural language text, their ability to reliably detect …
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Enhancing Robustness and Interpretability in Computer Vision AI
L'abstract è presente nell'allegato / the abstract is in the attachment