Year: 2024
Type: dissertation
Abstract: As language modelling has been progressing immensely towards genuinely useful applications driven by the increased availability of data and computational resources, our understanding and tools have not kept pace. On the one hand, it is usual for understanding to lag behind practice; on the other, often a steep price is to be paid for letting practice race too far ahead. \nA trained language model is the product of the interactions of data, optimization, the training objective, regularization, and the model itself, which not only provide rich veins for research individually but combine to create significant complexity, which hampers progress. This thesis pursues advances along these directions to solidify the footing and our understanding of the model and the process of its training in hopes of guiding research and applications towards better solutions.
Author: Melis, Gábor
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6997004338