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 10 of 10 for “"Pre-trained language model"”.
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Idiomatic sentence generation and paraphrasing
Idiomatic expressions (IE) play an important role in natural language, and have long been a “pain in the neck” for NLP systems. Despite this, text generation tasks related to IEs remain largely under-explored. In this study, we propose two new tasks of idiomatic sentence generation and paraphrasing …
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Empower entity set expansion via language model probing
… and several negative class names by probing a pre-trained language model, and further score each candidate entity based on selected class names. Experiments on two datasets show that our framework generates high-quality class names and outperforms previous state-of-the-art methods significantly.
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Pairwise embedding for event coreference resolution
… in information extraction research and natural language understanding areas. Recently, the pre-trained language models emerging in modern Natural Language Processing (NLP) community provide a new perspective of solving classical NLP tasks. This thesis presents a novel, extensible, and …
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Annotation-free location mention mining from text corpora
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms
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The Role of Precedent in Computational Models of Law
In common law countries, due to the doctrine of precedent, lawyers need to consider a body of case law which grows with each court decision. As a result, the complexity and number of documents a lawyer should be familiar with for each new decision increases rapidly over time. Robust models of …
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Towards Deployable Robust Text Classifiers
… for decades as a fundamental task in natural language processing. Deploying classifiers enables more efficient information processing, which is useful for various applications, including decision-making. However, classifiers also present challenging and long-standing problems. As their use …
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Deep learning applied to the assessment of online student programming exercises
… provision of qualitative feedback. Four tasks: language modeling, detecting idiomatic code, semantic code search, and predicting variable names are considered in detail. First, deep learning models are applied to the task of language modeling source code. A comparison is made between the …
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Stylistic Dialogue Generation Based on Character Personality in Narrative Films.
… in this document, we propose an approach using a pre-trained language model, in order to explore the potential of generating dialogues with embedded narrative-related features within the context of narrative films. In this approach, three different embedding methods are leveraged to incorporate …
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Machine learning for social event analysis : public perceptions during COVID-19 and collective violence in South Africa
… on any social event. The advancement in natural language processing, computing power, and pretrained language models has given rise to advanced text analysis. Computational analysis of social media complements the sociology framework that theorises human behaviour during a public health crisis or …
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Uncertainty Estimation on Natural Language Processing
… books, reports, and more. Consequently, Natural Language Processing (NLP) has garnered widespread attention. This technology empowers us to undertake tasks like text classification, entity recognition, and even crafting responses within a dialogue context. However, despite the expansive utility …