Essays about: "Sensitive Language"
Showing result 1 - 5 of 72 essays containing the words Sensitive Language.
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1. A type-driven approach for sensitivity checking with branching
University essay from Göteborgs universitet/Institutionen för data- och informationsteknikAbstract : Differential Privacy (DP) is a promising approach to allow privacy preserving statistics over large datasets of sensitive data. It works by adding random noise to the result of the analytics. Understanding the sensitivity of a query is key to add the right amount of noise capable of protecting privacy of individuals in the dataset. READ MORE
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2. Vargen – ”en syndabock för större socioekonomiska problem” : en kritisk diskursanalys av nyhetsrapporteringen av varg på lokal och rikstäckande nivå
University essay from SLU/Dept. of Urban and Rural DevelopmentAbstract : Uppsatsens syfte är att kritisk granska och analysera nyhetsrapporteringen av rovdjursdiskursen för att urskilja hur olika maktstrukturer mellan stad och land syns och reproduceras i porträtteringen. Särskilt fokus ligger i den mediala bilden av landsbygd i vargfrågan där traditionella diskurser om landsbygd kan reproduceras snarare än utmanas i frågan. READ MORE
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3. Towards End-User Understanding: Exploring Explanations For Profanity Detection
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Current text classification models can accurately identify instances of specific categories, such as hate speech or bad language, but they often don’t provide clear explanations to the end user for their decisions. This can lead to confusion or mistrust in the results, especially in sensitive applications where the consequences of misclassification can be significant. READ MORE
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4. Towards Building Privacy-Preserving Language Models: Challenges and Insights in Adapting PrivGAN for Generation of Synthetic Clinical Text
University essay from Stockholms universitet/Institutionen för data- och systemvetenskapAbstract : The growing development of artificial intelligence (AI), particularly neural networks, is transforming applications of AI in healthcare, yet it raises significant privacy concerns due to potential data leakage. As neural networks memorise training data, they may inadvertently expose sensitive clinical data to privacy breaches, which can engender serious repercussions like identity theft, fraud, and harmful medical errors. READ MORE
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5. Exploring GPT models as biomedical knowledge bases : By evaluating prompt methods for extracting information from language models pre-trained on scientific articles
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Scientific findings recorded in literature help continuously guide scientific advancements, but manual approaches to accessing that knowledge are insufficient due to the sheer quantity of information and data available. Although pre-trained language models are being explored for their utility as knowledge bases and structured data repositories, there is a lack of research for this application in the biomedical domain. READ MORE