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UBC Theses and Dissertations

NJM-Vis : applying and interpreting neural network joint models in natural language processing applications Johnson, David


Neural joint models have been shown to outperform non-joint models on several NLP and Vision tasks and constitute a thriving area of research in AI and ML. Although several researchers have worked on enhancing the interpretability of single-task neural models, in this thesis we present what is, to the best of our knowledge, the first interface to support the interpretation of results produced by joint models, focusing in particular on NLP settings. Our interface is intended to enhance interpretability of these models for both NLP practitioners and domain experts (e.g., linguists).

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