Arijit Ray

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This paper presents the Virginia Tech system that participated in the CoNLL-2016 shared task on shallow discourse parsing. We describe our end-to-end discourse parser that builds on the methods shown to be successful in previous work. The system consists of several components, such that each module performs a specific sub-task, and the components are(More)
Visual Question Answering (VQA) is the task of answering natural-language questions about images. We introduce the novel problem of determining the relevance of questions to images in VQA. Current VQA models do not reason about whether a question is even related to the given image (e.g. What is the capital of Argentina?) or if it requires information from(More)
Cover song identification is a trivial problem for human beings. A human can easily identify whether a song is a cover of another or not, without using much effort. However, cover song identification is not an easy task for machines , as the numerical audio data differs significantly. Since a major goal of Machine Learning and Artificial Intelligence is to(More)
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