Abstract The interpretation of deep learning models is a challenge due to their size, complexity, and often opaque internal state. In addition, many systems, such as image classifiers, operate on low-level features rather than high-level[…]

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Abstract The demand for more sophisticated human-computer interactions is rapidly increasing, as users become more accustomed to conversation-like interactions with their devices. In this paper, we examine this changing landscape in the context of human-machine[…]

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Abstract Sometimes complex problems have simple solutions that buck conventional wisdom. The BitFunnel algorithm, which powers the Bing search engine, uses Bloom filters to process queries. With a small team and a blank page, we[…]

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Abstract Speech applications such as text-to-speech (TTS) or automatic speech recognition (ASR), must not only know how to read ordinary words, but must also know how to read numbers, abbreviations, measure expressions, times, dates, and[…]

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Abstract Despite much progress in neural models for joint vision and language understanding, current models are largely opaque and non-compositional.  Many language tasks are inherently compositional, and can be solved by decomposing them into modular[…]

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Abstract Discourse relations such as ‘contrast’, ‘cause’ or ‘evidence’ are often postulated to explain how humans understand the function of one sentence in relation to another. Some relations are signaled rather directly using words such[…]

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Abstract Unbabel is accelerating the shift towards a world without language barriers by enabling trustworthy, seamless and scalable translations between companies and their customers. In this talk we will show how we combine different Machine[…]

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