Abstract Text simplification aims to help audiences read and understand a piece of text through lexical, syntactic, and discourse modifications, while remaining faithful to its central idea and meaning. Thanks to large-scale parallel corpora derived[…]

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Abstract Over the last few years, deep neural models have taken over the field of natural language processing (NLP), brandishing great improvements on many of its sequence-level tasks. But the end-to-end nature of these models[…]

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Abstract Speaker verification (SV) is particularly challenging when the audio recordings are short in duration. Aiming at this, the Short-duration Speaker Verification (SdSV) challenge was organized in 2020, providing a framework for the evaluation of[…]

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Abstract Robotics@Google’s mission is to make robots useful in the real world through machine learning. We are excited about a new model for robotics, designed for generalization across diverse environments and instructions. This model is[…]

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Abstract Neural sequence generation systems oftentimes generate sequences by searching for the most likely sequence under the learnt probability distribution. This assumes that the most likely sequence, i.e. the mode, under such a model must[…]

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Abstract Data science in small medical datasets usually means doing precision guesswork on unreliable data provided by those with high expectations. The first part of this talk will focus on issues that data scientists and[…]

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