Deep Learning, NLP, NMT, AI, ML
Test Type Co-referent? Pass Rate & Total Tests Example test case and outcome for test case Anaphora and Exophora resolution Yes 47.1% (16/34) M1: …to boost the struggling insect’s numbers… [PASS] M2: the annual migration of the monarch butterfly… No
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Abstract While a number of works showed gains from incorporating source-side symbolic syntactic and semantic structure into neural machine translation (NMT), much fewer works addressed the decoding of such structure. We propose a general Transformer-based approach for tree and graph decoding based on generating a sequence of transitions, inspired by a similar approach that uses RNNs by Dyer et al. (2016). Experiments with using the proposed decoder with Universal Dependencies syntax on English-German, German-English and English-Russian show improved performance over […]
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In Our model, we generate representations of post message in three methods: tokenized syllables-level text through Bert4News, tokenized word-level text through PhoBERT and tokenized syllables-level text through XLM. We simply concatenate both this three representations with the corresponding post metadata features. This can be considered as a naive model but are proved that can improve performance of systems (Tu et al. (2017), Thanh et al. (
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AM LM WER [%] Dev2 Test 1 CNN-TDNNf Alb 14.1 15.5 2 Alb + Wiki 13.6 14.9 3 Alb + Giga 13.6 15.1 4 Alb + Wiki + Giga 13.5 15.0 5
Read moreWith the aim of assessing the quality of the trained SE models, we use several trigger word detection classifier models, reporting the impact of the SE module at WUW classification performance. The WUW classifiers used here are a LeNet, a well-known standard classifier, easy to optimize [13]; Res15, Res15-narrow and Res8 based on a reimplementation by Tang and Lin [26] of Sainath and Parada’s Convolutional Neural Networks (CNNs) for
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Introduction Working with variables in data analysis always drives the question: How are the variables dependent, linked, and varying against each other? Covariance and Correlation measures aid in establishing this. Covariance brings about the variation across variables. We use covariance to measure how much two variables change with each other. Correlation reveals the relation between the variables. We use correlation to determine how strongly linked two variables are to each other. In this article, we’ll learn how to calculate the […]
Read moreIf someone told me ten years ago when I was a freshly graduated bachelor of computer science that there would models that would produce multilingual sentence representation allowing zero-shot model transfer, I would have hardly believed such a prediction. If they added that the models would be total black boxes and we would not know why it worked, I would think they were insane. After all, one of the goals of the mathematization of stuff in science is to make […]
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Gradient descent is an optimization algorithm that follows the negative gradient of an objective function in order to locate the minimum of the function. A problem with gradient descent is that it can bounce around the search space on optimization problems that have large amounts of curvature or noisy gradients, and it can get stuck in flat spots in the search space that have no gradient. Momentum is an extension to the gradient descent optimization algorithm that allows the search […]
Read moreFrom a research point of view, games offer an amazing environment in which to develop new machine learning algorithms and techniques. And we hope, in due course, that those new algorithms will feed back not just into gaming, but into many other domains. Beyond the very technical machine learning techniques themselves, gaming is an environment in which we can explore the relationship between AI and people, and see how they can work in partnership. It’s a very rich environment in […]
Read moreHaving spent a big part of my career as a graduate student researcher and now a Data Scientist in the industry, I have come to realize that a vast majority of solutions proposed both in academic research papers and in the work place are just not meant to ship — they just don’t scale! And when I say scale, I mean handling real world uses cases, ability to handle large amounts of data and ease of deployment in a production […]
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