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Learning language variations in news corpora through differential embeddings


Authors:  CarlosSelmo, JulianF.Martinez, MarianoG.Beiró....
Published date-11/13/2020
Tasks:  WordEmbeddings

Abstract: There is an increasing interest in the NLP community in capturing variations in the usage of language, either through time (i.e., semantic drift), across regions (as dialects or variants) or …

Wisdom of the Ensemble: Improving Consistency of Deep Learning Models


Authors:  LijingWang, DipanjanGhosh, MariaTeresaGonzalezDiaz....
Published date-11/13/2020

Abstract: Deep learning classifiers are assisting humans in making decisions and hence the user's trust in these models is of paramount importance. Trust is often a function of constant behavior. From …

Enabling the Sense of Self in a Dual-Arm Robot


Authors:  AliAlQallaf, GerardoAragon-Camarasa....
Published date-11/13/2020

Abstract: While humans are aware of their body and capabilities, robots are not. To address this, we present in this paper a neural network architecture that enables a dual-arm robot to …

FastTrack: an open-source software for tracking varying numbers of deformable objects


Authors:  BenjaminGallois, RaphaëlCandelier....
Published date-11/13/2020

Abstract: Analyzing the dynamical properties of mobile objects requires to extract trajectories from recordings, which is often done by tracking movies. We compiled a database of two-dimensional movies for very different …

Automatic segmentation with detection of local segmentation failures in cardiac MRI


Authors:  JörgSander, BobD.deVos, IvanaIšgum....
Published date-11/13/2020

Abstract: Segmentation of cardiac anatomical structures in cardiac magnetic resonance images (CMRI) is a prerequisite for automatic diagnosis and prognosis of cardiovascular diseases. To increase robustness and performance of segmentation methods …

Re-framing Incremental Deep Language Models for Dialogue Processing with Multi-task Learning


Authors:  MortezaRohanian, JulianHough....
Published date-11/13/2020
Tasks:  LanguageModelling, Multi-TaskLearning, Part-Of-SpeechTagging

Abstract: We present a multi-task learning framework to enable the training of one universal incremental dialogue processing model with four tasks of disfluency detection, language modelling, part-of-speech tagging, and utterance segmentation …

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