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Exploring Question-Specific Rewards for Generating Deep Questions
YuxiXie, LiangmingPan, DongzheWang....
Published date-11/02/2020
QuestionGeneration
Recent question generation (QG) approaches often utilize the sequence-to-sequence framework (Seq2Seq) to optimize the log-likelihood of ground-truth questions using teacher forcing. However, this training objective is inconsistent with actual question …
Speaker anonymisation using the McAdams coefficient
JosePatino, NataliaTomashenko, MassimilianoTodisco....
Published date-11/02/2020
SpeakerRecognition
Anonymisation has the goal of manipulating speech signals in order to degrade the reliability of automatic approaches to speaker recognition, while preserving other aspects of speech, such as those relating …
Diverse Image Captioning with Context-Object Split Latent Spaces
ShwetaMahajan, StefanRoth....
Published date-11/02/2020
ImageCaptioning, LatentVariableModels
Diverse image captioning models aim to learn one-to-many mappings that are innate to cross-domain datasets, such as of images and texts. Current methods for this task are based on generative …
Classification of Periodic Variable Stars with Novel Cyclic-Permutation Invariant Neural Networks
KemingZhang, JoshuaS.Bloom....
Published date-11/02/2020
FeatureEngineering, TimeSeries
Neural networks (NNs) have been shown to be competitive against state-of-the-art feature engineering and random forest (RF) classification of periodic variable stars. Although previous work utilising NNs has made use …
Emergent Communication Pretraining for Few-Shot Machine Translation
YaoyiranLi, EdoardoM.Ponti, IvanVulić....
Published date-11/02/2020
MachineTranslation, TransferLearning
While state-of-the-art models that rely upon massively multilingual pretrained encoders achieve sample efficiency in downstream applications, they still require abundant amounts of unlabelled text. Nevertheless, most of the world's languages …
MARNet: Multi-Abstraction Refinement Network for 3D Point Cloud Analysis
RahulChakwate, ArulkumarSubramaniam, AnuragMittal....
Published date-11/02/2020
RepresentationLearning, SemanticSegmentation
Representation learning from 3D point clouds is challenging due to their inherent nature of permutation invariance and irregular distribution in space. Existing deep learning methods follow a hierarchical feature extraction …