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Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial Attacks
DenisEmelin, IvanTitov, RicoSennrich....
Published date-11/03/2020
AdversarialAttack, MachineTranslation, WordSenseDisambiguation
Word sense disambiguation is a well-known source of translation errors in NMT. We posit that some of the incorrect disambiguation choices are due to models' over-reliance on dataset artifacts found …
Learning 3D Dynamic Scene Representations for Robot Manipulation
ZhenjiaXu, ZhanpengHe, JiajunWu....
Published date-11/03/2020
3D scene representation for robot manipulation should capture three key object properties: permanency -- objects that become occluded over time continue to exist; amodal completeness -- objects have 3D occupancy, …
Control with adaptive Q-learning
JoãoPedroAraújo, MárioA.T.Figueiredo, MiguelAyalaBotto....
Published date-11/03/2020
OpenAIGym, Q-Learning
This paper evaluates adaptive Q-learning (AQL) and single-partition adaptive Q-learning (SPAQL), two algorithms for efficient model-free episodic reinforcement learning (RL), in two classical control problems (Pendulum and Cartpole). AQL adaptively …
Cross-Media Keyphrase Prediction: A Unified Framework with Multi-Modality Multi-Head Attention and Image Wordings
YueWang, JingLi, MichaelR.Lyu....
Published date-11/03/2020
Social media produces large amounts of contents every day. To help users quickly capture what they need, keyphrase prediction is receiving a growing attention. Nevertheless, most prior efforts focus on …
CharBERT: Character-aware Pre-trained Language Model
WentaoMa, YimingCui, ChengleiSi....
Published date-11/03/2020
LanguageModelling, QuestionAnswering, RepresentationLearning, TextClassification
Most pre-trained language models (PLMs) construct word representations at subword level with Byte-Pair Encoding (BPE) or its variations, by which OOV (out-of-vocab) words are almost avoidable. However, those methods split …
Amortized Variational Deep Q Network
HaotianZhang, YuhaoWang, JianyongSun....
Published date-11/03/2020
EfficientExploration, OpenAIGym, VariationalInference
Efficient exploration is one of the most important issues in deep reinforcement learning. To address this issue, recent methods consider the value function parameters as random variables, and resort variational …