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  • PaperHighlights
  • 2019
    • 03
      • Not All Contexts Are Created Equal Better Word Representations with Variable Attention
      • Learning Context-Sensitive Word Embeddings with Neural Tensor Skip-Gram Model
      • Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
      • pair2vec: Compositional Word-Pair Embeddings for Cross-Sentence Inference
      • Contextual Word Representations: A Contextual Introduction
      • Not All Neural Embeddings are Born Equal
      • High-risk learning: acquiring new word vectors from tiny data
      • Learning word embeddings from dictionary definitions only
      • Dependency-Based Word Embeddings
    • 02
    • 01
  • 2018
  • 2017
  • Paper Title as Note Title
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  1. 2019

03

Not All Contexts Are Created Equal Better Word Representations with Variable AttentionLearning Context-Sensitive Word Embeddings with Neural Tensor Skip-Gram ModelApproximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNetpair2vec: Compositional Word-Pair Embeddings for Cross-Sentence InferenceContextual Word Representations: A Contextual IntroductionNot All Neural Embeddings are Born EqualHigh-risk learning: acquiring new word vectors from tiny dataLearning word embeddings from dictionary definitions onlyDependency-Based Word Embeddings
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