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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
Earlier work this paper cites.

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Neural word embedding as implicit matrix factorization
Omer Levy and Yoav Goldberg · 2014
Cited alongside, same era.

Glove: Global vectors for word representation
Original
Jeffrey Pennington, Richard Socher, and Christopher D Manning · 2014
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2014

Shi, Tianze, Liu, Zhiyuan

The Global Vectors for word representation (GloVe), introduced by Jeffrey Pennington et al.

is reported to be an efficient and effective method for learning vector representations of words.
State-of-the-art performance is also provided by skip-gram with negative-sampling (SGNS) implemented in the word2vec tool.
In this note, we explain the similarities between the training objectives of the two models, and show that the objective of SGNS is similar to the objective of a specialized form of GloVe, though their cost functions are defined differently.

Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean · 2013
Earlier work this paper cites.

Neural word embedding as implicit matrix factorization
Omer Levy and Yoav Goldberg · 2014
Cited alongside, same era.

Glove: Global vectors for word representation
Original
Jeffrey Pennington, Richard Socher, and Christopher D Manning · 2014
Closest in time.

alphaXiv searches the wider corpus for related work and actual follow-ups.

alphaXiv is searching for related work…