Papers with VG-

1 papers
Visually Grounded Neural Syntax Acquisition (P19-1)

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Challenge: a visually grounded neural syntax learner is an approach for learning syntactic representations without any supervision.
Approach: They propose a visually grounded neural syntax learner that acquires syntax by looking at images and reading captions.
Outcome: The proposed model outperforms unsupervised approaches on the MSCOCO data set . it is more stable with choice of initialization and amount of training data, the authors show .

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