Papers with BERT-based Aspect-based Sentiment model

1 papers
Transfer Learning Between Related Tasks Using Expected Label Proportions (D19-1)

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Challenge: Existing methods of data supervision are limited by labeled training data.
Approach: They propose a method where models are trained based on expected label proportions.
Outcome: The proposed method improves on a sentence-level sentiment predictor and is cumulative with LM-based pretraining.

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