Papers with transfer learning technique

2 papers
Supervised and Unsupervised Transfer Learning for Question Answering (N18-1)

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Challenge: Several QA scenarios and datasets have been introduced over the past few years.
Approach: They conduct extensive experiments to investigate the transferability of knowledge from a source QA dataset to a target dataset using two QA models.
Outcome: The proposed model outperforms the previous best model on TOEFL listening comprehension test by 7% on target datasets.
A Gated Self-attention Memory Network for Answer Selection (D19-1)

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Challenge: Existing deep learning approaches for answer selection use word-level comparison followed by aggregation.
Approach: They propose a new gated self-attention memory network for answer selection task . they combine a transfer learning technique from a large-scale online corpus to create a gated network .
Outcome: The proposed model outperforms existing methods on two standard answer selection datasets: TrecQA and WikiQA.

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