Papers with LSTM-based models

2 papers
You Only Need Attention to Traverse Trees (P19-1)

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Challenge: Recent research has focused on sentence representations.
Approach: They propose a tree-based model that captures phrase-level syntax and word-level dependencies by doing recursive traversal with attention.
Outcome: a new model captures phrase-level syntax and word-level dependencies with attention.
Universal-KD: Attention-based Output-Grounded Intermediate Layer Knowledge Distillation (2021.emnlp-main)

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Challenge: Existing methods for intermediate layer matching are limited due to huge over-parameterization .
Approach: They propose to match intermediate layers of teacher and student in output space via attention-based layer projection.
Outcome: The proposed method outperforms existing methods on GLUE tasks.

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