Papers with structural probing

2 papers
Introducing Orthogonal Constraint in Structural Probes (2021.acl-long)

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Challenge: Recent studies have focused on interpreting pre-trained models' representations and analyzing their structures.
Approach: They propose a new type of structural probing where a linear projection is decomposed into two types.
Outcome: The proposed method is tested on two novel tasks and shows that lexical and syntactic information is separated in the representations.
Syntax-guided Contrastive Learning for Pre-trained Language Model (2022.findings-acl)

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Challenge: Existing studies rely on additional syntax-driven attention components to enhance the transformer, which require more parameters and additional syntactic parsing in downstream tasks.
Approach: They propose a syntax-guided contrastive learning method which does not change the transformer architecture and does not alter the transformer structure.
Outcome: The proposed method achieves consistent improvements in a variety of tasks including grammatical error detection, entity tasks, structural probing and GLUE.

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