Improving cross-lingual model transfer by chunking

TL;DR

This paper introduces a shallow parser guided method for cross-lingual model transfer that uses sentence chunks as transfer units to better handle syntactic differences between languages.

Contribution

It proposes a novel chunk-based transfer approach that separately addresses phrase and sentence-level syntactic variations in cross-lingual models.

Findings

Improved transfer accuracy across languages.

Effective handling of syntactic differences.

Enhanced model robustness in multilingual settings.

Abstract

We present a shallow parser guided cross-lingual model transfer approach in order to address the syntactic differences between source and target languages more effectively. In this work, we assume the chunks or phrases in a sentence as transfer units in order to address the syntactic differences between the source and target languages arising due to the differences in ordering of words in the phrases and the ordering of phrases in a sentence separately.