Home  | Publications | HLF24

Understanding Cross-Lingual Alignment—A Survey

MCML Authors

Link to Profile Alexander Fraser PI Matchmaking

Alexander Fraser

Prof. Dr.

Principal Investigator

Abstract

Cross-lingual alignment, the meaningful similarity of representations across languages in multilingual language models, has been an active field of research in recent years. We survey the literature of techniques to improve cross-lingual alignment, providing a taxonomy of methods and summarising insights from throughout the field. We present different understandings of cross-lingual alignment and their limitations. We provide a qualitative summary of results from a number of surveyed papers. Finally, we discuss how these insights may be applied not only to encoder models, where this topic has been heavily studied, but also to encoder-decoder or even decoder-only models, and argue that an effective trade-off between language-neutral and language-specific information is key.

inproceedings


Findings @ACL 2024

Findings of the 62nd Annual Meeting of the Association for Computational Linguistics. Bangkok, Thailand, Aug 11-16, 2024.
Conference logo
A* Conference

Authors

K. Hämmerl • J. Libovický • A. Fraser

Links

DOI

Research Area

 B2 | Natural Language Processing

BibTeXKey: HLF24

Back to Top