On Bilingual Lexicon Induction with Large Language Models

Yaoyiran Li, Anna Korhonen, Ivan Vulić


Abstract
Bilingual Lexicon Induction (BLI) is a core task in multilingual NLP that still, to a large extent, relies on calculating cross-lingual word representations. Inspired by the global paradigm shift in NLP towards Large Language Models (LLMs), we examine the potential of the latest generation of LLMs for the development of bilingual lexicons. We ask the following research question: Is it possible to prompt and fine-tune multilingual LLMs (mLLMs) for BLI, and how does this approach compare against and complement current BLI approaches? To this end, we systematically study 1) zero-shot prompting for unsupervised BLI and 2) few-shot in-context prompting with a set of seed translation pairs, both without any LLM fine-tuning, as well as 3) standard BLI-oriented fine-tuning of smaller LLMs. We experiment with 18 open-source text-to-text mLLMs of different sizes (from 0.3B to 13B parameters) on two standard BLI benchmarks covering a range of typologically diverse languages. Our work is the first to demonstrate strong BLI capabilities of text-to-text mLLMs. The results reveal that few-shot prompting with in-context examples from nearest neighbours achieves the best performance, establishing new state-of-the-art BLI scores for many language pairs. We also conduct a series of in-depth analyses and ablation studies, providing more insights on BLI with (m)LLMs, also along with their limitations.
Anthology ID:
2023.emnlp-main.595
Volume:
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2023
Address:
Singapore
Editors:
Houda Bouamor, Juan Pino, Kalika Bali
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
9577–9599
Language:
URL:
https://aclanthology.org/2023.emnlp-main.595
DOI:
10.18653/v1/2023.emnlp-main.595
Bibkey:
Cite (ACL):
Yaoyiran Li, Anna Korhonen, and Ivan Vulić. 2023. On Bilingual Lexicon Induction with Large Language Models. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 9577–9599, Singapore. Association for Computational Linguistics.
Cite (Informal):
On Bilingual Lexicon Induction with Large Language Models (Li et al., EMNLP 2023)
Copy Citation:
PDF:
https://preview.aclanthology.org/emnlp22-frontmatter/2023.emnlp-main.595.pdf
Video:
 https://preview.aclanthology.org/emnlp22-frontmatter/2023.emnlp-main.595.mp4