Copy First, Translate Later: Interpreting Translation Dynamics in Multilingual Pretraining
Factual evidence
What the source reports
Research identifies 'copy first, translate later' learning dynamic in multilingual LLMs, showing cross-lingual generalization emerges early.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 12 October 2026
- Collected by OneBench
- 21 Apr 2026, 07:28 UK
Stored source excerpt
arXiv:2604.17633v1 Announce Type: new Abstract: Large language models exhibit impressive cross-lingual capabilities. However, prior work analyzes this phenomenon through isolated factors and at sparse points…
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OneBench interpretation
Institutional assessment
So what
This research provides a deeper understanding of how multilingual capabilities emerge in LLMs, which informs optimal training strategies for models intended for diverse global banking operations.
Do what
This study offers insights for your internal model development teams on efficient pretraining for multilingual banking applications, potentially reducing compute for specialized models.