Copy First, Translate Later: Interpreting Translation Dynamics in Multilingual Pretraining
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Computer Science > Computation and Language
Title:Copy First, Translate Later: Interpreting Translation Dynamics in Multilingual Pretraining
Abstract:Large language models exhibit impressive cross-lingual capabilities. However, prior work analyzes this phenomenon through isolated factors and at sparse points during training, limiting our understanding of how cross-lingual generalization emerges--particularly in the early phases of learning. To study the early trajectory of linguistic and translation capabilities, we pretrain a multilingual 1.7B model on nine diverse languages, capturing checkpoints at a much finer granularity. We use word-level translation as a testbed, introducing a novel dataset to trace how translation develops over training through behavioral analyses, model-component analysis, and parameter-based ablations. We find that the model quickly acquires basic linguistic capabilities in parallel with token-level copying, while translation develops in two distinct phases: an initial phase dominated by copying and surface-level similarities, and a second phase in which more generalizing translation mechanisms are developed while copying is refined. Together, these findings provide a fine-grained view of how cross-lingual generalization develops during multilingual pretraining.
| Comments: | 10 pages |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2604.17633 [cs.CL] |
| (or arXiv:2604.17633v2 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2604.17633
arXiv-issued DOI via DataCite
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Submission history
From: Maria Matveev [view email][v1] Sun, 19 Apr 2026 22:03:29 UTC (2,752 KB)
[v2] Fri, 26 Jun 2026 09:55:26 UTC (3,231 KB)
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