Latent Mechanisms of Language Control in Multilingual Language Models

Abstract:Multilingual large language models can exhibit unintended code-switching -- unnecessarily alternating between languages during generation. We present a comparative study of three methods that identify language-controlling latents in cross-layer transcoders: activation value-based selection (ValSel), activation frequency-based selection (FreqSel), and LLM-generated latent annotation-based selection (AnnSel). To evaluate the efficacy of these methods in identifying language-controlling latents, we introduce two multilingual benchmarks that exhibit code-switching for fine-grained analysis of language steering across seven languages. Through targeted intervention experiments on Gemma-2-2B and Qwen3-4B, we find that all three methods effectively manipulate generation language, with FreqSel achieving the strongest overall performance, while AnnSel offering interpretable latent selection through explicit language annotations. A knock-out analysis suggests the methods select non-overlapping but each-functional latent subsets, indicating redundancy rather than a single canonical language direction. Code and data can be found at this https URL.

Computation and Language (cs.CL)

arXiv:2609.00325 [cs.CL]

(or arXiv:2609.00325v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2609.00325 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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