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Multilingual LLMs: Probing language-specific states and translation mechanisms

By PulseAugur Editorial · [2 sources] ·

Two new research papers explore the internal workings of multilingual large language models (mLLMs) and their translation capabilities. The first paper questions the concept of a single "lingua franca" within these models, finding that different probing methods yield conflicting results about language-specific states. The second paper proposes a more modular view of translation, suggesting that models first establish target word order before generating the surface form of the target language, with specific attention heads dedicated to syntactic transformations. AI

IMPACT These studies offer deeper insights into how multilingual models process and translate languages, potentially guiding future model development and evaluation.

RANK_REASON Two academic papers published on arXiv detailing new research into the internal mechanisms of multilingual LLMs.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Multilingual LLMs: Probing language-specific states and translation mechanisms

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Two academic papers published on arXiv detailing new research into the internal mechanisms of multilingual LLMs.
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COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Deniz Bayazit, Badr AlKhamissi, Antoine Bosselut ·

    Lingua Franca or Probing Artifact? Rethinking Latent Language in Multilingual LLMs

    arXiv:2609.00155v1 Announce Type: cross Abstract: Latent language identification is often used to argue that multilingual language models route computation through language-specific states, such as English pivots. However, existing probes infer latent language from different sign…

  2. arXiv cs.CL TIER_1 English(EN) · Mikhail Sonkin, Tanja Baeumel, Daniil Gurgurov, Josef van Genabith, Simon Ostermann ·

    Separating Syntax from Language: A Mechanistic Account of Translation in Multilingual LLMs

    arXiv:2609.01356v1 Announce Type: new Abstract: Multilingual large language models (mLLMs) achieve strong performance in machine translation, yet our understanding of the mechanisms by which they transform representations from one language to another remains incomplete. Prior wor…

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