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The Interlingua Hypothesis: LLMs Translate via a Latent Task-agnostic Feature Space

arXiv · AI, language, vision and robotics · article · Sep 1, 2026 · UTC

Large language models (LLMs) have recently demonstrated improved machine translation performance over strong supervised baselines. This raises questions as to what mechanisms underlie how LLMs perform machine translation between languages. Motivated by recent interpretability findings--namely, that LLMs use massively multilingual latent feature representations to perform language modeling--we propose the interlingua hypothesis. The hypothesis holds that language models translate by reading a source sentence into a latent feature space, and generate a target sentence by reading from the latent

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