Papers with LAPE

2 papers
Language-Specific Neurons: The Key to Multilingual Capabilities in Large Language Models (2024.acl-long)

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Challenge: Despite the impressive multilingual capabilities demonstrated by LLMs, the understanding of how these abilities develop and function remains nascent.
Approach: They propose a novel detection method to pinpoint language-specific neurons within LLMs by selectively activating or deactivating these neurons.
Outcome: The proposed method can “steer” the output language of LLMs by selectively activating or deactivating language-specific neurons.
Multilingual Language Models Encode Script Over Linguistic Structure (2026.acl-long)

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Challenge: a recent study suggests that multilingual language models organize representations around surface form, but the nature of this internal organization remains elusive.
Approach: They analyze language-associated units across different model families and scales . romanization induces near-disjoint representations that align with neither native-script inputs nor English .
Outcome: The results show that multilingual language models organize representations around surface form . romanization induces near-disjoint representations that align with neither native-script inputs nor English .

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