Papers by Théo Dehaze

1 papers
Understanding and Mitigating Language Confusion in LLMs (2024.emnlp-main)

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Challenge: Llama Instruct and Mistral models exhibit high degrees of language confusion and even the strongest models fail to consistently respond in the correct language.
Approach: They develop a language confusion benchmark to evaluate LLMs' inability to consistently generate text in a user’s desired language.
Outcome: The proposed model fails to consistently respond in the correct language, despite being prone to high temperatures and complex prompts.

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