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LLMs show language-dependent skill gaps in multilingual self-play

By PulseAugur Editorial · [3 sources] ·

A new research paper, "Skill Issue: Are Skills Language-Invariant in LLMs?", investigates how large language models (LLMs) perform differently across languages. Using a multilingual self-play setup in a text-based game called TextArena, the study found that the same LLM can exhibit varying skill levels and strategic tendencies depending on the language interface it uses. Performance was often highest when interacting in English and lowest in languages like Hebrew, with specific failures noted in spatial reasoning and decision-making. The research suggests that language can significantly impact an LLM's decision-making process, hindering the development of truly multilingual models. AI

IMPACT Identifies a significant roadblock in developing truly multilingual LLMs, suggesting language choice impacts model performance and strategy.

RANK_REASON The cluster contains an academic paper detailing novel research findings on LLM behavior.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 3 sources. How we write summaries →

LLMs show language-dependent skill gaps in multilingual self-play

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The cluster contains an academic paper detailing novel research findings on LLM behavior.
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COVERAGE [3]

  1. arXiv cs.CL TIER_1 English(EN) · Bobby Cheng, Adam Gaber, Zhengyuan Liu, Catherine Arnett, Omer Goldman, Cheston Tan, Leshem Choshen ·

    Skill Issue: Are Skills Language-Invariant in LLMs?

    arXiv:2608.25832v1 Announce Type: new Abstract: Large language models access knowledge inconsistently across languages, but to what extent do they differ in their skill sets when interacting with different languages? This work quantifies cross-lingual skill inconsistency orthogon…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Skill Issue: Are Skills Language-Invariant in LLMs?

    Large language models access knowledge inconsistently across languages, but to what extent do they differ in their skill sets when interacting with different languages? This work quantifies cross-lingual skill inconsistency orthogonally from knowledge and general benchmark perfor…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    Skill Issue: Are Skills Language-Invariant in LLMs?

    Multilingual self-play reveals that large language models exhibit significant cross-lingual skill inconsistencies in reasoning and strategy, partly recoverable by altering intermediate reasoning language.

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