Linguistic Triggers of Gender and Racial Bias in Open-Weight LLMs Applied to Recruitment
研究通过多模型审计方法，探讨了开放权重大型语言模型在招聘中性别和种族偏见问题，发现特定语言风格会触发这些偏见，并提出了一种预部署审计协议。
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Bootstrapping Niche Multilingual Code Translation via Reinforcement Learning with Execution-Based Verifiable Supervision
This study addresses the poor executability of code translation for low-resource languages caused by insufficient parallel supervision. We propose an execution feedback-based reinforcement learning framework that trains a reward model using execution-verified data and optimizes large language models via the GRPO algorithm to enhance cross-language code generation correctness. Additionally, we introduce Humaneval-X++, a multilingual evaluation benchmark. Experiments demonstrate that a 4B-parameter model achieves an average performance improvement of 13% on this benchmark, with gains reaching 21% for medium-resource languages. The approach successfully enables executable code translation across 600 language pairs, significantly mitigating alignment challenges in low-resource scenarios.
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Linguistic Triggers of Gender and Racial Bias in Open-Weight LLMs Applied to Recruitment
研究通过多模型审计方法，探讨了开放权重大型语言模型在招聘中性别和种族偏见问题，发现特定语言风格会触发这些偏见，并提出了一种预部署审计协议。
0 citationsRead paper
Bootstrapping Niche Multilingual Code Translation via Reinforcement Learning with Execution-Based Verifiable Supervision
This study addresses the poor executability of code translation for low-resource languages caused by insufficient parallel supervision. We propose an execution feedback-based reinforcement learning framework that trains a reward model using execution-verified data and optimizes large language models via the GRPO algorithm to enhance cross-language code generation correctness. Additionally, we introduce Humaneval-X++, a multilingual evaluation benchmark. Experiments demonstrate that a 4B-parameter model achieves an average performance improvement of 13% on this benchmark, with gains reaching 21% for medium-resource languages. The approach successfully enables executable code translation across 600 language pairs, significantly mitigating alignment challenges in low-resource scenarios.
0 citationsRead paper