New research highlights English bias in LLMs, calls for per-language investment

A new paper reveals that large language models are significantly biased towards English, even when fine-tuned for other languages. Researchers found that continual pre-training does not improve cultural understanding in a target language cost-effectively compared to training from scratch. This suggests that future LLM development may require dedicated investment in per-language resources rather than solely expanding English-centric ones. AI

影响 Suggests a shift towards dedicated per-language LLM development, potentially increasing costs and complexity for non-English applications.

排序理由 Academic paper analyzing LLM language bias. [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

• English
• LLMs

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