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MIDB: Multilingual Instruction Data Booster for Enhancing Cultural Equality in Multilingual Instruction Synthesis

arXiv — cs.CL•Wednesday, November 12, 2025 at 5:00:00 AM
PositiveArtificial Intelligence
The introduction of MIDB represents a significant advancement in the field of multilingual instruction synthesis, addressing critical data quality issues that have long plagued the training of large language models (LLMs). Traditional methods often rely on machine translation, which can introduce errors and cultural biases, leading to inequities in LLM performance across different languages. By utilizing a dataset of 36.8k revision examples curated by linguistic experts across 16 languages, MIDB aims to rectify these deficiencies. The positive outcomes from both automatic and human evaluations indicate that MIDB not only enhances the quality of instruction data but also significantly improves the cultural understanding capabilities of multilingual LLMs. This development is crucial as it promotes cultural equality in AI, ensuring that diverse linguistic and cultural contexts are adequately represented and understood in AI applications.
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