Bucket-Level MOO reformulates multilingual fine-tuning as localized multi-objective optimization and proves it enforces a tighter Pareto stationarity condition while improving cross-lingual performance on four LLMs.
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Multilingual Fine-Tuning via Localized Gradient Conflict Resolution
Bucket-Level MOO reformulates multilingual fine-tuning as localized multi-objective optimization and proves it enforces a tighter Pareto stationarity condition while improving cross-lingual performance on four LLMs.