The paper introduces the Turkic Transfer Coefficient (TTC) as a theoretical measure of transfer potential and a scaling model linking adaptation performance to model capacity, data size, and adaptation module expressivity in Turkic languages.
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A 72GB Tibetan corpus enables continual pre-training of Qwen2.5-7B and a 50B-A10B MoE model, with new benchmarks showing outperformance over prior Tibetan models.
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Cross-Lingual Transfer and Parameter-Efficient Adaptation in the Turkic Language Family: A Theoretical Framework for Low-Resource Language Models
The paper introduces the Turkic Transfer Coefficient (TTC) as a theoretical measure of transfer potential and a scaling model linking adaptation performance to model capacity, data size, and adaptation module expressivity in Turkic languages.
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From Curated Data to Scalable Models: Continual Pre-training of Dense and MoE Large Language Models for Tibetan
A 72GB Tibetan corpus enables continual pre-training of Qwen2.5-7B and a 50B-A10B MoE model, with new benchmarks showing outperformance over prior Tibetan models.