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cs.DC2026★ 2 cited
HexiScale: Facilitating Large Language Model Training over Heterogeneous Hardware
Ran Yan, Youhe Jiang, Xiaonan Nie +3
Training large language models (LLMs) is a computationally intensive task, which is typically conducted in data centers with homogeneous high-performance GPUs. In this paper, we ex…
cs.CL2026
TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation
Lin Sun, Guangxiang Zhao, Xiaoqi Jian +18
The challenge of reducing the size of Large Language Models (LLMs) while maintaining their performance has gained significant attention. However, existing methods, such as model di…