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cs.CL2026
Late-to-Early Training: LET LLMs Learn Earlier, So Faster and Better
Ji Zhao, Yufei Gu, Shitong Shao +3
As Large Language Models (LLMs) achieve remarkable empirical success through scaling model and data size, pretraining has become increasingly critical yet computationally prohibiti…
cs.CL2025
Balanced Actor Initialization: Stable RLHF Training of Distillation-Based Reasoning Models
Chen Zheng, Yiyuan Ma, Yuan Yang +11
The development of alignment and reasoning capabilities in large language models has seen remarkable progress through two paradigms: instruction tuning and reinforcement learning f…