2 papers
cs.DC2026
psRL: Efficient Training for Agentic AI via Training-Time Prefix Sharing
Mianjie Yu, Zizhao Mo, Huanyu Qu +8
In modern agentic AI training, the system bottleneck is shifting from rollout to update. Emerging sampling strategies such as tree-structured and step-wise RL greatly increase trai…
cs.AI2026
Scaling Domain Data Repetition in LLM Pretraining
Jingwei Li, Xinran Gu, Rui Dai +5
As large language models scale, their training-token budgets must also increase to maintain an appropriate tokens-per-parameter ratio (\(\mathrm{TPP}\)). However, high-quality doma…