10 citations · 12 across the 3 of their papers we have counts for
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cs.DC2025
RLBoost: Harvesting Preemptible Resources for Cost-Efficient Reinforcement Learning on LLMs
Yongji Wu, Xueshen Liu, Haizhong Zheng +5
Reinforcement learning (RL) has become essential for unlocking advanced reasoning capabilities in large language models (LLMs). RL workflows involve interleaving rollout and traini…
cs.DC2022★ 2 cited
Elastic Model Aggregation with Parameter Service
Juncheng Gu, Mosharaf Chowdhury, Kang G. Shin +1
Model aggregation, the process that updates model parameters, is an important step for model convergence in distributed deep learning (DDL). However, the parameter server (PS), a p…