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cs.LG2026
Sparse-RL: Breaking the Memory Wall in LLM Reinforcement Learning via Stable Sparse Rollouts
Sijia Luo, Xiaokang Zhang, Yuxuan Hu +6
Reinforcement Learning (RL) has become essential for eliciting complex reasoning capabilities in Large Language Models (LLMs). However, the substantial memory overhead of storing K…
cs.LG2025
QUAD: Quantization and Parameter-Efficient Tuning of LLM with Activation Decomposition
Yuxuan Hu, Xiaodong Chen, Cuiping Li +2
Large Language Models (LLMs) excel in diverse applications but suffer inefficiency due to massive scale. While quantization reduces computational costs, existing methods degrade ac…