21 citations · 57 across the 20 of their papers we have counts for
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cs.LG2025
SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning
Xiao Liang, Zhong-Zhi Li, Yeyun Gong +5
Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective for training large language models (LLMs) on complex reasoning tasks, such as mathematical problem solvin…
cs.LG2024★ 2 cited
MTL-LoRA: Low-Rank Adaptation for Multi-Task Learning
Yaming Yang, Dilxat Muhtar, Yelong Shen +9
Parameter-efficient fine-tuning (PEFT) has been widely employed for domain adaptation, with LoRA being one of the most prominent methods due to its simplicity and effectiveness. Ho…
cs.LG2023★ 2 cited
Efficient RLHF: Reducing the Memory Usage of PPO
Michael Santacroce, Yadong Lu, Han Yu +2
Reinforcement Learning with Human Feedback (RLHF) has revolutionized language modeling by aligning models with human preferences. However, the RL stage, Proximal Policy Optimizatio…