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cs.LG2025
ConfClip: Confidence-Weighted and Clipped Reward for Reinforcement Learning in LLMs
Bonan Zhang, Zhongqi Chen, Bowen Song +3
Reinforcement learning (RL) has become a standard paradigm for refining large language models (LLMs) beyond pre-training and instruction tuning. A prominent line of work is RL with…
cs.LG2025★ 1 cited
Quality over Quantity: Boosting Data Efficiency Through Ensembled Multimodal Data Curation
Jinda Xu, Yuhao Song, Daming Wang +4
In an era overwhelmed by vast amounts of data, the effective curation of web-crawl datasets is essential for optimizing model performance. This paper tackles the challenges associa…