2 citations · 2 across the 8 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2026
VAE-Inf: A statistically interpretable generative paradigm for imbalanced classification
Hongfei Wu, Ruijian Han, Yancheng Yuan
Imbalanced classification remains a pervasive challenge in machine learning, particularly when minority samples are too scarce to provide a robust discriminative boundary. In such…
cs.LG2025
Accelerating RLHF Training with Reward Variance Increase
Zonglin Yang, Zhexuan Gu, Houduo Qi +1
Reinforcement learning from human feedback (RLHF) is an essential technique for ensuring that large language models (LLMs) are aligned with human values and preferences during the…