11 citations · 14 across the 5 of their papers we have counts for
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cs.LG2024★ 2 cited
Alignment of Diffusion Models: Fundamentals, Challenges, and Future
Buhua Liu, Shitong Shao, Bao Li +6
Diffusion models have emerged as the leading paradigm in generative modeling, excelling in various applications. Despite their success, these models often misalign with human inten…
cs.LG2024★ 1 cited
Improve Knowledge Distillation via Label Revision and Data Selection
Weichao Lan, Yiu-ming Cheung, Qing Xu +4
Knowledge distillation (KD) has become a widely used technique in the field of model compression, which aims to transfer knowledge from a large teacher model to a lightweight stude…