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cs.LG2026
Random Is Hard to Beat: Active Selection in online DPO with Modern LLMs
Giyeong Oh, Junghyun Lee, Jaehyun Park +3
Modern LLMs inherit strong priors from web-scale pretraining, which can limit the headroom of post-training data-selection strategies. While Active Preference Learning (APL) seeks…
cs.LG2025
Vicinity-Guided Discriminative Latent Diffusion for Privacy-Preserving Domain Adaptation
Jing Wang, Wonho Bae, Jiahong Chen +2
Recent work on latent diffusion models (LDMs) has focused almost exclusively on generative tasks, leaving their potential for discriminative transfer largely unexplored. We introdu…
cs.LG2024
Generalized Coverage for More Robust Low-Budget Active Learning
Wonho Bae, Junhyug Noh, Danica J. Sutherland
The ProbCover method of Yehuda et al. is a well-motivated algorithm for active learning in low-budget regimes, which attempts to "cover" the data distribution with balls of a given…