most citedFine tuning Pre trained Models for Robustness Under Noisy Labels

2 citations · 2 across the 4 of their papers we have counts for

collaborators
Showing cs.LGShow all

2 papers · 1 filter

cs.LG2024

Automated Filtering of Human Feedback Data for Aligning Text-to-Image Diffusion Models

Yongjin Yang, Sihyeon Kim, Hojung Jung +4

Fine-tuning text-to-image diffusion models with human feedback is an effective method for aligning model behavior with human intentions. However, this alignment process often suffe…

cs.LG2023★ 2 cited

Fine tuning Pre trained Models for Robustness Under Noisy Labels

Sumyeong Ahn, Sihyeon Kim, Jongwoo Ko +1

The presence of noisy labels in a training dataset can significantly impact the performance of machine learning models. To tackle this issue, researchers have explored methods for…