SuperLoss: A Generic Loss for Robust Curriculum Learning. - Thibault Castells; Philippe Weinzaepfel; Jérôme Revaud (NeurIPS, 2020)

Automatic Neural Network Pruning that Efficiently Preserves the Model Accuracy. - Thibault Castells; Seul-Ki Yeom (CoRR, 2021)

On Architectural Compression of Text-to-Image Diffusion Models. - Bo-Kyeong Kim; Hyoung-Kyu Song; Thibault Castells; Shinkook Choi (CoRR, 2023)

LD-Pruner: Efficient Pruning of Latent Diffusion Models using Task-Agnostic Insights. - Thibault Castells; Hyoung-Kyu Song; Bo-Kyeong Kim; Shinkook Choi (CVPR Workshops, 2024)

BK-SDM: A Lightweight, Fast, and Cheap Version of Stable Diffusion. - Bo-Kyeong Kim; Hyoung-Kyu Song 002; Thibault Castells; Shinkook Choi (ECCV (54), 2024)

Shortened LLaMA: A Simple Depth Pruning for Large Language Models. - Bo-Kyeong Kim; Geon-min Kim; Tae-Ho Kim; Thibault Castells; Shinkook Choi; Junho Shin; Hyoung-Kyu Song (CoRR, 2024)

EdgeFusion: On-Device Text-to-Image Generation. - Thibault Castells; Hyoung-Kyu Song; Tairen Piao; Shinkook Choi; Bo-Kyeong Kim; Hanyoung Yim; Changgwun Lee; Jae Gon Kim; Tae-Ho Kim (CoRR, 2024)