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cs.CL2024
MuLan: Adapting Multilingual Diffusion Models for Hundreds of Languages with Negligible Cost
Sen Xing, Muyan Zhong, Zeqiang Lai +5
In this work, we explore a cost-effective framework for multilingual image generation. We find that, unlike models tuned on high-quality images with multilingual annotations, lever…
cs.LG2024
Bidirectional Consistency Models
Liangchen Li, Jiajun He
Diffusion models (DMs) are capable of generating remarkably high-quality samples by iteratively denoising a random vector, a process that corresponds to moving along the probabilit…