Trimodal Masked Diffusion Model
The first trimodal masked diffusion model pretrained from scratch, trained simultaneously on text, image-text and audio-text data, exploring the design space of multimodal diffusion models.
Timeline (last 90 days)
The latest research proposes the first trimodal masked diffusion model pretrained from scratch, trained simultaneously on text, image-text, and audio-text data.
The cost of the trimodal from-scratch pretraining approach is higher computational demand, and the potential benefit is more natural cross-modal generation capability.
This study optimized the default parameters for inference sampling, which can be directly borrowed to reduce tuning costs.
All Facts (3)
The cost of the trimodal from-scratch pretraining approach is higher computational demand, and the potential benefit is more natural cross-modal generation capability.
50%UnverifiedThis study optimized the default parameters for inference sampling, which can be directly borrowed to reduce tuning costs.
50%UnverifiedThe latest research proposes the first trimodal masked diffusion model pretrained from scratch, trained simultaneously on text, image-text, and audio-text data.
50%