Adobe Research Unlocking Long-Term Memory in Video World Models with State-Space Models | Haber Detay
Adobe Research Unlocking Long-Term Memory in Video World Models with State-Space Models
Category: Synced | Date: 2025-06-25 11:18:08
By combining State-Space Models (SSMs) for efficient long-range dependency modeling with dense local attention for coherence, and using training strategies like diffusion forcing and frame local attention, researchers from Adobe Research successfully overcome the long-standing challenge of long-term memory in video generation. The post Adobe Research Unlocking Long-Term Memory in Video World Models with State-Space Models first appeared on Synced.
