By aligning KV cache compression with semantic planning constraints, you can reduce memory usage by 3.35x and speed up video generation by 1.22x without retraining, making agentic video generation more practical for resource-constrained settings.
This paper presents SemanticKV, a method to compress the key-value cache in video generation models by using semantic constraints from a planner to decide which cached information to keep.