Existing methods suffer feature drift or content collapse
Yale Song and Yiwen Song report that existing methods suffer from feature drift, where entities and environments gradually change unintentionally, or content collapse, where narratives fail to progress meaningfully.
Supporting evidence
Original excerpt
existing methods suffer from feature drift , where entities and environments gradually change unintentionally, or content collapse , where narratives fail to progress meaningfully.
Context
Most existing agentic pipelines automate this process via chained modules but suffer from semantic drift (subtle shifts in character attire or scenery across shots) and cascading failures (e.g., an upstream asset artifact corrupting downstream video synthesis) due to independent, handcrafted prompting. Because early errors propagate and break long-horizon consistency, the process often requires exhaustive manual intervention. From a structural perspective, this reflects the classical credit assignment problem, as terminal failures are difficult to trace back to specific prompts. Furthermore,