DramaR²: Recursive Self-Evolution of Coherent Short-Drama Generation

## Abstract Short-drama generation aims to tell a complete and coherent story within a few minutes. Recent methods use agentic systems to plan and organize short-drama production and long-video generation. However, multi-agent production spans multiple stages and can be unstable, leading to unexpected failures. A failure that appears local may therefore reveal a broader weakness in the production harness. Recursive self-improvement (RSI) offers a promising path for improving agentic short-drama generation. By learning from failures observed during production and updating the harness, RSI closes a higher-level loop from production to harness evolution and back to production, allowing the generator itself to improve across projects. We introduce DRAMAR², a self-evolving multi-agent framework for short-drama generation with an inner production loop and an outer RSI loop. The inner loop turns a story into an edited short drama. The outer loop reads the production trace, turns failures into harness updates, replays the original case, and compares the updated and current harnesses on paired test cases. In this way, RSI changes the target of improvement from one drama to the harness that produces later dramas. Accepted updates guide later productions, whose traces provide evidence for further improvement. We also introduce DRAMAR²-Bench with drama-level and pair-level tracks for complete short-drama evaluation. Experimental results show that DRAMAR² outperforms four existing agentic long-video generation systems. See our project page for video demos.