GenRouter: Unified Workflow Routing for Agentic Image Generation
- Published
- Source
- arXiv
- Paper number
- 925
- Field
- Computer Vision
- arXiv ID
- 2608.16721
Key points
- GenCanvas provides a fixed framework ranging from lightweight direct generation to heavy workflows that use retrieval, spatial sketches, and iterative verification.
- GenRouter chooses the appropriate workflow in the order of requirement analysis, candidate pruning, experience matching, and quality-versus-cost filtering.
- The main comparison uses Qwen-Image-2512 and Z-Image-Turbo as generators, with common language and vision tools aligned to Kimi K2.5.
- In experiments with 500 mixed prompts from nine benchmarks, adding experience from three benchmarks raises the score from 73.5 to 75.2, while cost and time fall by 8.7% and 7.9%, respectively.
- It uses 10 calibration prompts separated from evaluation for each new benchmark, and it runs all possible workflow and generator combinations for each prompt. Because cost and time weights are also chosen by humans, it is not fully zero-shot.
Paper links
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