AutoResearch on Diffusers' Pipeline for 10 Rounds on JarvisLabs

An experiment conducted with the support of JarvisLabs explored the nuances of image generation using Diffusers, focusing on the iterative process beyond initial prompt generation. The study utilized Codex as a research agent to manage the selection and testing of variables such as aspect ratio and floor separation in a text-to-image task, which aimed to create a complex architectural watercolor. The experiment highlighted the importance of understanding failures and making adjustments, rather than relying solely on prompts. Successful outcomes resulted from identifying and modifying specific elements like semantic anchors and floor structure, while less effective changes, such as increasing image density or relying on negative constraints, proved informative in understanding the limitations of prompt-based control. The experiment emphasized a modular approach to image generation, leveraging JarvisLabs' GPU capabilities for rapid iteration and emphasizing the value of a structured, agent-driven research methodology over simple prompt manipulation.

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