n, an iterative
image editing module, and a crucial LVLM-driven feedback and evaluation loop.
To rigorously evaluate RefineEdit-Agent, we propose LongBench-T2I-Edit, a new
benchmark featuring 500 initial images with complex, multi-turn editing
instructions across nine visual dimensions. Extensive experiments demonstrate
that RefineEdit-Agent significantly outperforms state-of-the-art baselines,
achieving an average score of 3.67 on LongBench-T2I-Edit, compared to 2.29 for
Direct Re-Prompting, 2.91 for Instr