# Trajectory-Tail Steering

In multi-turn image editing, each output becomes the next input, so small unintended changes to untouched content accumulate into visible drift. TailSteer concentrates preservation corrections near the tail of the diffusion denoising trajectory while keeping early dynamics close to the base model, and learns them from the editor's own on-policy rollouts using unchanged source content as reference, without curated editing pairs. Across four backbones in the FLUX, SenseNova and Qwen families, cumulative drift over 15 to 20 editing turns drops substantially while text-to-image and single-turn editing benchmarks stay largely intact.

In multi-turn image editing, each output becomes the next input, so small unintended changes to untouched content accumulate into visible drift. TailSteer concentrates preservation corrections near the tail of the diffusion denoising trajectory while keeping early dynamics close to the base model, and learns them from the editor's own on-policy rollouts using unchanged source content as reference, without curated editing pairs. Across four backbones in the FLUX, SenseNova and Qwen families, cumulative drift over 15 to 20 editing turns drops substantially while text-to-image and single-turn editing benchmarks stay largely intact.