PEAT: Progressive Editing via ASCII Art Transforms for Rendering in Pixels

ASCII art represents object shapes and tones through spatial arrangements of characters. We introduce PEAT (Progressive Editing via ASCII Art Transforms), which uses ASCII art as a visual bottleneck for multi-turn image editing. This representation provides a discrete, inspectable editing state while keeping the original image as a separate appearance reference. At each turn, a large language model (LLM) updates the ASCII art and scene prompt from a user instruction. After the final turn, an image editing model synthesizes an RGB image from the updated state, the aggregated edit instruction, and the original image. Across four turns, PEAT shows the smallest decline in CLIP-I and AugCLIP among six editors and achieves the highest fourth-turn AugCLIP, MANIQA, and MUSIQ scores. Over a four-turn sequence, it uses 60.2% less inference time and 90.9% less GPU energy than sequential Qwen-Edit.