Adobe's EditAgent beats prior image-editing agents but needs ~10x the compute
emmanuelvivier · x · 2026-11-02
Adobe Research and UC San Diego built EditAgent, which decomposes editing tasks into sub-steps paired with specialized tools (sharpening, zooming) and uses an unmodified LLM to judge parallel candidates via measured statistics and close-up crops — outperforming purpose-trained evaluators and prior agents, at 10x compute. Verified outputs can train faster editing models.
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