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Adobe Research and UC San Diego propose the image editing agent EditAgent, which chooses between a general-purpose editor and specialized tools for each step of the task, and uses verification records with brightness, color statistics, and difference maps to let the language model select results. According to The Decoder, on a benchmark of 600 edits, the general-purpose editor Flux-2-Klein-9B produced unusable results in 42.7% of cases, and the specialized tools resolved about two-thirds of them; after adding verification records, all seven tested models surpassed the fine-tuned EditScore, with Qwen3.8-27B selecting usable results 81.3% of the time, higher than EditScore-72B's 74.8%. EditAgent outperforms seven other agents on three benchmarks, but its computational cost is about ten times that of a single editor.
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Adobe and UC San Diego propose EditAgent, enabling AI agents to...Developments
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Adobe Research and UC San Diego propose image editing agent EditAgent
Source:The Decoder
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Nov 1
The Decoder
Adobe and UC San Diego propose EditAgent, enabling AI agents to...
Adobe Research and UC San Diego propose the image editing agent EditAgent, which selects the better option between a general editor and specialized tools for each step of a task, and uses verification records with brightness, color statistics, and change maps to let a language model pick the result. On a benchmark of 600 edits, the general editor Flux-2-Klein-9B produced unusable results in 42.7% of cases, and specialized tools resolved about two-thirds of those; after adding verification records, all seven tested models surpassed the fine-tuned EditScore, with Qwen3.8-27B selecting usable results 81.3% of the time, higher than EditScore-72B's 74.8%. EditAgent outperforms seven other agents on three benchmarks, but its computational cost is about ten times that of a single editor.