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chibifire/editreward-bench

News | Quick Start | Benchmark Usage | Citation EditScore is a series of state-of-the-art open-source reward models (7B–72B) designed to evaluate and enhance instruction-guided image editing. ✨ Highlights State-of-the-Art Performance: Effectively matches the performance of leading proprietary VLMs. With a self-ensembling strategy, our largest model surpasses even GPT-5 on our comprehensive benchmark… See the full description on the dataset page: https://huggingface.co/datasets/chibifire/editreward-bench.

sourceHugging Faceapache-2.0updated 23d agoView on Hugging Face
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