GEditBench-v2/VCReward-Bench

VCReward-Bench includes 3,506 expert-annotated preference pairs for evaluating assessment models of image editing in Visual Consistency. 🚀 Quick Start! Clone github repo git clone https://github.com/ZhangqiJiang07/GEditBench_v2.git cd GEditBench_v2 Use our autopipeline CIL for evaluation # (optional, or you can invoke the CLIs directly with `python -m src.cli.<tool>`) ./scripts/install_autopipeline.sh # you can use `python -m… See the full description on the dataset page: https://huggingface.co/datasets/GEditBench-v2/VCReward-Bench.

<iframe src="https://silytics.si/embed/item/b1379473-cbd9-4165-aaef-c5dfa563f3ea" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Silytics shows public metadata from Hugging Face and links to the original. Information may be incomplete or out of date. Last refreshed 19 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.