BenchmarkVL-RewardBench
VL-RewardBench
A benchmark for evaluating the ability of vision-language models to compare multimodal answers and make reward judgments.
Timeline (last 90 days)
Oct 17
On VL-RewardBench, JEV-27B-VL achieves an overall accuracy of 78.3%, 83.2% on hallucination items, 78.2% on reasoning items, and 58.0% on general questions.
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