enalis/LeafBenchV2

LeafBench 2.0 LeafBench 2.0 is a visual question answering (VQA) benchmark for evaluating fine-grained plant disease understanding in vision-language models (VLMs). Derived directly from LeafNet 2.0, the benchmark consists of multiple-choice questions spanning 9 complementary plant pathology tasks, designed to assess disease understanding beyond coarse category recognition. LeafBench 2.0 was evaluated across 16 VLMs including 7 CLIP-based models, 7 generative VLMs, and 2… See the full description on the dataset page: https://huggingface.co/datasets/enalis/LeafBenchV2.