TomaMMU is a tomato-leaf-disease VQA dataset with more than 200,000 question-answer pairs, and TomaBench shows that current vision-language models underperform on it, while fine-tuning on TomaMMU lifts MCQ accuracy to about 96%.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
TomaMMU: A Comprehensive Multimodal Understanding Benchmark for Tomato Leaf Diseases
TomaMMU is a tomato-leaf-disease VQA dataset with more than 200,000 question-answer pairs, and TomaBench shows that current vision-language models underperform on it, while fine-tuning on TomaMMU lifts MCQ accuracy to about 96%.