A new 839K-image plant disease dataset paired with an agentic visual reasoning system that uses source-grounded symptoms raises diagnosis accuracy by 16.2 points on average and generalizes to unseen crops without retraining.
Visual large language model for wheat disease diagnosis in the wild.Computers and Electronics in Agriculture, 227: 109587
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SAGE: Scalable Agentic Grounded Evaluation for Crop Disease Diagnosis
A new 839K-image plant disease dataset paired with an agentic visual reasoning system that uses source-grounded symptoms raises diagnosis accuracy by 16.2 points on average and generalizes to unseen crops without retraining.