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Most reported gains in crop disease classification from environmental sensors are illusory, driven by simple session memorization rather than genuine multimodal learning.
Instead of trying to replace solvers with GNNs for combinatorial auctions, this work shows you can get surprisingly far by simply predicting *when* a fast greedy heuristic will fail and then switching to a more powerful GNN solver only when needed.
