MM-OptBench is a solver-grounded benchmark showing current multimodal LLMs reach at most 52% pass@1 on generating correct optimization models from text-plus-visual problem specifications.
Candidates that fail any check are rejected and regenerated until the target number of valid instances is collected
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MM-OptBench: A Solver-Grounded Benchmark for Multimodal Optimization Modeling
MM-OptBench is a solver-grounded benchmark showing current multimodal LLMs reach at most 52% pass@1 on generating correct optimization models from text-plus-visual problem specifications.