CurveBench benchmark reveals that even leading VLMs like Gemini 3.1 Pro reach only 71.1% accuracy recovering containment trees on easy nested-curve images and 19.1% on hard versions, while fine-tuning lifts an open 8B model to 33.3% on easy cases.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages =
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CurveBench: A Benchmark for Exact Topological Reasoning over Nested Jordan Curves
CurveBench benchmark reveals that even leading VLMs like Gemini 3.1 Pro reach only 71.1% accuracy recovering containment trees on easy nested-curve images and 19.1% on hard versions, while fine-tuning lifts an open 8B model to 33.3% on easy cases.