SpecVQA is a new benchmark dataset and evaluation suite for testing multimodal large language models on scientific spectral image understanding and visual question answering, supported by a curve-preserving sampling method that improves results.
In: Machine Intelli- gence and pattern recognition, vol
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An O(log n) round algorithm computes a decomposition of arbitrary amoebot structures into O(number of holes) geodesically convex regions using reconfigurable circuits.
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SpecVQA: A Benchmark for Spectral Understanding and Visual Question Answering in Scientific Images
SpecVQA is a new benchmark dataset and evaluation suite for testing multimodal large language models on scientific spectral image understanding and visual question answering, supported by a curve-preserving sampling method that improves results.
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Logarithmic-Time Geodesically Convex Decomposition in Programmable Matter
An O(log n) round algorithm computes a decomposition of arbitrary amoebot structures into O(number of holes) geodesically convex regions using reconfigurable circuits.