PRISM-VLM: A Multi-Axis Discriminative Benchmark for Compact Vision-Language Models
PRISM-VLM is introduced, a multi-axis discriminative benchmark that scores every item along seven axes covering the recurring failure modes (task quality, behavioral robustness, and capability bottlenecks) and combines them into a single PScore, with items recycled from fifteen public benchmarks.
Sanghee Park, Kee-Eung Kim
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