Kee-Eung Kim

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.