AI RESEARCH
VISTA: Video Interaction Spatio-Temporal Analysis Benchmark
arXiv CS.CV
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ArXi:2605.01391v1 Announce Type: new Existing benchmarks for Vision-Language Models (VLMs) primarily evaluate spatio-temporal understanding on simple single-action videos, closed attribute sets and restricted entity types, failing to capture the freeform, multi-action interactions between diverse entities which characterize real-world video understanding. Furthermore, the lack of a systematic framework for analyzing model failures across complementary spatio-temporal axes hinders comprehensive evaluation. To address these gaps, we