TRACE audits streaming video understanding across 1,240 records from 517 videos, finding that near-identical accuracy hides large gaps in completion, invalid output, and response timing
TRACE introduces a condition-aware benchmark and evaluation framework for streaming video understanding that makes temporal validity, execution conditions, and operational outcomes explicit, evaluating eight publicly available models or systems in eight configurations on 1,240 records from 517 videos, and finds that nearly identical QA accuracy can mask substantial differences in completion, answer validity, and generation workload, while proactive performance separates into response quality, response delay, false alarms, and missed target windows.