VideoSTF: Stress-Testing Output Repetition in Video Large Language Models
VIDEOSTF systematically tests output repetition in Video Large Language Models (VideoLLMs) using three metrics and 10,000 videos. Findings show repetition is pervasive across models, highly sensitive to temporal changes like frame manipulation, and easily induced via few-query black-box attacks. This establishes output repetition as a fundamental stability issue.