CCTVBench: Contrastive Consistency Traffic VideoQA Benchmark for Multimodal LLMs
- URL: http://arxiv.org/abs/2604.20460v1
- Date: Wed, 22 Apr 2026 11:39:02 GMT
- Title: CCTVBench: Contrastive Consistency Traffic VideoQA Benchmark for Multimodal LLMs
- Abstract summary: We present CCTVBench, a Contrastive Consistency Traffic VideoQA Benchmark built on paired real accident videos and world-model-generated counterfactual counterparts.<n>CCTVBench enforces a single structured decision pattern over each video question quadruple and provides actionable diagnostics.<n>C-TCD, a contrastive decoding approach leveraging a semantically exclusive counterpart video as the contrast input at inference time, improves both instance-level QA and contrastive consistency.
- Score: 43.70351207569419
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Safety-critical traffic reasoning requires contrastive consistency: models must detect true hazards when an accident occurs, and reliably reject plausible-but-false hypotheses under near-identical counterfactual scenes. We present CCTVBench, a Contrastive Consistency Traffic VideoQA Benchmark built on paired real accident videos and world-model-generated counterfactual counterparts, together with minimally different, mutually exclusive hypothesis questions. CCTVBench enforces a single structured decision pattern over each video question quadruple and provides actionable diagnostics that decompose failures into positive omission, positive swap, negative hallucination, and mutual-exclusivity violation, while separating video versus question consistency. Experiments across open-source and proprietary video LLMs reveal a large and persistent gap between standard per-instance QA metrics and quadruple-level contrastive consistency, with unreliable none-of-the-above rejection as a key bottleneck. Finally, we introduce C-TCD, a contrastive decoding approach leveraging a semantically exclusive counterpart video as the contrast input at inference time, improving both instance-level QA and contrastive consistency.
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