A contract-based multi-agent system maintains a claim-level semantic memory for long videos, enabling targeted corrections that raise VQA accuracy from 0.71 to 0.79 and cut human arbitration cost by 4.8x on VidOR.
Image retrieval using scene graphs,
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IMPACT-CYCLE: A Contract-Based Multi-Agent System for Claim-Level Supervisory Correction of Long-Video Semantic Memory
A contract-based multi-agent system maintains a claim-level semantic memory for long videos, enabling targeted corrections that raise VQA accuracy from 0.71 to 0.79 and cut human arbitration cost by 4.8x on VidOR.