CogniGPT uses an interactive loop between a Multi-Granular Perception Agent and an Active Verification Agent to identify reliable clues in long videos with high accuracy and low frame usage.
Semi-parametric video-grounded text generation
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
UNIVID generates policy-aware captions for video moderation, reducing violation leakage by 42.7% and overkill rate by 37.0% while replacing over 1,000 policy-specific models with a single backbone.
AirVista-II integrates agent-based task identification and scheduling, multimodal perception, and scenario-tailored keyframe extraction to deliver high-quality zero-shot semantic understanding for embodied UAVs in dynamic environments.
citing papers explorer
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Perceive, Verify and Understand Long Video: Multi-Granular Perception and Active Verification via Interactive Agents
CogniGPT uses an interactive loop between a Multi-Granular Perception Agent and an Active Verification Agent to identify reliable clues in long videos with high accuracy and low frame usage.
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UNIVID: Unified Vision-Language Model for Video Moderation
UNIVID generates policy-aware captions for video moderation, reducing violation leakage by 42.7% and overkill rate by 37.0% while replacing over 1,000 policy-specific models with a single backbone.
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AirVista-II: An Agentic System for Embodied UAVs Toward Dynamic Scene Semantic Understanding
AirVista-II integrates agent-based task identification and scheduling, multimodal perception, and scenario-tailored keyframe extraction to deliver high-quality zero-shot semantic understanding for embodied UAVs in dynamic environments.