EduVideoBench is a new KSA-grounded benchmark that evaluates five frontier video generation models and finds substantial gaps in educational validity across knowledge, skills, and attitudes.
Fetv: A benchmark for fine-grained evaluation of open-domain text-to-video gen- eration.arXiv preprint arXiv:2311.01813, 2023
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LongAV-Compass is a new benchmark and evaluation framework for minute-scale audio-visual generation across T2AV, I2AV, and V2AV with multi-dimensional assessment.
Current video models succeed on basic understanding but achieve under 25% success on logically grounded generation and near 0% on interactive generation, exposing gaps in multimodal reasoning.
NeuS-E is a post-generation refinement method that uses neuro-symbolic analysis of a formal video representation to detect and correct semantic and temporal inconsistencies in text-to-video outputs, improving prompt alignment by nearly 40%.
citing papers explorer
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Are Video Models Zero-Shot Learners and Reasoners in Education? EduVideoBench, A Knowledge-Skills-Attitude Benchmark for Educational Video Generation
EduVideoBench is a new KSA-grounded benchmark that evaluates five frontier video generation models and finds substantial gaps in educational validity across knowledge, skills, and attitudes.
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LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV
LongAV-Compass is a new benchmark and evaluation framework for minute-scale audio-visual generation across T2AV, I2AV, and V2AV with multi-dimensional assessment.
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How Far Are Video Models from True Multimodal Reasoning?
Current video models succeed on basic understanding but achieve under 25% success on logically grounded generation and near 0% on interactive generation, exposing gaps in multimodal reasoning.
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We'll Fix it in Post: Improving Text-to-Video Generation with Neuro-Symbolic Feedback
NeuS-E is a post-generation refinement method that uses neuro-symbolic analysis of a formal video representation to detect and correct semantic and temporal inconsistencies in text-to-video outputs, improving prompt alignment by nearly 40%.