Bernini is a framework that uses an MLLM planner to output semantic representations for a DiT renderer to generate or edit videos, reporting SOTA benchmark performance.
Howto100m: Learning a text-video embedding by watching hundred million narrated video clips
2 Pith papers cite this work. Polarity classification is still indexing.
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VDCook is an automated, self-evolving platform for generating in-domain video datasets for MLLMs via natural language queries, retrieval-synthesis, and multi-dimensional metadata.
citing papers explorer
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Bernini: Latent Semantic Planning for Video Diffusion
Bernini is a framework that uses an MLLM planner to output semantic representations for a DiT renderer to generate or edit videos, reporting SOTA benchmark performance.
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VDCook:DIY video data cook your MLLMs
VDCook is an automated, self-evolving platform for generating in-domain video datasets for MLLMs via natural language queries, retrieval-synthesis, and multi-dimensional metadata.