VDCook:DIY video data cook your MLLMs

• URL: http://arxiv.org/abs/2603.05539v1
• Date: Wed, 04 Mar 2026 10:39:04 GMT
• Title: VDCook:DIY video data cook your MLLMs
• Abstract summary: VDCook is a self-evolving video data operating system for researchers and vertical domain teams.<n>It generates in-domain data packages with complete provenance and metadata, along with reproducible Notebooks.
• Score: 3.170179753848826
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We introduce VDCook: a self-evolving video data operating system, a configurable video data construction platform for researchers and vertical domain teams. Users initiate data requests via natural language queries and adjustable parameters (scale, retrieval-synthesis ratio, quality threshold). The system automatically performs query optimization, concurrently running real video retrieval and controlled synthesis modules. It ultimately generates in-domain data packages with complete provenance and metadata, along with reproducible Notebooks. Unlike traditional static, one-time-built datasets, VDCook enables continuous updates and domain expansion through its automated data ingestion mechanism based on MCP (Model Context Protocol)\cite{mcp2024anthropic}, transforming datasets into dynamically evolving open ecosystems. The system also provides multi-dimensional metadata annotation (scene segmentation, motion scoring, OCR ratio, automatic captioning, etc.), laying the foundation for flexible subsequent data `cooking' and indexing\cite{vlogger}. This platform aims to significantly lower the barrier to constructing specialized video training datasets through infrastructure-level solutions, while supporting community contributions and a governance-enabled data expansion paradigm. \textbf{Project demo:} https://screenapp.io/app/v/WP0SvffgsH

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