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      "statement": "# Villegas et al.: causal video tokenization with variable-prompt generation\n\nCompressed videos with a temporally causal discrete tokenizer and generated tokens with a text-conditioned masked transformer, combining image/text and video/text data for variable-length prompt sequences.\n\n## Scientific scope\n\nMasked generation, transformers and discrete autoencoders are inherited. Variable-length generation is an architectural capability, not arbitrarily long semantic/visual coherence or unlimited compute. Original2022 snapshot controls.\n\n## Reading status\n\nThis is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.\n\n## People and systems\n\nRuben Villegas; Mohammad Babaeizadeh; Pieter-Jan Kindermans; Hernan Moraldo; Han Zhang; Mohammad Taghi Saffar; Santiago Castro; Julius Kunze; Dumitru Erhan\n\nSource-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.\n\n\n\n## Original sources\n\n- [Phenaki: Variable Length Video Generation From Open Domain Textual Description](https://arxiv.org/abs/2210.02399v1)\n",
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