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Faster-than-real-time performance is tied to reported H100 hardware, steps and resolution, not a universal service guarantee. The original preprint was submitted December2024 despite its2501 identifier; later LTX versions are not backdated.", "domain": "Efficient video diffusion systems" }, "sources": [ { "citation": "LTX-Video: Realtime Video Latent Diffusion", "url": "https://arxiv.org/abs/2501.00103v1" }, { "citation": "HaCohen et al.: LTX-Video coupled video compression and pixel denoising — official research provenance", "url": "https://github.com/Lightricks/LTX-Video" } ], "statement": "# HaCohen et al.: LTX-Video coupled video compression and pixel denoising\n\nMoved patchification into a high-compression video autoencoder and assigned its decoder the final pixel-space denoising step, co-designing compressed latent generation and fine-detail reconstruction for efficient video synthesis.\n\n## Scientific scope\n\nDiT/PixArt, latent diffusion and prior high-compression autoencoders retain credit. Faster-than-real-time performance is tied to reported H100 hardware, steps and resolution, not a universal service guarantee. The original preprint was submitted December2024 despite its2501 identifier; later LTX versions are not backdated.\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\nYoav HaCohen; Nisan Chiprut; Benny Brazowski; Daniel Shalem; Dudu Moshe; Eitan Richardson; Eran Levin; Guy Shiran; Nir Zabari; Ori Gordon; Poriya Panet; Sapir Weissbuch; Victor Kulikov; Yaki Bitterman; Zeev Melumian; Ofir Bibi\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- [LTX-Video: Realtime Video Latent Diffusion](https://arxiv.org/abs/2501.00103v1)\n- [HaCohen et al.: LTX-Video coupled video compression and pixel denoising — official research provenance](https://github.com/Lightricks/LTX-Video)\n", "summary": "Moved patchification into a high-compression video autoencoder and assigned its decoder the final pixel-space denoising step, co-designing compressed latent generation and fine-detail reconstruction for efficient video synthesis.", "title": "HaCohen et al.: LTX-Video coupled video compression and pixel denoising" }, "record_id": "urn:uuid:e699c12f-a9a1-4b23-a7af-0f6323d07aea", "version": 1, "source_ref": { "record_id": "urn:uuid:e699c12f-a9a1-4b23-a7af-0f6323d07aea", "version": 1, "content_hash": "sha256:3ea7729158f6093d7f4c5ad9865a62272d67d19d0b560403ced92a7bf15fd318" }, "export_view": "wrs-public-editorial-view-1", "public_view_hash": "sha256:1ac97c50b68f04aafa6e5877c32426fb6c0537678671df0021429c839ad27296" }, "target": { "record_id": "urn:uuid:e699c12f-a9a1-4b23-a7af-0f6323d07aea", "version": 1, "content_hash": "sha256:3ea7729158f6093d7f4c5ad9865a62272d67d19d0b560403ced92a7bf15fd318" }, "published_grade": { "profile": "wrs-published-grade-1", "edition": "2026-10-28.1", "id": "hacohen-et-al-ltx-video-joint-decoder-2024", "entry_id": "hacohen-et-al-ltx-video-joint-decoder-2024", "revision": 1, "title": "HaCohen et al.: LTX-Video coupled video compression and pixel denoising", "context": "Efficient video diffusion systems", "track": "Human-designed research method or resource", "band": "B", "modifier": "+", "status": "PROVISIONAL_EDITORIAL", "assessed_on": "2026-10-16", "evidence_cutoff": "2026-10-16", "achievement_state": "SUPPORTED_SCOPED_RESULT", "what_changed": "Moved patchification into a high-compression video autoencoder and assigned its decoder the final pixel-space denoising step, co-designing compressed latent generation and fine-detail reconstruction for efficient video synthesis.", "scope": "Moved patchification into a high-compression video autoencoder and assigned its decoder the final pixel-space denoising step, co-designing compressed latent generation and fine-detail reconstruction for efficient video synthesis. 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