QuantVideoGen: Quantization Solves KV Cache Memory Bottleneck in Long Video Generation
songhan_mit · x · 2026-07-08
QuantVideoGen, a study shared by Professor Song Han of MIT and others, is set to be published at ICML 2026. Addressing the KV cache memory bottleneck in long video generation, it leverages quantization techniques to save approximately 7x memory, effectively improving the scalability and efficiency of long video generation.
More from Multimodal
- One prompt to a 2-3 min narrated short: hands-on test of Antigravity video generation — AI_Andrew · 2026-10-26
- FLUX.3 Klein step-distilled to 4-8 steps with CFG baked in — Fit-Structure-6489 · 2026-10-26
- Full animation short made with Google Gemini tools, 10,564 frames — AI_Andrew · 2026-10-26
- ostris pre-training "Primal VAE": 1-channel latents match modern 8x VAEs via patching — ostrisai · 2026-10-26
- Community checkpoint 'Narrative Drift' brings art-directed visuals to Krea 2 Turbo — MoonbearAIArt · 2026-10-26
- Same prompt, split results: Claude Opus 5.5 vs GPT-6 Astra on a 3D C-section explainer — Sourcecode12 · 2026-10-26