[ICML 2026] Official codebase for "Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation" & Causal Forcing++
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Updated
Aug 28, 2026 - Python
[ICML 2026] Official codebase for "Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation" & Causal Forcing++
Mixed-precision quantization scheme (16/8/4bit mixed quantization) for the Wan2.2-Animate-14B model. Compresses the original 35GB base model to 17GB, balancing inference performance and model size.
Identity-preserving image-to-video generation: vision-grounded prompt simplification via Qwen3-VL, Lightning LoRA 4-step inference, and SAM3-masked DINOv3 candidate reranking for fluid 720p video from a single reference image.
Local AI video generation — Wan 2.2 GGUF + LTX-Video via ComfyUI API. RTX 4090 optimized. No cloud.
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