Chameleon: Dynamic Format Adapter for Efficient Diffusion

arXiv:2609.33496 · cs.LG, cs.AI, cs.CV · Submitted 2026-09-27 · Read on arXiv

cs.LG, cs.AI, cs.CV

Submitted: 2026-09-27

Updated: 2026-09-27

Terminology

• Quantization — 76× in this paper · explained in 12 episodes
• Calibration — 44× in this paper · explained in 7 episodes
• Transformer — 17× in this paper · explained in 2 episodes
• Diffusion Model — 12× in this paper · explained in 8 episodes
• Diffusion Models — 12× in this paper · explained in 6 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Consistency — 6× in this paper · explained in 3 episodes
• Fidelity — 6× in this paper · explained in 2 episodes
• Generative AI — 6× in this paper · explained in 2 episodes
• Alignment — 5× in this paper · explained in 1 episode
• Distillation — 4× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Generalization — 2× in this paper · explained in 13 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Prompt Adherence — 2× in this paper · explained in 2 episodes
• Quantization-Aware Training — 2× in this paper · explained in 3 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adaptivity — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Consistency Distillation — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Edge Devices — 1× in this paper · explained in 2 episodes
• Elias — 1× in this paper · explained in 2 episodes
• Latent Diffusion Model — 1× in this paper · explained in 2 episodes
• Latent Diffusion Models — 1× in this paper · explained in 2 episodes
• Mean Squared Quantization Error — 1× in this paper
• Non-stationarity — 1× in this paper · explained in 2 episodes
• Pruning — 1× in this paper · explained in 4 episodes
• Reconstruction Error — 1× in this paper · explained in 2 episodes
• Semantic Alignment — 1× in this paper · explained in 3 episodes
• Sparsity — 1× in this paper · explained in 4 episodes

Sources

• A White Paper on Neural Network Quantization
• Temporal Dynamic Quantization for Diffusion Models
• OASIS: Optimized Lightweight Autoencoder System for Distributed In-Sensor computing

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