Revisiting Diffusion Fine-Tuning for Unsupervised Domain Adaptation

arXiv:2609.33716 · cs.CV · Submitted 2026-09-27 · Read on arXiv

cs.CV

Submitted: 2026-09-27

Updated: 2026-09-27

Project page: https://xuanqi99.github.io/MUSE

Terminology

• Adaptation — 103× in this paper · explained in 1 episode
• Core — 57× in this paper · explained in 2 episodes
• Fine-Tuning — 57× in this paper · explained in 5 episodes
• Domain Adaptation — 32× in this paper · explained in 5 episodes
• Accuracy — 25× in this paper · explained in 1 episode
• Benchmark — 18× in this paper · explained in 2 episodes
• Diffusion Model — 18× in this paper · explained in 8 episodes
• Ablation — 13× in this paper · explained in 1 episode
• Diffusion Models — 13× in this paper · explained in 6 episodes
• Adaptive Sampling — 8× in this paper · explained in 1 episode
• Alignment — 8× in this paper · explained in 1 episode
• Regularization — 5× in this paper · explained in 3 episodes
• Domain Shift — 4× in this paper · explained in 4 episodes
• Latent Diffusion Model — 4× in this paper · explained in 2 episodes
• Adversarial Training — 3× in this paper · explained in 1 episode
• Ablation Studies — 2× in this paper · explained in 1 episode
• Foundation Model — 2× in this paper · explained in 3 episodes
• Institutional Review Board — 2× in this paper
• Latent Diffusion Models — 2× in this paper · explained in 2 episodes
• Pseudo-labeling — 2× in this paper · explained in 3 episodes
• Semantic Drift — 2× in this paper · explained in 3 episodes
• Transfer Learning — 2× in this paper · explained in 10 episodes
• Abstraction — 1× in this paper · explained in 1 episode
• Distillation — 1× in this paper · explained in 2 episodes
• Distribution Shift — 1× in this paper · explained in 5 episodes
• Ensemble Learning — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative Model — 1× in this paper · explained in 2 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Knowledge Distillation — 1× in this paper · explained in 11 episodes
• Model Merging — 1× in this paper · explained in 2 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Provenance — 1× in this paper · explained in 3 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Synthetic Data Generation — 1× in this paper · explained in 5 episodes
• Transferability — 1× in this paper · explained in 4 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• Deep Domain Confusion: Maximizing for Domain Invariance

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