Method: Ablating Diffusion Training Data Without Full Retraining
maier_ak · x · 2026-08-25
The team built a causal counterfactual framework to assess the specific impact of training data.
- It operates by asking a counterfactual question: "what-if" a training example never existed?
- Using a diffusion-ensemble—many sub-models each trained on a data slice—the team can ablate any component.
- This allows generating a model without a specific data influence and analyzing causal relationships without retraining the full model.
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