Research map / Architectures and efficiency / RNNs and normalization
Deep Model Transferability from Attribution Maps
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| use eps-LRP or gradient*input instead of saliency for attribution maps (ablation) | attribution-map transferability estimator · Taskonomy transferability P@K/R@K | P@K, R@K | Helped |
| use COCO or indoor scene probe data instead of taskonomy data (ablation) | attribution-map transferability estimator · Taskonomy transferability P@K/R@K | P@K, R@K | Helped |
| use attribution-map distance instead of SVCCA to estimate transferability | transferability estimator · Taskonomy transferability P@K/R@K | P@K, R@K | No clear effect |
Closest papers by meaning
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- Understanding Task Transfer in Vision-Language Models (CVPR 2026 · similarity 0.87)
- Exploiting Task Relationships in Continual Learning via Transferability-Aware Task Embeddings (NeurIPS 2025 · similarity 0.86)
- Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models (ICML 2024 · similarity 0.86)
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