Safety, alignment & interpretability· 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
DOI 10.1109/iccv.2017.74arXiv 1610.02391OpenAlex W2962858109
On the reading lists
- #91 in the Top 500 (2026 edition)
- #9 in Safety, alignment & interpretability (2026 edition)
Why it matters
Made class-specific visual explanations accessible across convolutional architectures and computer vision applications.
Condensed from the expert lists' notes.
The record
- First released
- 2016 (from arXiv 1610.02391)
- Published
- 2017
- Citations
- 30,248 citations, as counted by Papers With Code (CC BY-SA 4.0)
- Named by
- both expert lists
- Score
- 0.669 · computed rank 91 · consensus 0.91, must-read 0.5, citations percentile 0.989 (2010s · safety), awards 0, existing lists 0. Method
Data sources
Catalogue data from OpenAlex (CC0), Crossref (CC0 metadata; no abstracts are shown), arXiv, and Papers With Code (CC BY-SA 4.0). Each count names its source. See the method.