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Paper Citation Record · LEDGER

Fill in the blanks: Rethinking Interpretability in vision

As of 19 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 1 inbound Pith citation observation for arXiv:2411.10273.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2411.10273 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:52:21.800261Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:52:21.607072Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-12T19:52:21.964938Z

Reference resolution

33 of 33 outbound references displayed

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External citation measurements

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Outbound references

Observation 474a2b6b-e692-4f9f-838b-8d6010e55c67 · outbound

This paper cites black box.

Fill in the blanks: Rethinking Interpretability in vision black box

Reference 1

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Observation 7f59287c-5818-480b-9542-55d5bf590679 · outbound

This paper cites Fill in the blanks: Rethinking Interpretability in vision.

Fill in the blanks: Rethinking Interpretability in vision Fill in the blanks: Rethinking Interpretability in vision

Reference 2

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This paper cites an unresolved cited work.

Fill in the blanks: Rethinking Interpretability in vision Unresolved cited work

Reference 3

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Observation 74d6120c-5367-484b-b6db-8a4b4554f791 · outbound

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Fill in the blanks: Rethinking Interpretability in vision Unresolved cited work

Reference 4

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Observation 26757a3d-2cca-4544-a83e-49197f9d07bb · outbound

This paper cites The conclusions on the model will be interpreted by the human, based on perceived patterns of the visual result.

Fill in the blanks: Rethinking Interpretability in vision The conclusions on the model will be interpreted by the human, based on perceived patterns of the visual result

Reference 5

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Observation 146b2caa-5712-4fb2-8e25-eef86208fecf · outbound

This paper cites “why should i trust you?.

Fill in the blanks: Rethinking Interpretability in vision “why should i trust you?

Reference 6

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Observation 03f4fa34-34a5-4e36-ba10-7ac12a45131f · outbound

This paper cites Rethinking interpretability Let us focus on the task of image classification, and re-visit how a human recalls from memory.

Fill in the blanks: Rethinking Interpretability in vision Rethinking interpretability Let us focus on the task of image classification, and re-visit how a human recalls from memory

Reference 7

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Observation 9cfbba91-3729-452e-9df8-ea7e66cc6c8f · outbound

This paper cites How f gener- ates the prototypical class based on the given structure.

Fill in the blanks: Rethinking Interpretability in vision How f gener- ates the prototypical class based on the given structure

Reference 8

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This paper cites Can the model recognise our visualisation of the ‘prototypical image’, as an instance of the original class ?.

Fill in the blanks: Rethinking Interpretability in vision Can the model recognise our visualisation of the ‘prototypical image’, as an instance of the original class ?

Reference 9

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Observation 976d8abd-2bc9-4ee1-ad86-43965acf9d42 · outbound

This paper cites How would a vision model fill in masked-out patches?.

Fill in the blanks: Rethinking Interpretability in vision How would a vision model fill in masked-out patches?

Reference 10

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Observation 781d36dc-51d9-4ac8-bd50-3f138692a91f · outbound

This paper cites As such, we propose to visualise how a pre- trained image classifier would ‘Fill in the blanks’ of a masked image.

Fill in the blanks: Rethinking Interpretability in vision As such, we propose to visualise how a pre- trained image classifier would ‘Fill in the blanks’ of a masked image

Reference 11

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This paper cites Methods for Interpreting and Understanding Deep Neural Networks.

Fill in the blanks: Rethinking Interpretability in vision Methods for Interpreting and Understanding Deep Neural Networks

Reference 12

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This paper cites Visualizing and Understanding Convolutional Networks.

Fill in the blanks: Rethinking Interpretability in vision Visualizing and Understanding Convolutional Networks

Reference 13

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This paper cites Under- standing deep image representations by inverting them,.

Fill in the blanks: Rethinking Interpretability in vision Under- standing deep image representations by inverting them,

Reference 14

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This paper cites Understanding neural net- works through deep visualization,.

Fill in the blanks: Rethinking Interpretability in vision Understanding neural net- works through deep visualization,

Reference 15

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This paper cites On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation.,.

Fill in the blanks: Rethinking Interpretability in vision On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation.,

Reference 16

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This paper cites Learning important features through propagating activation differences,.

Fill in the blanks: Rethinking Interpretability in vision Learning important features through propagating activation differences,

Reference 17

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Fill in the blanks: Rethinking Interpretability in vision Ax- iomatic attribution for deep networks,

Reference 18

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This paper cites Learning deep features for discriminative localization,.

Fill in the blanks: Rethinking Interpretability in vision Learning deep features for discriminative localization,

Reference 19

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Fill in the blanks: Rethinking Interpretability in vision Grad-cam: Visual explanations from deep net- works via gradient-based localization,

Reference 20

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Fill in the blanks: Rethinking Interpretability in vision Score-cam: Score-weighted visual explanations for convolutional neural networks,

Reference 21

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Fill in the blanks: Rethinking Interpretability in vision Ablation-cam: Visual explanations for deep con- volutional network via gradient-free localization,

Reference 22

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Fill in the blanks: Rethinking Interpretability in vision Axiom-based Grad-CAM: Towards Accurate Visualization and Explanation of CNNs

Reference 23

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Fill in the blanks: Rethinking Interpretability in vision Visualizing higher-layer features of a deep network,

Reference 24

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This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Fill in the blanks: Rethinking Interpretability in vision Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 25

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Fill in the blanks: Rethinking Interpretability in vision Striving for simplic- ity: The all convolutional net,

Reference 26

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Fill in the blanks: Rethinking Interpretability in vision Visualizing deep convolutional neural networks using natural pre- images,

Reference 27

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Fill in the blanks: Rethinking Interpretability in vision Synthesizing the pre- ferred inputs for neurons in neural networks via deep generator networks,

Reference 28

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Fill in the blanks: Rethinking Interpretability in vision Plug and amp; play generative net- works: Conditional iterative generation of images in la- tent space,

Reference 29

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Fill in the blanks: Rethinking Interpretability in vision Mnist handwritten digit database,

Reference 30

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Fill in the blanks: Rethinking Interpretability in vision Feature visualization,

Reference 31

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Fill in the blanks: Rethinking Interpretability in vision Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 32

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Fill in the blanks: Rethinking Interpretability in vision Deep residual learning for image recognition,

Reference 33

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Pith citing papers

Observation 7f59287c-5818-480b-9542-55d5bf590679 · inbound

Fill in the blanks: Rethinking Interpretability in vision cites this paper.

Fill in the blanks: Rethinking Interpretability in vision Fill in the blanks: Rethinking Interpretability in vision

Reference 2

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