Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation | Paper Citation Record

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This paper cites Quantifying Attention Flow in Transformers.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Quantifying Attention Flow in Transformers

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This paper cites Sanity checks for saliency maps.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Sanity checks for saliency maps

Reference 2

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

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation

Reference 3

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This paper cites Random forests.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Random forests

Reference 4

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This paper cites Machine learning interpretability: A survey on meth- ods and metrics.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Machine learning interpretability: A survey on meth- ods and metrics

Reference 5

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This paper cites Grad-cam++: Gener- alized gradient-based visual explanations for deep convo- lutional networks.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Grad-cam++: Gener- alized gradient-based visual explanations for deep convo- lutional networks

Reference 6

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This paper cites Transformer inter- pretability beyond attention visualization.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Transformer inter- pretability beyond attention visualization

Reference 7

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This paper cites Robust physical-world attacks on deep learning visual classification.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Robust physical-world attacks on deep learning visual classification

Reference 8

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This paper cites Revisit fuzzy neural network: bridging the gap between fuzzy logic and deep learning.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Revisit fuzzy neural network: bridging the gap between fuzzy logic and deep learning

Reference 9

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This paper cites Shapley values for feature selection: The good, the bad, and the axioms.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Shapley values for feature selection: The good, the bad, and the axioms

Reference 10

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This paper cites Neural- symbolic learning and reasoning: A survey and interpreta- tion.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Neural- symbolic learning and reasoning: A survey and interpreta- tion

Reference 11

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This paper cites Pytorch library for cam methods.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Pytorch library for cam methods

Reference 12

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This paper cites Joint Shapley values: a measure of joint feature importance.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Joint Shapley values: a measure of joint feature importance

Reference 13

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This paper cites On Baselines for Local Feature Attributions.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation On Baselines for Local Feature Attributions

Reference 14

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This paper cites Deep residual learning for image recognition.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Deep residual learning for image recognition

Reference 15

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This paper cites A benchmark for interpretability methods in deep neural networks.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation A benchmark for interpretability methods in deep neural networks

Reference 16

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This paper cites Unre- stricted permutation forces extrapolation: variable impor- tance requires at least one more model, or there is no free variable importance.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Unre- stricted permutation forces extrapolation: variable impor- tance requires at least one more model, or there is no free variable importance

Reference 17

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This paper cites Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness?.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness?

Reference 18

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This paper cites Logic Traps in Evaluating Attribution Scores.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Logic Traps in Evaluating Attribution Scores

Reference 19

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This paper cites The (un) reliability of saliency methods.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation The (un) reliability of saliency methods

Reference 20

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This paper cites Captum: A unified and generic model interpretability library for PyTorch.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Captum: A unified and generic model interpretability library for PyTorch

Reference 21

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This paper cites Investigating sanity checks for saliency maps with image and text classification.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Investigating sanity checks for saliency maps with image and text classification

Reference 22

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This paper cites Shapley residuals: Quantifying the limits of the shapley value for explana- tions.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Shapley residuals: Quantifying the limits of the shapley value for explana- tions

Reference 23

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This paper cites Unmasking clever hans predictors and as- sessing what machines really learn.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Unmasking clever hans predictors and as- sessing what machines really learn

Reference 24

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Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Unresolved cited work

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This paper cites An experimental study of quantitative evaluations on saliency methods.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation An experimental study of quantitative evaluations on saliency methods

Reference 26

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This paper cites A unified approach to interpreting model predictions.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation A unified approach to interpreting model predictions

Reference 27

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This paper cites Logic-based explainability in ma- chine learning.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Logic-based explainability in ma- chine learning

Reference 28

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This paper cites Interpretable machine learning.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Interpretable machine learning

Reference 29

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This paper cites Meaningful explanations of black box ai decision systems.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Meaningful explanations of black box ai decision systems

Reference 30

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This paper cites Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey

Reference 31

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This paper cites A Consistent and Efficient Evaluation Strategy for Attribution Methods.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation A Consistent and Efficient Evaluation Strategy for Attribution Methods

Reference 32

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This paper cites Evaluating feature attribution: An information-theoretic perspective.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Evaluating feature attribution: An information-theoretic perspective

Reference 33

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This paper cites Learning interpretable models.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Learning interpretable models

Reference 34

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This paper cites Grad-cam: Visual explanations from deep networks via gradient-based localization.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Grad-cam: Visual explanations from deep networks via gradient-based localization

Reference 35

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This paper cites Do input gradients highlight discriminative features? Advances in Neural Information Processing Systems, 34:2046–2059, 2021.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Do input gradients highlight discriminative features? Advances in Neural Information Processing Systems, 34:2046–2059, 2021

Reference 36

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This paper cites Learning important features through propagating acti- vation differences.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Learning important features through propagating acti- vation differences

Reference 37

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This paper cites When explanations lie: Why many modified bp attributions fail.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation When explanations lie: Why many modified bp attributions fail

Reference 38

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This paper cites Fooling lime and shap: Ad- versarial attacks on post hoc explanation methods.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Fooling lime and shap: Ad- versarial attacks on post hoc explanation methods

Reference 39

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This paper cites Logical explanations for deep relational machines using relevance information.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Logical explanations for deep relational machines using relevance information

Reference 40

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This paper cites Visu- alizing the impact of feature attribution baselines.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Visu- alizing the impact of feature attribution baselines

Reference 41

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This paper cites Ax- iomatic attribution for deep networks.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Ax- iomatic attribution for deep networks

Reference 42

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This paper cites Sanity checks for saliency metrics.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Sanity checks for saliency metrics

Reference 43

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This paper cites Evaluation of post-hoc xai ap- proaches through synthetic tabular data.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Evaluation of post-hoc xai ap- proaches through synthetic tabular data

Reference 44

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This paper cites Attention is all you need.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Attention is all you need

Reference 45

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This paper cites Transformers in Time Series: A Survey.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Transformers in Time Series: A Survey

Reference 46

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This paper cites Evaluating the Correctness of Explainable AI Algorithms for Classification.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Evaluating the Correctness of Explainable AI Algorithms for Classification

Reference 47

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This paper cites Revisiting Sanity Checks for Saliency Maps.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Revisiting Sanity Checks for Saliency Maps

Reference 48

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This paper cites Visualizing and un- derstanding convolutional networks.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation Visualizing and un- derstanding convolutional networks

Reference 49

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This paper cites A survey on neural network interpretability.

Saliency Methods are Encoders: Analysing Logical Relations Towards Interpretation A survey on neural network interpretability

Reference 50

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