Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions | Paper Citation Record

Observation 12b1fd65-095e-4d83-8874-adfe148d9444 · outbound

This paper cites Sanity checks for saliency maps,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Sanity checks for saliency maps,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.439934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e390553c-9777-475c-917c-b7ccd5cc5718 · outbound

This paper cites Logic Traps in Evaluating Attribution Scores.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Logic Traps in Evaluating Attribution Scores

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-10T15:27:09.706631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a7647d1b-b54e-4407-94e4-b759174effe2 · outbound

This paper cites Evaluation of post-hoc interpretability methods in time- series classification,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Evaluation of post-hoc interpretability methods in time- series classification,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.425926Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6957a905-ce00-49af-9157-5492ec64f338 · outbound

This paper cites Saliency methods are encoders: Analysing logical relations towards interpreta- tion,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Saliency methods are encoders: Analysing logical relations towards interpreta- tion,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.411803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5f7a5a30-d713-459f-98b3-2e2d325a4a74 · outbound

This paper cites Constructing global coherence representations: Identifying interpretability and coherences of transformer attention in time series data,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Constructing global coherence representations: Identifying interpretability and coherences of transformer attention in time series data,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.397522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 27e25d75-1491-4b2d-b4d4-fb28ef1c1745 · outbound

This paper cites Abstracting local transformer attention for enhancing interpretability on time series data.,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Abstracting local transformer attention for enhancing interpretability on time series data.,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.382481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 551b21bf-a9b4-459b-9b49-23981df88319 · outbound

This paper cites Extracting Interpretable Local and Global Representations from Attention on Time Series.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Extracting Interpretable Local and Global Representations from Attention on Time Series

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-08-10T15:27:09.686930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 611cf5c4-006c-4974-b9a7-edbb0beebadd · outbound

This paper cites Molnar, Interpretable machine learning.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Molnar, Interpretable machine learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.218783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96892492-01fa-4512-9785-5f9e3a0b3a8b · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Joint Shapley values: a measure of joint feature importance

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.223184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa009095-3de5-4409-a7f5-b40be0edbef9 · outbound

This paper cites Shapley residuals: Quantifying the limits of the shapley value for explanations,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Shapley residuals: Quantifying the limits of the shapley value for explanations,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.356984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9af148de-7ad4-4b8b-b40a-d0da6d6cf07b · outbound

This paper cites Faith-shap: The faithful shapley interaction index,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Faith-shap: The faithful shapley interaction index,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.342418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ce03b40d-678a-48c6-9476-a29edfc440ed · outbound

This paper cites Disentangling Interactions and Dependencies in Feature Attribution.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Disentangling Interactions and Dependencies in Feature Attribution

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.236604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 204fe287-7f85-4636-a796-ea191641d021 · outbound

This paper cites Shap-iq: Unified approximation of any-order shapley interactions,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Shap-iq: Unified approximation of any-order shapley interactions,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.327689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 26d9e51c-bf3e-49b1-90a2-efbdaab2a1e0 · outbound

This paper cites Interpreting multivariate shapley interactions in dnns,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Interpreting multivariate shapley interactions in dnns,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.313140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0ef48b0d-4875-47e0-957d-d2b66cd4daa0 · outbound

This paper cites How does this interaction affect me? interpretable attribution for feature interactions,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions How does this interaction affect me? interpretable attribution for feature interactions,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.299303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8fc63d99-2ac8-4189-8cf2-cd38bad6c3f4 · outbound

This paper cites Explaining explanations: Axiomatic feature interactions for deep net- works,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Explaining explanations: Axiomatic feature interactions for deep net- works,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.285009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 13620db0-ed1c-4e00-b5cc-fd6b7b4e4609 · outbound

This paper cites Ma- chine learning interpretability: A survey on methods and metrics,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Ma- chine learning interpretability: A survey on methods and metrics,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.269352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 98cda0a2-7bd8-44d6-a4f3-692d62a5cc7f · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions An experimental study of quantitative evaluations on saliency methods,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.255094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation de08615f-99ab-4959-8630-871c66fadac0 · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions The (un) reliability of saliency methods,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.240632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a9267f61-d05d-462c-a48d-11d749b49ad0 · outbound

This paper cites Do input gradients highlight discriminative features?,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Do input gradients highlight discriminative features?,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.225712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 70c24ef6-45bb-4ec8-a6ba-66f53fc82aef · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Investigating sanity checks for saliency maps with image and text classification

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-08-10T15:27:09.624546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9b9a5887-7112-463e-a016-74a4bf28544d · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions When explanations lie: Why many modified bp attributions fail,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.211474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 381e743a-25dd-4ef1-bbe2-553b2c6271bb · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness?

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.284368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f148f8c9-f09b-4a47-977d-af5db34268d3 · outbound

This paper cites On Baselines for Local Feature Attributions.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions On Baselines for Local Feature Attributions

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.289201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fe63e6b-e5d2-4e7b-aef4-96cd9649bd49 · outbound

This paper cites Visualizing the impact of feature attribution baselines,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Visualizing the impact of feature attribution baselines,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.293451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2de56fc2-03f9-490c-a0ef-447878b793b2 · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions A benchmark for interpretability methods in deep neural networks,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.188407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d2c1555c-1d0d-4022-b0c1-b1e228613e72 · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions A Consistent and Efficient Evaluation Strategy for Attribution Methods

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.301978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4febb512-dc8d-458e-8310-59ad18070dc7 · outbound

This paper cites Geometric remove-and-retrain (goar): Coordinate-invariant explain- able ai assessment,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Geometric remove-and-retrain (goar): Coordinate-invariant explain- able ai assessment,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.175123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation aa28cb21-72ba-4e5f-9908-8a9bb59a4e10 · outbound

This paper cites Learning global pairwise interactions with bayesian neural networks,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Learning global pairwise interactions with bayesian neural networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.161529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c812a67d-811b-4eba-bca1-f3f8b0e6bd5f · outbound

This paper cites Fooling lime and shap: Adversarial attacks on post hoc explanation methods,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Fooling lime and shap: Adversarial attacks on post hoc explanation methods,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.147807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 100fd317-cfb6-436c-a98d-84e70a536b5e · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Shapley values for feature selection: The good, the bad, and the axioms,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.132352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 29efb6d6-244d-4ba1-a5f7-080f4985b383 · outbound

This paper cites Show me what you’re looking for: Visualizing abstracted transformer attention for enhancing their local interpretability on time series data,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Show me what you’re looking for: Visualizing abstracted transformer attention for enhancing their local interpretability on time series data,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.116953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4c328d74-b4cf-42b5-8b04-06f8761ce70d · outbound

This paper cites A survey on neural network interpretability,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions A survey on neural network interpretability,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.103106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 372d121a-d7da-46c4-bb0b-3cb06093f6ba · outbound

This paper cites Logic-based explainability in machine learning,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Logic-based explainability in machine learning,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.088544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 717e2e01-e6ba-4812-9762-0a5eef5d9235 · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Revisit fuzzy neural network: bridging the gap between fuzzy logic and deep learning,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.074788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e337f7e8-1612-4f6b-b5f5-7753f5096789 · outbound

This paper cites Neural-symbolic learning and reasoning: A survey and interpretation,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Neural-symbolic learning and reasoning: A survey and interpretation,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.061603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 967273c2-fd30-408f-ad0e-ac3167334327 · outbound

This paper cites Logical expla- nations for deep relational machines using relevance information,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Logical expla- nations for deep relational machines using relevance information,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.046871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4072d9de-ef9c-49c8-bfbd-ffe559695d91 · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Meaningful explanations of black box ai decision systems,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.032693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 63b8a5e9-c535-44c8-a549-6297fcf55f86 · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Evaluating the Correctness of Explainable AI Algorithms for Classification

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.352549Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 593bca2a-8a9a-4ab3-aa9b-f9099209c44b · outbound

This paper cites Evaluation of post-hoc xai approaches through synthetic tabular data,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Evaluation of post-hoc xai approaches through synthetic tabular data,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.018644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation be3e2a59-2125-4a5b-a395-2efc637782ed · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Evaluating feature attribution: An information-theoretic perspective,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:10.004461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a9d18e62-f0e0-49b9-8f6d-ed58a5d49c5a · outbound

This paper cites Sanity checks for saliency metrics,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Sanity checks for saliency metrics,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.990015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 621a5a2d-17b6-4e19-b951-28c1edc39372 · outbound

This paper cites Metrics for saliency map evaluation of deep learning explanation methods,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Metrics for saliency map evaluation of deep learning explanation methods,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.975130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 36073e0a-372b-4a4a-b04d-c4c124231c32 · outbound

This paper cites Explaining deep neural networks: A survey on the global interpretation methods,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Explaining deep neural networks: A survey on the global interpretation methods,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.961082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6660f7c0-cfee-4421-bd84-3ae185349872 · outbound

This paper cites A Symbolic Representation of Time Series, with Implications for Streaming Algorithms,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions A Symbolic Representation of Time Series, with Implications for Streaming Algorithms,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.946505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 503b9618-1251-47b1-827d-142f05c30618 · outbound

This paper cites Experiencing SAX: A Novel Symbolic Representation of Time Series,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Experiencing SAX: A Novel Symbolic Representation of Time Series,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.933266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ac749019-9b41-4640-b6c0-b86c8cc7b7c7 · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Explainable Artificial Intelligence (XAI) on TimeSeries Data: A Survey

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.387297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 497913d1-7ae1-4a7a-8853-e56bac40284f · outbound

This paper cites Explanation-aware feature selection using symbolic time series abstraction: approaches and experiences in a petro-chemical production context,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Explanation-aware feature selection using symbolic time series abstraction: approaches and experiences in a petro-chemical production context,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.919518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 92a600ba-f5de-44b8-973c-f162dfc843ad · outbound

This paper cites Imbalanced-learn: A python toolbox to tackle the curse of imbalanced datasets in machine learning,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Imbalanced-learn: A python toolbox to tackle the curse of imbalanced datasets in machine learning,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.904882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 81f4f51e-c4d8-4258-9d58-dfccefc6d44f · outbound

This paper cites Transformers in Time Series: A Survey.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Transformers in Time Series: A Survey

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.399779Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40c5ded6-f1cc-4370-8a75-084ffc321998 · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Grad-cam: Visual explanations from deep networks via gradient-based localization,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.890083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c35d906d-d864-410e-887a-127ed5358e6a · outbound

This paper cites Deep residual learning for image recognition,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Deep residual learning for image recognition,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.407594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 984a9634-f672-47a4-ac35-6875dab5fe5b · outbound

This paper cites Attention is all you need,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Attention is all you need,

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.411505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 966fab4d-41f9-4f58-a44a-2411482d2cc8 · outbound

This paper cites Transformer inter- pretability beyond attention visualization,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Transformer inter- pretability beyond attention visualization,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.858253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c70361d0-7753-4acf-b644-4b3abf0e0e66 · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.843913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e37eb5f3-4521-4c49-a23e-1e66a4fe3ddf · outbound

This paper cites Quantifying Attention Flow in Transformers.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Quantifying Attention Flow in Transformers

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.424058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 413dd49f-c787-48e1-9577-2ed7086db575 · outbound

This paper cites Axiomatic at- tribution for deep networks,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Axiomatic at- tribution for deep networks,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.830502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 394d3a8c-9c1d-40ad-b289-c0cb643e548c · outbound

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

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Captum: A unified and generic model interpretability library for PyTorch

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.432427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9dcd6919-962d-45e3-8c26-8708dc425a3b · outbound

This paper cites Learning important features through propagating activation differ- ences,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Learning important features through propagating activation differ- ences,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.816232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 013e0af3-ce36-422f-b768-172170f78d52 · outbound

This paper cites Visualizing and understand- ing convolutional networks,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Visualizing and understand- ing convolutional networks,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.800961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e20bdc9a-2439-4d6c-8153-7108e52f8058 · outbound

This paper cites Pytorch library for cam methods.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Pytorch library for cam methods

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.785921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2c005167-2f97-47a6-b0ed-50da64162569 · outbound

This paper cites Grad-cam++: Generalized gradient- based visual explanations for deep convolutional net- works,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Grad-cam++: Generalized gradient- based visual explanations for deep convolutional net- works,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.772155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b12e1712-2f97-4dde-9d49-6b0a684fb273 · outbound

This paper cites A unified approach to interpreting model predictions,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions A unified approach to interpreting model predictions,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.758559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 590dc91d-6e09-4880-8e96-1c5d7283cdf5 · outbound

This paper cites On the effects of non-normality on the distribution of the sample product-moment correlation coefficient,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions On the effects of non-normality on the distribution of the sample product-moment correlation coefficient,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.743812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 04514d13-7f40-4cad-8929-695ebf6ef240 · outbound

This paper cites Random forests,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Random forests,

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.463299Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a3c9a4d-0cd0-40c9-9e13-d59eacbda7b0 · outbound

This paper cites Unmasking clever hans predictors and assessing what machines really learn,.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Unmasking clever hans predictors and assessing what machines really learn,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T15:27:09.721257Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 03231093-a8fc-4b28-847d-e68aa27d1a3b · outbound

This paper cites Revisiting Sanity Checks for Saliency Maps.

Saliency Maps are Ambiguous: Analysis of Logical Relations on First and Second Order Attributions Revisiting Sanity Checks for Saliency Maps

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-10T15:27:09.471658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers