Attribution for Enhanced Explanation with Transferable Adversarial eXploration | Paper Citation Record

Observation 81a12d11-1166-4629-acd4-e62ca0c4668c · outbound

This paper cites Deep learning,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Deep learning,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.493813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd7319ed-4cd2-4a9e-b625-30adeb043f0e · outbound

This paper cites Dermatologist-level classification of skin cancer with deep neural networks,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Dermatologist-level classification of skin cancer with deep neural networks,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.499550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74602d3b-ddf6-478c-b8d9-c2d6950fcf7c · outbound

This paper cites Xgboost: A scalable tree boosting system,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Xgboost: A scalable tree boosting system,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.504767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bfe390d8-f450-40c1-adcf-5fbe288b5f38 · outbound

This paper cites Towards A Rigorous Science of Interpretable Machine Learning.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Towards A Rigorous Science of Interpretable Machine Learning

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.510129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f12712a-50f3-4bca-825c-ba681aa0b595 · outbound

This paper cites The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery.,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery.,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.714158Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation de40d7da-d3ca-43ea-9644-a4b6fe3d4be6 · outbound

This paper cites Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.520011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 130f19eb-26b6-4fc8-b1b4-fd9d1445aa66 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Explaining and Harnessing Adversarial Examples

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.527406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5865bd0-4332-4f7b-a196-ec5bd90cc525 · outbound

This paper cites A survey on bias and fairness in machine learning,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration A survey on bias and fairness in machine learning,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.532873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 903e0cf6-52ad-453d-8f62-0536e2e71bb4 · outbound

This paper cites Propagating transparency: A deep dive into the interpretability of neural networks,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Propagating transparency: A deep dive into the interpretability of neural networks,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.670266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 99c81095-ae74-48ac-93c8-0cdeabd98443 · outbound

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

Attribution for Enhanced Explanation with Transferable Adversarial eXploration A benchmark for interpretability methods in deep neural networks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.650971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fafb6085-a30c-4b3d-ad57-a696d308ddae · outbound

This paper cites Methods for interpreting and understanding deep neural networks,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Methods for interpreting and understanding deep neural networks,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.546619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b41d6f55-e1d4-4939-9d78-209da470d453 · outbound

This paper cites A survey on explainable artificial intelligence (xai): Toward medical xai,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration A survey on explainable artificial intelligence (xai): Toward medical xai,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.551855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e1060f6-006f-4ba1-b90b-e8600fee59f1 · outbound

This paper cites Interpretability of machine learning methods applied to neuroimaging,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Interpretability of machine learning methods applied to neuroimaging,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.606612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c74a40af-f1f6-4d6c-b736-1d1e7beabbb5 · outbound

This paper cites Simple black-box adversarial attacks on deep neural networks.,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Simple black-box adversarial attacks on deep neural networks.,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.588993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 71d0a27b-a704-40c4-81ea-bda7f46a0c65 · outbound

This paper cites Di-aa: An interpretable white-box attack for fooling deep neural networks,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Di-aa: An interpretable white-box attack for fooling deep neural networks,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.570884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 59a5f3bb-e648-4ecd-974e-cb198cb34dd0 · outbound

This paper cites Improving the adversarial robustness and interpretability of deep neural networks by regularizing their input gra- dients,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Improving the adversarial robustness and interpretability of deep neural networks by regularizing their input gra- dients,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.546540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 213bc81b-f467-4857-a030-b67310c4fa7d · outbound

This paper cites Fooling network inter- pretation in image classification,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Fooling network inter- pretation in image classification,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.524760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fd313251-581a-41ff-85d2-f2d7dbf24f6f · outbound

This paper cites Adversarial perturbation defense on deep neural networks,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Adversarial perturbation defense on deep neural networks,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.502235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8404bf02-275a-4d73-a8ae-12a1489104a2 · outbound

This paper cites Interpreting adversarial examples in deep learning: A review,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Interpreting adversarial examples in deep learning: A review,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.484761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a4b5456c-6bca-46da-94a2-333ac95a3f09 · outbound

This paper cites Attexplore: Attribution for explanation with model parameters exploration,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Attexplore: Attribution for explanation with model parameters exploration,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.467283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c70593ce-6006-4b6f-84f6-ca98bf6a8a6f · outbound

This paper cites ” why should i trust you?.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration ” why should i trust you?

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.600693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41411573-fd11-44b3-b8c1-829f89a9a793 · outbound

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

Attribution for Enhanced Explanation with Transferable Adversarial eXploration A unified approach to interpreting model predictions,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.605712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34a3ba29-e7bb-4f98-a4ed-f7c602aded6f · outbound

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

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Learning important features through propagating activation differences,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.424591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4e5cc2b9-3b4c-4b0d-95c4-e699ce92d00d · outbound

This paper cites Axiomatic attribution for deep networks,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Axiomatic attribution for deep networks,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.407255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7ad29b38-883e-4c0b-abd0-6153f4bbe03a · outbound

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

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.622681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e67e531-ee0d-48aa-9121-9802f4b86059 · outbound

This paper cites SmoothGrad: removing noise by adding noise.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration SmoothGrad: removing noise by adding noise

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.628315Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c37fdd65-c134-48ac-9050-ed11f6b04fe0 · outbound

This paper cites Guided integrated gradients: An adaptive path method for removing noise,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Guided integrated gradients: An adaptive path method for removing noise,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.386851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1ef12e17-9b2a-46e1-9cee-f5c8b5364429 · outbound

This paper cites Improving performance of deep learning models with axiomatic attribution priors and expected gradients,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Improving performance of deep learning models with axiomatic attribution priors and expected gradients,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.364252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 701bc7c5-0bfe-4e92-a8a0-8ed8ecf96c13 · outbound

This paper cites Robust Models Are More Interpretable Because Attributions Look Normal.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Robust Models Are More Interpretable Because Attributions Look Normal

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.644260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5f9ef4f-b901-435b-9298-a1cdd572fd66 · outbound

This paper cites Fast axiomatic attribution for neural networks,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Fast axiomatic attribution for neural networks,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.349420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a0fe9ce5-48a0-487f-b25b-44312e0cf6b5 · outbound

This paper cites Explaining deep neural network models with adversarial gradient integration,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Explaining deep neural network models with adversarial gradient integration,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.333045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a06953d0-71db-49f2-a353-771ce81de674 · outbound

This paper cites MFABA: A More Faithful and Accelerated Boundary-based Attribution Method for Deep Neural Networks.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration MFABA: A More Faithful and Accelerated Boundary-based Attribution Method for Deep Neural Networks

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-08-11T00:19:48.957629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1d94d594-41a0-4946-bd14-6e611180d577 · outbound

This paper cites Iterative search attribution for deep neural networks,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Iterative search attribution for deep neural networks,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.314195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 24c357fc-b3ca-41f8-9208-b91e9a0f4e27 · outbound

This paper cites Enhancing Model Interpretability with Local Attribution over Global Exploration.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Enhancing Model Interpretability with Local Attribution over Global Exploration

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-08-11T00:19:48.934179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d52c7128-af61-4e03-8688-7897b934e3d8 · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.677638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97b200c8-8390-47d3-8884-9ee969ba9b51 · outbound

This paper cites Towards evaluating the robustness of neural networks,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Towards evaluating the robustness of neural networks,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.294216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5a854719-6ea4-4674-bcb1-a4f51cc27af0 · outbound

This paper cites Benchmarking transferable adversarial attacks.,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Benchmarking transferable adversarial attacks.,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.277762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 73632eb1-a9f3-4fe5-9270-ba2eeaac66fc · outbound

This paper cites Boost- ing adversarial attacks with momentum,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Boost- ing adversarial attacks with momentum,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.257255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f0c857fb-db92-45f5-81c0-fe38bb69db9a · outbound

This paper cites Transferable adversarial attack for both vision transformers and convolutional networks via momentum integrated gradients,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Transferable adversarial attack for both vision transformers and convolutional networks via momentum integrated gradients,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.240609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9fbed891-a686-4310-951a-0c8d8e4fd604 · outbound

This paper cites Improving transferability of adversarial examples with input diversity,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Improving transferability of adversarial examples with input diversity,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.220701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9ab00d03-a491-4b82-bd1c-224fb6a580a8 · outbound

This paper cites Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.712400Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18221b05-3faa-4ff5-bda0-1f9c0551d86b · outbound

This paper cites Evading defenses to transferable adversarial examples by translation-invariant attacks,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Evading defenses to transferable adversarial examples by translation-invariant attacks,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.202140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c0162563-c057-4a0b-a792-648ac8ba4f1b · outbound

This paper cites Improving adversarial transferability via neuron attribution-based attacks,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Improving adversarial transferability via neuron attribution-based attacks,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.185900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 656613ce-8895-415a-9e9c-d4957576e99a · outbound

This paper cites Structure invariant transformation for better adversarial transferability,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Structure invariant transformation for better adversarial transferability,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.170845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 02bb85cb-c6cd-4173-92b3-f5b7190d265f · outbound

This paper cites Boosting adversarial transferability via gradient relevance attack,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Boosting adversarial transferability via gradient relevance attack,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.155019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 77c60702-5cbe-495e-9c9b-d06287fc48e8 · outbound

This paper cites Improving adversarial transferability via frequency-based stationary point search,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Improving adversarial transferability via frequency-based stationary point search,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.138024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2738f06b-7d82-4e95-823d-36de8209845d · outbound

This paper cites Adversarial examples in the physical world,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Adversarial examples in the physical world,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.741774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a7549f6-616c-4779-8eed-2863b24a53de · outbound

This paper cites Frequency domain model augmentation for adversarial attack,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Frequency domain model augmentation for adversarial attack,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:19:49.105512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c2b1e97b-51c3-40b2-b613-05f6723f371b · outbound

This paper cites Imagenet: A large-scale hierarchical image database,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Imagenet: A large-scale hierarchical image database,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.751303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52ad8a5b-2636-438c-88d7-6611810e4df2 · outbound

This paper cites Rethinking the inception architecture for computer vision,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Rethinking the inception architecture for computer vision,

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.756636Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f3eccc3-8a92-412f-94f7-d71dfab2be30 · outbound

This paper cites Deep residual learning for image recognition,.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Deep residual learning for image recognition,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.764151Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 195f7407-3f3b-4024-98c1-3746f886e4ef · outbound

This paper cites Very Deep Convolutional Networks for Large-Scale Image Recognition.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration Very Deep Convolutional Networks for Large-Scale Image Recognition

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.770345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0dd81bb-cc23-4f79-9bfc-4419fafd430e · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.775336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dbc0804-179f-47dd-b2b8-00fa4c389154 · outbound

This paper cites RISE: Randomized Input Sampling for Explanation of Black-box Models.

Attribution for Enhanced Explanation with Transferable Adversarial eXploration RISE: Randomized Input Sampling for Explanation of Black-box Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-11T00:19:48.780152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Coverage vector

Reference resolution

Outbound references

Pith citing papers