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Paper Citation Record · LEDGER

Towards Evaluating the Robustness of Neural Networks

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 inbound Pith citation observations for arXiv:1608.04644.

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

pith.paper-citation-record.v1
1608.04644 v2

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:30:12.861686Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-25T01:56:32.560598Z

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External citation measurements

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Outbound references

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Pith citing papers

Observation 7c6dc9f1-337d-450b-976f-98d13c187494 · inbound

Affine Disentangled GAN for Interpretable and Robust AV Perception cites this paper.

Affine Disentangled GAN for Interpretable and Robust AV Perception Towards Evaluating the Robustness of Neural Networks

Reference 2

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local_arxiv, observed 2026-05-25T01:56:32.563139Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c317ce83-dc64-439c-9f38-96ef446fa9f7 · inbound

Stateful Detection of Black-Box Adversarial Attacks cites this paper.

Stateful Detection of Black-Box Adversarial Attacks Towards Evaluating the Robustness of Neural Networks

Reference 10

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local_arxiv, observed 2026-05-24T22:50:03.114573Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d8e9c506-78cf-4785-99b1-afbb31a38e3e · inbound

Why Blocking Targeted Adversarial Perturbations Impairs the Ability to Learn cites this paper.

Why Blocking Targeted Adversarial Perturbations Impairs the Ability to Learn Towards Evaluating the Robustness of Neural Networks

Reference 5

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local_arxiv, observed 2026-05-24T23:15:03.495987Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation dba6a7b7-a9b3-4b1c-8f88-39473116759f · inbound

Measuring the Transferability of Adversarial Examples cites this paper.

Measuring the Transferability of Adversarial Examples Towards Evaluating the Robustness of Neural Networks

Reference 1

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local_arxiv, observed 2026-05-24T21:29:57.996511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 27e46986-c939-45fc-a711-5f06ba7154d1 · inbound

A principled approach for generating adversarial images under non-smooth dissimilarity metrics cites this paper.

A principled approach for generating adversarial images under non-smooth dissimilarity metrics Towards Evaluating the Robustness of Neural Networks

Reference 8

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Observation 94ba226c-2252-4021-9332-e197553b8f60 · inbound

BlurNet: Defense by Filtering the Feature Maps cites this paper.

BlurNet: Defense by Filtering the Feature Maps Towards Evaluating the Robustness of Neural Networks

Reference 5

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Observation 5ffc6531-e2bf-4b11-819c-a7128df421d9 · inbound

Reliable Evaluation of Attribution Maps in CNNs: A Perturbation-Based Approach cites this paper.

Reliable Evaluation of Attribution Maps in CNNs: A Perturbation-Based Approach Towards Evaluating the Robustness of Neural Networks

Reference 44

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source=arxiv_source observed=2026-08-12T14:46:12.309521Z digest=sha256:52d3f22642b35d029e356cb86a739dea41cd5b5737e8a57b0af7479a8a5a6a6d

Observation 91f74a3d-40f8-47dd-bcf9-5a2b45878f17 · inbound

Err on the Side of Texture: Texture Bias on Real Data cites this paper.

Err on the Side of Texture: Texture Bias on Real Data Towards Evaluating the Robustness of Neural Networks

Reference 17

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Observation 1f28775a-c5a0-4938-a24a-2383d56d6e0b · inbound

A Comprehensive Review of Adversarial Attacks on Machine Learning cites this paper.

A Comprehensive Review of Adversarial Attacks on Machine Learning Towards Evaluating the Robustness of Neural Networks

Reference 4

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Observation ad48b854-9e53-4206-a480-579fa5810be2 · inbound

CP-Guard: Malicious Agent Detection and Defense in Collaborative Bird's Eye View Perception cites this paper.

CP-Guard: Malicious Agent Detection and Defense in Collaborative Bird's Eye View Perception Towards Evaluating the Robustness of Neural Networks

Reference 3

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Observation efd8292f-c2c3-4c34-b8c2-c3f0bd975988 · inbound

Targeted View-Invariant Adversarial Perturbations for 3D Object Recognition cites this paper.

Targeted View-Invariant Adversarial Perturbations for 3D Object Recognition Towards Evaluating the Robustness of Neural Networks

Reference 6

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source=arxiv_source observed=2026-08-11T13:15:05.197313Z digest=sha256:f97b29fe9225842c074b414cb71bf0d35f2d2eca313816ca833fdf2e70f7cc0b

Observation 023c7f7d-0349-4015-9a32-650bbe16b050 · inbound

Towards Adversarially Robust Deep Metric Learning cites this paper.

Towards Adversarially Robust Deep Metric Learning Towards Evaluating the Robustness of Neural Networks

Reference 7

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Observation 7e7f1ff9-d5cb-4f79-a289-f191482cdee6 · inbound

A Numerical Gradient Inversion Attack in Variational Quantum Neural-Networks cites this paper.

A Numerical Gradient Inversion Attack in Variational Quantum Neural-Networks Towards Evaluating the Robustness of Neural Networks

Reference 69

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Observation 4b9745d8-4989-4440-bad2-2651be9f528a · inbound

A Framework for Adversarial Analysis of Decision Support Systems Prior to Deployment cites this paper.

A Framework for Adversarial Analysis of Decision Support Systems Prior to Deployment Towards Evaluating the Robustness of Neural Networks

Reference 3

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Observation dcc03eda-692d-4b7a-b9b4-60c93f295392 · inbound

Robustness as Architecture: Designing IQA Models to Withstand Adversarial Perturbations cites this paper.

Robustness as Architecture: Designing IQA Models to Withstand Adversarial Perturbations Towards Evaluating the Robustness of Neural Networks

Reference 2017

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source=pdf_text observed=2026-08-07T10:37:11.399156Z digest=sha256:890601d208c062f08acd8a816822679ae5c82c6613a3e2e9c07df98235188e65

Observation c8bc226d-acb1-4c1a-8b0b-d8b11f8ced72 · inbound

Teach Me to Trick: Exploring Adversarial Transferability via Knowledge Distillation cites this paper.

Teach Me to Trick: Exploring Adversarial Transferability via Knowledge Distillation Towards Evaluating the Robustness of Neural Networks

Reference 1

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no resolver link, observed 2026-08-06T12:14:57.219950Z

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Observation 702430e7-ddde-4a7f-9978-ba6f357107e2 · inbound

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods cites this paper.

Investigating the Invertibility of Multimodal Latent Spaces: Limitations of Optimization-Based Methods Towards Evaluating the Robustness of Neural Networks

Reference 2

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Observation 2a8cb003-69ce-4f67-b6b4-0b8d3b430be9 · inbound

Adversarial Examples Are Not Bugs, They Are Superposition cites this paper.

Adversarial Examples Are Not Bugs, They Are Superposition Towards Evaluating the Robustness of Neural Networks

Reference 3

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Observation 4ae7b7a7-e422-4ce1-bea9-04c679648037 · inbound

SyncBreaker:Stage-Aware Multimodal Adversarial Attacks on Audio-Driven Talking Head Generation cites this paper.

SyncBreaker:Stage-Aware Multimodal Adversarial Attacks on Audio-Driven Talking Head Generation Towards Evaluating the Robustness of Neural Networks

Reference 2

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arxiv_id, observed 2026-05-11T06:41:26.756514Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 47b31ef9-ffb9-44e8-be68-bba7d53147c4 · inbound

SyncBreaker:Stage-Aware Multimodal Adversarial Attacks on Audio-Driven Talking Head Generation cites this paper.

SyncBreaker:Stage-Aware Multimodal Adversarial Attacks on Audio-Driven Talking Head Generation Towards Evaluating the Robustness of Neural Networks

Reference 2

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Observation d377a4aa-8187-4905-ac29-601318b95ffa · inbound

Auto-ART: Structured Literature Synthesis and Automated Adversarial Robustness Testing cites this paper.

Auto-ART: Structured Literature Synthesis and Automated Adversarial Robustness Testing Towards Evaluating the Robustness of Neural Networks

Reference 13

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arxiv_id, observed 2026-05-10T00:39:48.181702Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 5e7fd3b0-d4fa-478f-8c4d-35b7f0e7f90a · inbound

Transferable Physical-World Adversarial Patches Against Pedestrian Detection Models cites this paper.

Transferable Physical-World Adversarial Patches Against Pedestrian Detection Models Towards Evaluating the Robustness of Neural Networks

Reference 14

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arxiv_id, observed 2026-05-11T19:16:07.998582Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 07cba9a8-01ee-4f9f-95e2-a2563837a415 · inbound

Memory Efficient Full-gradient Attacks (MEFA) Framework for Adversarial Defense Evaluations cites this paper.

Memory Efficient Full-gradient Attacks (MEFA) Framework for Adversarial Defense Evaluations Towards Evaluating the Robustness of Neural Networks

Reference 7

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arxiv_id, observed 2026-05-11T19:01:18.323639Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-08T12:53:11.185208Z digest=sha256:96ab8595271c28a3a36843b79784ae7e3622ebb0d2f35afd6f30d397d1919929

Observation 2bd20a56-d7b9-45ea-91e3-902ba6f6830a · inbound

Uncovering Hidden Systematics in Neural Network Models for High Energy Physics cites this paper.

Uncovering Hidden Systematics in Neural Network Models for High Energy Physics Towards Evaluating the Robustness of Neural Networks

Reference 18

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arxiv_id, observed 2026-05-11T03:50:55.999557Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 34945939-0589-4161-9bbf-2e2d2fb5d161 · inbound

BadSKP: Backdoor Attacks on Knowledge Graph-Enhanced LLMs with Soft Prompts cites this paper.

BadSKP: Backdoor Attacks on Knowledge Graph-Enhanced LLMs with Soft Prompts Towards Evaluating the Robustness of Neural Networks

Reference 34

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arxiv_id, observed 2026-05-13T05:12:17.830359Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 91a15cd5-9881-487f-a5a1-8b9ee8db3e44 · inbound

Fast SDP certification of neural networks : towards large multi-class datasets cites this paper.

Fast SDP certification of neural networks : towards large multi-class datasets Towards Evaluating the Robustness of Neural Networks

Reference 5

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Observation e3a7fb5d-fbe4-43d2-8a9d-ffe9eab223f7 · inbound

When cheap gradients fail: the measurement cost of attacking quantum classifiers cites this paper.

When cheap gradients fail: the measurement cost of attacking quantum classifiers Towards Evaluating the Robustness of Neural Networks

Reference 4

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