Paper Citation Record · LEDGER

Metric Learning for Adversarial Robustness

As of 18 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 2 inbound Pith citation observations for arXiv:1909.00900.

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

pith.paper-citation-record.v1
1909.00900 v2

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:37:26.141859Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:30:21.450443Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T16:07:41.126606Z

Reference resolution

53 of 53 outbound references displayed

verified exact5
verified fuzzy21
unresolved27
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0c7d73c9-de12-42b7-84ae-3ea3a9146a36 · outbound

This paper cites an unresolved cited work.

Metric Learning for Adversarial Robustness Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-14T05:37:26.741194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fc3c6ef5-90a6-436d-b923-2504187b8bf5 · outbound

This paper cites an unresolved cited work.

Metric Learning for Adversarial Robustness Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-14T05:37:26.730731Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4e8f9a04-b267-41c7-85c3-a63320849b53 · outbound

This paper cites an unresolved cited work.

Metric Learning for Adversarial Robustness Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-14T05:37:26.720478Z

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Observation 16309b79-f761-4a29-a03a-dd7d86782bca · outbound

This paper cites Goodfellow.

Metric Learning for Adversarial Robustness Goodfellow

Reference 4

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Observation a97637dc-47e5-4204-b31a-935b01c55f80 · outbound

This paper cites an unresolved cited work.

Metric Learning for Adversarial Robustness Unresolved cited work

Reference 5

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Observation a9809efa-9388-4fdb-ad37-3093c9a0928c · outbound

This paper cites Beyond triplet loss: a deep quadruplet network for person re-identification.

Metric Learning for Adversarial Robustness Beyond triplet loss: a deep quadruplet network for person re-identification

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-08-14T05:37:26.428970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e8c24480-c840-4f02-841d-98389786fa95 · outbound

This paper cites Parseval networks: Improving robustness to adversarial examples.

Metric Learning for Adversarial Robustness Parseval networks: Improving robustness to adversarial examples

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.687606Z

Source-reported events for the cited work

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Observation c984e8c4-cff6-499e-8bda-25af1001bccc · outbound

This paper cites Dhillon, Kamyar Azizzadenesheli, Zachary C.

Metric Learning for Adversarial Robustness Dhillon, Kamyar Azizzadenesheli, Zachary C

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.675508Z

Source-reported events for the cited work

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Observation cb8dee73-283e-4ea8-8552-9b3ed910796a · outbound

This paper cites Boosting adversarial attacks with momentum.

Metric Learning for Adversarial Robustness Boosting adversarial attacks with momentum

Reference 9

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Source-reported events for the cited work

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Observation 8603b1e4-4f13-46aa-b64b-13dd7c0161e9 · outbound

This paper cites Deep adversarial metric learning.

Metric Learning for Adversarial Robustness Deep adversarial metric learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.653734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8a802c06-aa0b-4caf-aac7-cc04f4845e91 · outbound

This paper cites Evaluating and Understanding the Robustness of Adversarial Logit Pairing.

Metric Learning for Adversarial Robustness Evaluating and Understanding the Robustness of Adversarial Logit Pairing

Reference 11

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Source-reported events for the cited work

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Observation fd001813-0653-4e41-81b1-1e94c0e1f1c8 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Metric Learning for Adversarial Robustness Explaining and Harnessing Adversarial Examples

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-14T05:37:25.980222Z

Source-reported events for the cited work

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Observation e6028baa-2b40-446a-a157-1f39a967fd71 · outbound

This paper cites Countering Adversarial Images using Input Transformations.

Metric Learning for Adversarial Robustness Countering Adversarial Images using Input Transformations

Reference 13

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Source-reported events for the cited work

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Observation 7b03eeb4-caa4-402b-b79a-17b1095bc0c8 · outbound

This paper cites Deep Speech: Scaling up end-to-end speech recognition.

Metric Learning for Adversarial Robustness Deep Speech: Scaling up end-to-end speech recognition

Reference 14

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Source-reported events for the cited work

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Observation 7d1e2cc5-3b42-42f2-86c7-d5240f6dec1d · outbound

This paper cites Deep metric learning using triplet network.

Metric Learning for Adversarial Robustness Deep metric learning using triplet network

Reference 15

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Source-reported events for the cited work

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Observation 4d6b0dcc-460e-41d5-8f89-5d94b343e74c · outbound

This paper cites Adversarial Logit Pairing.

Metric Learning for Adversarial Robustness Adversarial Logit Pairing

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-14T05:37:25.995512Z

Source-reported events for the cited work

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Observation 09ad0dff-be8e-438c-95f5-ecfe1b3d8da6 · outbound

This paper cites an unresolved cited work.

Metric Learning for Adversarial Robustness Unresolved cited work

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4795e537-1a97-42a7-a0f7-d51f872cfa5b · outbound

This paper cites Adversarial examples in the physical world.

Metric Learning for Adversarial Robustness Adversarial examples in the physical world

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T05:37:26.003241Z

Source-reported events for the cited work

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Observation 16a76e85-4636-4c57-b4e4-45ddb0d5263b · outbound

This paper cites Towards deep learning models resistant to adversarial attacks.

Metric Learning for Adversarial Robustness Towards deep learning models resistant to adversarial attacks

Reference 19

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Source-reported events for the cited work

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Observation 64afc757-6391-4ef7-8750-cb17fe1ca85a · outbound

This paper cites A probabilistic learning approach to uwb ranging error mitigation.

Metric Learning for Adversarial Robustness A probabilistic learning approach to uwb ranging error mitigation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.613727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2c195bdd-e61a-4d54-9493-229274533ea3 · outbound

This paper cites Distributed representations of words and phrases and their compositionality.

Metric Learning for Adversarial Robustness Distributed representations of words and phrases and their compositionality

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.601958Z

Source-reported events for the cited work

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Observation 5c4c3654-8617-4254-8d30-5059c8ae7ae2 · outbound

This paper cites Logit Pairing Methods Can Fool Gradient-Based Attacks.

Metric Learning for Adversarial Robustness Logit Pairing Methods Can Fool Gradient-Based Attacks

Reference 22

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Source-reported events for the cited work

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Observation ea01b395-d919-4610-b2ed-c88f5486caa6 · outbound

This paper cites Deep neural networks are easily fooled: High conﬁdence predictions for unrecognizable images.

Metric Learning for Adversarial Robustness Deep neural networks are easily fooled: High conﬁdence predictions for unrecognizable images

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.590625Z

Source-reported events for the cited work

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Observation 53f94442-9707-4297-9b4a-8614cb5bc437 · outbound

This paper cites Lipschitz regularized Deep Neural Networks generalize and are adversarially robust.

Metric Learning for Adversarial Robustness Lipschitz regularized Deep Neural Networks generalize and are adversarially robust

Reference 24

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Source-reported events for the cited work

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Observation f98efb69-4412-4b3a-82b6-b8e00a9ebc8d · outbound

This paper cites Improving Adversarial Robustness via Promoting Ensemble Diversity.

Metric Learning for Adversarial Robustness Improving Adversarial Robustness via Promoting Ensemble Diversity

Reference 25

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Source-reported events for the cited work

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Observation 69041560-6708-4d57-83ed-293346dfb3d3 · outbound

This paper cites Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples.

Metric Learning for Adversarial Robustness Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

Reference 26

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Source-reported events for the cited work

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Observation 7a63376c-c7db-4a29-bd18-e288a1bd5efc · outbound

This paper cites The Limitations of Deep Learning in Adversarial Settings.

Metric Learning for Adversarial Robustness The Limitations of Deep Learning in Adversarial Settings

Reference 27

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Source-reported events for the cited work

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Observation ed3579b8-c0b6-48b4-aef1-0e1c25174382 · outbound

This paper cites Generalizability vs. Robustness: Adversarial Examples for Medical Imaging.

Metric Learning for Adversarial Robustness Generalizability vs. Robustness: Adversarial Examples for Medical Imaging

Reference 28

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Source-reported events for the cited work

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Observation 4d8847a1-9fe4-4cc2-95b3-72aae6e4578c · outbound

This paper cites DeepXplore: Automated Whitebox Testing of Deep Learning Systems.

Metric Learning for Adversarial Robustness DeepXplore: Automated Whitebox Testing of Deep Learning Systems

Reference 29

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Source-reported events for the cited work

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Observation 29d8b47a-b592-4070-a457-d82d38bde700 · outbound

This paper cites Defend Deep Neural Networks Against Adversarial Examples via Fixed and Dynamic Quantized Activation Functions.

Metric Learning for Adversarial Robustness Defend Deep Neural Networks Against Adversarial Examples via Fixed and Dynamic Quantized Activation Functions

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-14T05:37:26.283857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 34465690-390e-42fc-bf59-3d617a57a3dd · outbound

This paper cites Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models.

Metric Learning for Adversarial Robustness Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models

Reference 31

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Source-reported events for the cited work

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Observation 9b8a1bec-8f31-49dd-af6e-bfc2f22be368 · outbound

This paper cites Facenet: A uniﬁed embedding for face recognition and clustering.

Metric Learning for Adversarial Robustness Facenet: A uniﬁed embedding for face recognition and clustering

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.578600Z

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Observation dee77b44-d775-4d49-81e6-abed517a3111 · outbound

This paper cites Improving the Generalization of Adversarial Training with Domain Adaptation.

Metric Learning for Adversarial Robustness Improving the Generalization of Adversarial Training with Domain Adaptation

Reference 33

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Observation 68e4046f-4150-438c-aa6e-9fcdc8272371 · outbound

This paper cites Deep metric learning via lifted structured feature embedding.

Metric Learning for Adversarial Robustness Deep metric learning via lifted structured feature embedding

Reference 34

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Observation d44f0445-9a25-44b9-a3b7-5584888192bd · outbound

This paper cites Goodfellow, and Rob Fergus.

Metric Learning for Adversarial Robustness Goodfellow, and Rob Fergus

Reference 35

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Source-reported events for the cited work

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Observation 7daf8ac6-3976-4152-96a6-d624c74fa3a0 · outbound

This paper cites DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars.

Metric Learning for Adversarial Robustness DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars

Reference 36

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Source-reported events for the cited work

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Observation f0bf0eb5-86c4-46e1-a901-b2b488d7cad6 · outbound

This paper cites Ensemble Adversarial Training: Attacks and Defenses.

Metric Learning for Adversarial Robustness Ensemble Adversarial Training: Attacks and Defenses

Reference 37

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Observation a730ba0e-4e38-4a2d-bc8c-8cc3dc6b5569 · outbound

This paper cites Robust- ness may be at odds with accuracy.

Metric Learning for Adversarial Robustness Robust- ness may be at odds with accuracy

Reference 38

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Source-reported events for the cited work

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Observation 8b9fbf79-eb7b-40c3-bce2-f4ba532ef2ef · outbound

This paper cites Are Labels Required for Improving Adversarial Robustness?.

Metric Learning for Adversarial Robustness Are Labels Required for Improving Adversarial Robustness?

Reference 39

Resolution: verified exact; local_arxiv, observed 2026-08-14T05:37:26.230598Z

Source-reported events for the cited work

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Observation 7c3e9a9d-2f8a-4ad2-be7d-4de02d19f2b1 · outbound

This paper cites Visualizing data using t-SNE.

Metric Learning for Adversarial Robustness Visualizing data using t-SNE

Reference 40

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Source-reported events for the cited work

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Observation 24e084a9-7602-4a2e-811b-9633062aaec4 · outbound

This paper cites Jaakkola, and Dina Katabi.

Metric Learning for Adversarial Robustness Jaakkola, and Dina Katabi

Reference 41

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Observation e86ec0e4-9a7d-41d3-8258-bfdbf85489d6 · outbound

This paper cites Deep metric learning with angular loss.

Metric Learning for Adversarial Robustness Deep metric learning with angular loss

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.523305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e6fd4abf-d353-47b9-8432-6e4c9a453db6 · outbound

This paper cites Formal Security Analysis of Neural Networks using Symbolic Intervals.

Metric Learning for Adversarial Robustness Formal Security Analysis of Neural Networks using Symbolic Intervals

Reference 43

Resolution: verified exact; local_arxiv, observed 2026-08-14T05:37:26.215344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 563b006d-d15a-4ef5-9cb0-1f1de80beaf6 · outbound

This paper cites Weinberger and Lawrence K.

Metric Learning for Adversarial Robustness Weinberger and Lawrence K

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.510955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7ba90c0b-8655-4c9e-b87b-1cdf78c94c7c · outbound

This paper cites Reinforcing adversarial robustness using model conﬁdence induced by adversarial training.

Metric Learning for Adversarial Robustness Reinforcing adversarial robustness using model conﬁdence induced by adversarial training

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.499964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 4d5516e9-272a-40e9-b32a-cf8048ff98b9 · outbound

This paper cites Feature Denoising for Improving Adversarial Robustness.

Metric Learning for Adversarial Robustness Feature Denoising for Improving Adversarial Robustness

Reference 46

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Observation bd051bd4-e4b6-4d4d-8ea1-14bde651ad50 · outbound

This paper cites Deep defense: Training dnns with improved adversarial robustness.

Metric Learning for Adversarial Robustness Deep defense: Training dnns with improved adversarial robustness

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.487131Z

Source-reported events for the cited work

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Observation f986fe15-3541-435b-8edd-21b1203718f9 · outbound

This paper cites Me-net: Towards effective adversarial robustness with matrix estimation.

Metric Learning for Adversarial Robustness Me-net: Towards effective adversarial robustness with matrix estimation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.475941Z

Source-reported events for the cited work

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Observation 12242d91-2692-4c75-84c3-cea459527962 · outbound

This paper cites Theoretically Principled Trade-off between Robustness and Accuracy.

Metric Learning for Adversarial Robustness Theoretically Principled Trade-off between Robustness and Accuracy

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-14T05:37:26.127547Z

Source-reported events for the cited work

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Observation a3f15054-3a26-40fb-bb98-ab8211700171 · outbound

This paper cites Goodfellow.

Metric Learning for Adversarial Robustness Goodfellow

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.465049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ede25908-2056-41cd-945c-6f28df47d6bb · outbound

This paper cites Hardness-Aware Deep Metric Learning.

Metric Learning for Adversarial Robustness Hardness-Aware Deep Metric Learning

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-08-14T05:37:26.178740Z

Source-reported events for the cited work

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Observation fd801964-4a66-44e1-b613-0a610cd1a8ba · outbound

This paper cites Metric Learning for Adversarial Robustness.

Metric Learning for Adversarial Robustness Metric Learning for Adversarial Robustness

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.453676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d72d8276-1b27-415d-a1f3-77f3609d0a83 · outbound

This paper cites We set up the experiment we reported in the table with the following hyper-parameters.

Metric Learning for Adversarial Robustness We set up the experiment we reported in the table with the following hyper-parameters

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:37:26.440496Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation af272d09-9cf4-4d6b-aa14-5b844331838f · inbound

HEM: a margin-based loss for visual categorisation tasks cites this paper.

HEM: a margin-based loss for visual categorisation tasks Metric Learning for Adversarial Robustness

Reference 59

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Observation 608cbd3d-9c37-4d13-8e49-afb70fb396b4 · inbound

Margin-Adaptive Confidence Ranking for Reliable LLM Judgement cites this paper.

Margin-Adaptive Confidence Ranking for Reliable LLM Judgement Metric Learning for Adversarial Robustness

Reference 143

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:07:41.128479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.