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Paper Citation Record · LEDGER

Towards Adversarially Robust Deep Metric Learning

As of 12 August 2026, this Paper Citation Record lists 61 of 61 outbound references and 0 inbound Pith citation observations for arXiv:2501.01025.

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

pith.paper-citation-record.v1
2501.01025 v2

Coverage vector

measured 61 of 61 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:40:29.663537Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

61 of 61 outbound references displayed

  • verified exact5
  • verified fuzzy6
  • unresolved50
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1541da85-4963-441b-b284-76a4aa251080 · outbound

This paper cites , " * write output.state after.block = add.period write newline.

Towards Adversarially Robust Deep Metric Learning , " * write output.state after.block = add.period write newline

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 28e7f455-2deb-42a3-8a61-dcd80c2315b3 · outbound

This paper cites write newline.

Towards Adversarially Robust Deep Metric Learning write newline

Reference 2

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Observation 2fd72dea-1919-437a-bd62-35b180727ab9 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 5e9fc3c0-0b51-4861-aa8b-857fff075d76 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 4

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Observation 0f6e4866-d39b-48c6-9ed0-8e28069b29a2 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 5

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Observation d71c7438-3117-4108-b130-dc2d80c05dc4 · outbound

This paper cites a ckinger, E.; and Shah, R. 1994. Signature verification using a.

Towards Adversarially Robust Deep Metric Learning a ckinger, E.; and Shah, R. 1994. Signature verification using a

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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

This paper cites Towards Evaluating the Robustness of Neural Networks.

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

Reference 7

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Observation 0a03b1b1-9e2f-4cf5-bdc4-49a704d79181 · outbound

This paper cites ALMN: Deep Embedding Learning with Geometrical Virtual Point Generating.

Towards Adversarially Robust Deep Metric Learning ALMN: Deep Embedding Learning with Geometrical Virtual Point Generating

Reference 8

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Observation 377422fc-3b7a-4db3-9496-427b8fbe0506 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 9

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 0a1b5368-d14e-4a0f-a385-6b61c7216ed5 · outbound

This paper cites an unresolved cited work.

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Reference 10

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Observation f9397f5c-053f-496b-bd80-094bd9819365 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 11

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Observation 68e318b9-15fe-487e-a595-bb652d97eaf4 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 12

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 26e6ec54-c8ab-44db-9d7d-71fef4607efa · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 13

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 6d54eeeb-2ab3-43d0-9576-c75c071de139 · outbound

This paper cites K.; Harandi, M.; and Sekhar, C.

Towards Adversarially Robust Deep Metric Learning K.; Harandi, M.; and Sekhar, C

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 14f25629-6e18-402f-9dc2-4de87b436089 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Towards Adversarially Robust Deep Metric Learning Explaining and Harnessing Adversarial Examples

Reference 15

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Observation 61372ba8-fa09-4816-ade7-78ada349a10d · outbound

This paper cites Countering Adversarial Images using Input Transformations.

Towards Adversarially Robust Deep Metric Learning Countering Adversarial Images using Input Transformations

Reference 16

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Observation b23272c3-554d-493e-a0e4-1fc2613579c6 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 17

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation e59a8126-f8ad-4e34-b771-5316e13dc24c · outbound

This paper cites an unresolved cited work.

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Reference 18

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Observation f105a21e-9c77-4c09-9ca6-1d4ee81201a2 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 19

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Observation 589a981f-5dfc-450a-ba85-f85714c50d4e · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 20

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Observation 384e16fd-7902-4789-9036-e5bf24918f7b · outbound

This paper cites an unresolved cited work.

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Reference 21

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Observation f626aad7-e19d-45a1-a7c9-cf58cdb94c84 · outbound

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Reference 22

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Observation d105c405-8264-4461-8ae5-406e27f5e617 · outbound

This paper cites Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift.

Towards Adversarially Robust Deep Metric Learning Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift

Reference 23

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Observation 2a6f25bf-84c6-4b61-96e8-be29ee71e280 · outbound

This paper cites Proxy Anchor Loss for Deep Metric Learning.

Towards Adversarially Robust Deep Metric Learning Proxy Anchor Loss for Deep Metric Learning

Reference 24

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Observation 4ff53de3-2338-4479-afc5-fe8d05b30026 · outbound

This paper cites an unresolved cited work.

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Reference 25

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 6ebcb7a4-5dbf-4c13-b74c-da7ed3f50644 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Towards Adversarially Robust Deep Metric Learning Adam: A Method for Stochastic Optimization

Reference 26

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Observation f8ac88cd-5b00-4c5a-938d-fb779fc5144b · outbound

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Reference 27

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 9c5d525d-ae53-40ef-aa56-721a531f494a · outbound

This paper cites Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Too Much Accuracy.

Towards Adversarially Robust Deep Metric Learning Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Too Much Accuracy

Reference 28

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 0acc8454-5fc5-4eea-81bf-d90335a8518b · outbound

This paper cites an unresolved cited work.

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Reference 29

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Observation 7577219d-9d78-4051-9d3c-2b3e59b8a372 · outbound

This paper cites an unresolved cited work.

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Reference 30

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation e56bbeed-a80a-4cea-91d3-6caa1baea664 · outbound

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Towards Adversarially Robust Deep Metric Learning Decoupled Weight Decay Regularization

Reference 31

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Observation c420cfdb-d08f-4b71-8283-45b2f06627b5 · outbound

This paper cites an unresolved cited work.

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Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 15ae086d-f269-40d8-ab63-75f4ae80cc26 · outbound

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

Towards Adversarially Robust Deep Metric Learning Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 33

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Unavailable: canonical work link unavailable.

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Observation 0e2b311a-7e0a-44d1-9bb2-169141ca8b67 · outbound

This paper cites K.; Ioffe, S.; and Singh, S.

Towards Adversarially Robust Deep Metric Learning K.; Ioffe, S.; and Singh, S

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation e88f565f-be4c-45f1-8f5c-aaf04858c119 · outbound

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Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 1c265ab4-ce27-4222-90fe-e20edb7b0eac · outbound

This paper cites Improving Adversarial Robustness via Promoting Ensemble Diversity.

Towards Adversarially Robust Deep Metric Learning Improving Adversarial Robustness via Promoting Ensemble Diversity

Reference 36

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation a6f4bca5-9319-4a94-976d-cbc564fdd265 · outbound

This paper cites Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks.

Towards Adversarially Robust Deep Metric Learning Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks

Reference 37

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 6f541f0e-9002-4916-be9a-02551f7ff008 · outbound

This paper cites Exploring Adversarial Robustness of Deep Metric Learning.

Towards Adversarially Robust Deep Metric Learning Exploring Adversarial Robustness of Deep Metric Learning

Reference 38

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no resolver link, observed 2026-08-10T22:40:29.416088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:40:29.416088Z digest=sha256:eb00ec33cffebc77f3a5ad6fb0076f15442592c1cf17b46abc9b4380a8cf2a58

Observation 9f837c5e-840c-45c7-909e-e24220f39f1b · outbound

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

Towards Adversarially Robust Deep Metric Learning The Limitations of Deep Learning in Adversarial Settings

Reference 39

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source=arxiv_source observed=2026-08-10T22:40:29.424926Z digest=sha256:d46d58bee9be35fe2bfb2309eaaa5a3336e740861bc642201568dd8cac36df48

Observation 38a09bc9-eb9e-4160-a544-f64f2b86e0f1 · outbound

This paper cites M.; Vedaldi, A.; and Zisserman, A.

Towards Adversarially Robust Deep Metric Learning M.; Vedaldi, A.; and Zisserman, A

Reference 40

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raw_fallback, observed 2026-08-10T22:40:30.621040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.432088Z digest=sha256:e173216091b5202f391f604b8cfe9b26cfe341ab60621ed4e6d60b8a05b205fb

Observation 557a0970-fac5-4072-97a7-0e8bffe54bc8 · outbound

This paper cites G.; Stra z ar, M.; and Zupan, B.

Towards Adversarially Robust Deep Metric Learning G.; Stra z ar, M.; and Zupan, B

Reference 41

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raw_fallback, observed 2026-08-10T22:40:30.603722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.445160Z digest=sha256:06d7fdc7fff1996d30cec05be297d4cef6d99409fd978b0795dfcd5337418adf

Observation 11525a49-fdcf-4b1a-ab75-7cd756ea0208 · outbound

This paper cites SoftTriple Loss: Deep Metric Learning Without Triplet Sampling.

Towards Adversarially Robust Deep Metric Learning SoftTriple Loss: Deep Metric Learning Without Triplet Sampling

Reference 42

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verified exact
local_arxiv, observed 2026-08-10T22:40:29.974365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.458088Z digest=sha256:ef36d2c88388eeeab0610ef55d9c2f67a6e6ad3716ae1f9d9bc615ae80a6353e

Observation 55dad838-f1b7-4d05-9944-0cf9cff683ea · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 43

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.467072Z digest=sha256:7efa87091f8ae86ebf0aaad23221d49de3d932360162bf654f1cfd9f138406fb

Observation f90c8d2a-c288-43ac-aef0-8081595ec21f · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 44

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raw_fallback, observed 2026-08-10T22:40:30.563113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 458b40ec-3ab3-427e-947b-a7c4a053ddf5 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 45

Resolution
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raw_fallback, observed 2026-08-10T22:40:30.534407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.480107Z digest=sha256:54818165f97cf03e19e321a597603cbe0c6e15b7db473a3b26e4b64b48c85392

Observation a2dcd0d3-1449-43f1-ae22-459e938ff642 · outbound

This paper cites Revisiting Training Strategies and Generalization Performance in Deep Metric Learning.

Towards Adversarially Robust Deep Metric Learning Revisiting Training Strategies and Generalization Performance in Deep Metric Learning

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-08-10T22:40:29.929726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.485326Z digest=sha256:7b020987deb0c7148071be0596c350de60650c603b6c792b4f787f265b6dd01b

Observation 865e11e2-458d-4a7f-82d0-0659da00db45 · outbound

This paper cites MobileNetV2: Inverted Residuals and Linear Bottlenecks.

Towards Adversarially Robust Deep Metric Learning MobileNetV2: Inverted Residuals and Linear Bottlenecks

Reference 47

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no resolver link, observed 2026-08-10T22:40:29.491828Z

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source=arxiv_source observed=2026-08-10T22:40:29.491828Z digest=sha256:85d82b76f2881980768b8d2aeb7c1a693d5251eb1fd0a2d50cfce5bbbbfe4b46

Observation a560055e-b367-4c73-805d-cdf4596fbd7c · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 48

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raw_fallback, observed 2026-08-10T22:40:30.513693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.505115Z digest=sha256:2894443bfaf0403d15cdf12958b36bff7473a58b11e9e249e0726e6cfdc35b15

Observation 50407477-d77d-431a-a58d-35c73b20daa6 · outbound

This paper cites Constrained Deep Metric Learning for Person Re-identification.

Towards Adversarially Robust Deep Metric Learning Constrained Deep Metric Learning for Person Re-identification

Reference 49

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no resolver link, observed 2026-08-10T22:40:29.518363Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-10T22:40:29.518363Z digest=sha256:0a8819f561590d00c82a73b453c069eb99981d7d9927c838c8eab08f7edd4873

Observation 1c3e1ae9-15b8-4e58-9efe-69bbd60823c9 · outbound

This paper cites H.; and Hospedales, T.

Towards Adversarially Robust Deep Metric Learning H.; and Hospedales, T

Reference 50

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source=arxiv_source observed=2026-08-10T22:40:29.526253Z digest=sha256:2f747ac396649d07a4fbb86fd32ffa2463992aa3fa9a1c990887c6d2f7eeac91

Observation 2455ac8c-393c-4e86-bc0a-737b9f97500c · outbound

This paper cites Intriguing properties of neural networks.

Towards Adversarially Robust Deep Metric Learning Intriguing properties of neural networks

Reference 51

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source=arxiv_source observed=2026-08-10T22:40:29.531728Z digest=sha256:9207acdfb5630cf5ef30298a45095bdeed72b9980d17f3b7c3f5b3802e1a670a

Observation a1ef10fc-c714-4141-88be-bcf05fb85485 · outbound

This paper cites Manifold Mixup: Better Representations by Interpolating Hidden States.

Towards Adversarially Robust Deep Metric Learning Manifold Mixup: Better Representations by Interpolating Hidden States

Reference 52

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source=arxiv_source observed=2026-08-10T22:40:29.548393Z digest=sha256:abebf9c47b1f430f3ca03fb853adef525c7adfa174944c12f08f348b44b584b9

Observation 642fbb2f-5754-4ad2-bf7a-092355433ad2 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 53

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unresolved
raw_fallback, observed 2026-08-10T22:40:30.485694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.570550Z digest=sha256:c0b565678121645fd5a6bab22c1facba035d9a515a93dd23ac3ee92d1af2665a

Observation 2de4012a-49ae-4416-9753-5bee6c51eae2 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 54

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unresolved
raw_fallback, observed 2026-08-10T22:40:30.464600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.587834Z digest=sha256:a9f6c03d5f402c0858877daf8da9ba3f9480d42871b9506d8bdf662359c5bb46

Observation baaab654-88f3-4a92-8379-c85f3e53f5a8 · outbound

This paper cites T.; and Ni, L.

Towards Adversarially Robust Deep Metric Learning T.; and Ni, L

Reference 55

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verified fuzzy
raw_fallback, observed 2026-08-10T22:40:30.445116Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.602465Z digest=sha256:cbe473a9867a8c71847fb680788962a42e24b35410caa7678c4fd142a8cb7208

Observation b374c175-db23-47c6-a474-8858b0d40c67 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 56

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raw_fallback, observed 2026-08-10T22:40:30.423187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.609470Z digest=sha256:29b8bf21d01a6141f151de1872cc1ada111dabc66ba567a5eca36966d8d907c6

Observation 91289af8-fd55-4df9-88a4-c0de65a5a664 · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 57

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unresolved
raw_fallback, observed 2026-08-10T22:40:30.395179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.623836Z digest=sha256:5529ed36e61725e74bdc2bc450c265f51be269a141e297d750d8d601b947b19c

Observation 9c96d5f9-9772-4133-b5a4-38506386bc4f · outbound

This paper cites an unresolved cited work.

Towards Adversarially Robust Deep Metric Learning Unresolved cited work

Reference 58

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raw_fallback, observed 2026-08-10T22:40:30.360391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-10T22:40:29.634821Z digest=sha256:ccc681ea51608500cb933abb17cf5bf026fef359d41482ad6ce0ecaa87a48a3c

Observation 0acacf78-a73d-4946-a75b-e9c68f8b4b1c · outbound

This paper cites Mitigating Adversarial Effects Through Randomization.

Towards Adversarially Robust Deep Metric Learning Mitigating Adversarial Effects Through Randomization

Reference 59

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no resolver link, observed 2026-08-10T22:40:29.642000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:40:29.642000Z digest=sha256:09dd5daf543ea5a7ec0e3cf5e35af0dac082a7639f8b10c4c60b4d6d10850e01

Observation de0eb9e4-d3da-44ef-beb1-ee3997b758c9 · outbound

This paper cites mixup: Beyond Empirical Risk Minimization.

Towards Adversarially Robust Deep Metric Learning mixup: Beyond Empirical Risk Minimization

Reference 60

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no resolver link, observed 2026-08-10T22:40:29.652228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:40:29.652228Z digest=sha256:f68fd83fcecfc026e7f29ed405f94b325dc2f36706203fd855833e3adf65c239

Observation a7c12fd3-88fd-4431-9b61-dfa4d9b0a00c · outbound

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

Towards Adversarially Robust Deep Metric Learning Theoretically Principled Trade-off between Robustness and Accuracy

Reference 61

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no resolver link, observed 2026-08-10T22:40:29.663537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:40:29.663537Z digest=sha256:c23561aa1f0a93447bd71a78fd06158149b036206ec45dbc73dabb300f45f728

Pith citing papers

No inbound Pith citation observations are available.