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Paper Citation Record · LEDGER

RED: Robust Environmental Design

As of 21 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2411.17026.

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

pith.paper-citation-record.v1
2411.17026 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:40:28.920086Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

20 of 20 outbound references displayed

  • verified exact1
  • verified fuzzy14
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a2cdeb92-c383-4171-9252-49e52da11c62 · outbound

This paper cites Explaining and harnessing adversarial examples.

RED: Robust Environmental Design Explaining and harnessing adversarial examples

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.109520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.857047Z digest=sha256:edd4b6aab78b574df51726256d3c6b6e7a53de62cb8a467051c63cd9a47c01bf

Observation a41a7387-e6c4-473d-9256-845c606e12b3 · outbound

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

RED: Robust Environmental Design Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-12T12:40:28.860668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:40:28.860668Z digest=sha256:8b6289ef26c9168c0b9f2b23a8d533bb27ef8e17d7d5e41101d8878986beaeac

Observation 0531eb9d-87a9-41da-a279-1f48f3199a31 · outbound

This paper cites Adversarial examples in the physical world.

RED: Robust Environmental Design Adversarial examples in the physical world

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.101401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.864622Z digest=sha256:a21cf9ebd615c123060917cdd3ca51871ded4a410c685ee6c53228a2afceafbf

Observation 939136ba-8f8a-42c4-85d4-632bf2bc4100 · outbound

This paper cites Unadversarial examples: Designing objects for robust vision.

RED: Robust Environmental Design Unadversarial examples: Designing objects for robust vision

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.093472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.868104Z digest=sha256:e49a188350620a04a008b7fc8eb8ee3e1ca36e0adcf1e3be20bad788255a76ff

Observation 87a14b90-f789-44aa-9c50-6c9be3b26f92 · outbound

This paper cites Robust physical-world attacks on deep learning visual classification.

RED: Robust Environmental Design Robust physical-world attacks on deep learning visual classification

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.085648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.872145Z digest=sha256:e6f3a6681860cab88c360ea711ac6f69522e6d651e38e378318ba09e0a171337

Observation cb4d6dc1-1e52-421c-856a-c8d761232d17 · outbound

This paper cites Patchattack: A black-box texture-based attack with reinforcement learning.

RED: Robust Environmental Design Patchattack: A black-box texture-based attack with reinforcement learning

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.076781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.875339Z digest=sha256:1bc23ea43a602128b855e22936b96ae6ccb52258f9c7d7fd2a57b5a29fc54c6b

Observation 6aa1df58-d0d0-4f7e-81a7-c3ade5a92aea · outbound

This paper cites Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples.

RED: Robust Environmental Design Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.068619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.878648Z digest=sha256:8b383c2f0b1750f859071e8265cc36dc4b03051beb90c3bd6750c7a3edeed54e

Observation 41263fdb-c070-4159-8b45-ce224da5ce97 · outbound

This paper cites Adversarial Patch.

RED: Robust Environmental Design Adversarial Patch

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-12T12:40:28.882015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:40:28.882015Z digest=sha256:6748e80756a0823e322cfb64fedba48b1acfe9b183c3061a4a943d8f353566d0

Observation 7196feb2-25f5-425f-991c-e4eca01eb498 · outbound

This paper cites Delving into Transferable Adversarial Examples and Black-box Attacks.

RED: Robust Environmental Design Delving into Transferable Adversarial Examples and Black-box Attacks

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T12:40:28.885695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:40:28.885695Z digest=sha256:e2aac9cfc751f2a3c48c0ac3e6621a7aca088af00db62dab60191a816a0ada68

Observation 23e19861-4cae-4c14-a795-18fb50a6fc8c · outbound

This paper cites LaVAN: Localized and Visible Adversarial Noise.

RED: Robust Environmental Design LaVAN: Localized and Visible Adversarial Noise

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-12T12:40:28.965144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.888872Z digest=sha256:4f8e03de5bfca1514673297d24ff885af4d1bb07365698989a073af8ccadac20

Observation cc32b585-e1b3-4b10-a778-79f2b6f95794 · outbound

This paper cites Search for muon-philic new light gauge boson at Belle II.

RED: Robust Environmental Design Search for muon-philic new light gauge boson at Belle II

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-12T12:40:28.894277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:40:28.894277Z digest=sha256:75c8bdb8158a4d49d2c01e5b6f9c689f03aa89f20011bdd3835ef50f2afad4ae

Observation b9641ad2-8e9e-4503-85ce-ff3340137537 · outbound

This paper cites Adversarial training for free! Advances in Neural Information Processing Systems (NeurIPS), 32, 2019.

RED: Robust Environmental Design Adversarial training for free! Advances in Neural Information Processing Systems (NeurIPS), 32, 2019

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.058977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.897717Z digest=sha256:e5f9028c01073811a8f2058e4e9dd212b44d4921621e6648e3d4c0ab5eabff8f

Observation 0ed5278d-4e73-4a9b-b23e-5e567bd052ef · outbound

This paper cites Certified adversarial robustness via randomized smoothing.

RED: Robust Environmental Design Certified adversarial robustness via randomized smoothing

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.050370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.900520Z digest=sha256:aaffffb7c5c47c666fab4bd46e8fcb3a8e2f212a7e620ec6947a1729a7f6bbea

Observation bb080c78-5689-41ea-9623-5329c2e3d8f2 · outbound

This paper cites Certified robustness to adversarial examples with differential privacy.

RED: Robust Environmental Design Certified robustness to adversarial examples with differential privacy

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.042030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.903254Z digest=sha256:4370c2dba04e1aee3ccec7576b8e0be4f56503386a093f53b8f2dbfd51205e70

Observation c32e05a4-54aa-4d0b-b53d-d0fdb983d1ff · outbound

This paper cites Provably robust deep learning via adversarially trained smoothed classifiers.

RED: Robust Environmental Design Provably robust deep learning via adversarially trained smoothed classifiers

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.033030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.905907Z digest=sha256:5775b79147b347f19fa236d55deebab6961d9000b2b28d829a87fdd7f49b25f5

Observation 8a6e7512-6134-4774-a59b-907c68b4ff1b · outbound

This paper cites Patchguard: A provably robust defense against adversarial patches via small receptive fields and masking.

RED: Robust Environmental Design Patchguard: A provably robust defense against adversarial patches via small receptive fields and masking

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.024494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.908618Z digest=sha256:1c8e3b0c143f65b9743240ee9a7d2f2f1c0def36fefed3d1caf93df943c9e7a6

Observation 58fd64f4-8b57-4a3d-b57a-666ccea3e1c1 · outbound

This paper cites Pushing the limits of raw waveform speaker recognition.

RED: Robust Environmental Design Pushing the limits of raw waveform speaker recognition

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-12T12:40:28.911288Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:40:28.911288Z digest=sha256:977eaf4a40eb66f8c89cc32e6b707d449c03b09c613803a786d7ebf65417d0fe

Observation 6371f224-1d78-412e-b4f5-6c4dda6225d0 · outbound

This paper cites Patchzero: Defending against adversarial patch attacks by detecting and zeroing the patch.

RED: Robust Environmental Design Patchzero: Defending against adversarial patch attacks by detecting and zeroing the patch

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.016156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.914273Z digest=sha256:4a41aad163eea2fafb47e2c9c872883799b7131c43c5b71b9f994b66d816592f

Observation 5b40cbb9-48df-4137-ba19-0fbe1483f3e2 · outbound

This paper cites Benson, Aleksander Mądry, Elan Rosenfeld, and Zico Kolter.

RED: Robust Environmental Design Benson, Aleksander Mądry, Elan Rosenfeld, and Zico Kolter

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:29.007716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.917489Z digest=sha256:8d87264f2d57df0da2902c45a3a5555fe5d2c595109da26b497d9ad1c9f04bb2

Observation b8797ae6-f805-4c99-895b-0a1d8836af60 · outbound

This paper cites (de) randomized smoothing for certifiable defense against patch attacks.

RED: Robust Environmental Design (de) randomized smoothing for certifiable defense against patch attacks

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T12:40:28.999089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.920086Z digest=sha256:b0e336091d940e2044e1f6319e051b2d3eb7922caa045c9f5f0c50d80726aced

Pith citing papers

No inbound Pith citation observations are available.