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Paper Citation Record · LEDGER

RED: Robust Environmental Design

As of 17 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 2026-08-16T06:30:59.297886+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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.857047Z digest=sha256:129d3bd5457d95ad02064b77376d43d094e84a546331a6b8a158c11ded351cb4

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=sha256:91dbc29117d54e0f89913d0264597893a2e53cbf87a69cba2ea5438161702ead

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.864622Z digest=sha256:6a2b4baf5ca789374fdf5b09c09f976d6dc142151cf5f1dc74f0252fa415ba56

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.868104Z digest=sha256:5686598fbb44f87f83d82a9f8b09ce1bbcb3dc12297ac8bd30ba3acd51ff176e

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.872145Z digest=sha256:fc453a25f9f4d041a78acf1466daea8c052269cb742a95b0f1867531e0467ea3

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.875339Z digest=sha256:e744c3805f6988d270c0a2e32c6478d47dd9ff1b4991cb56b0d32d4471fd1555

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.878648Z digest=sha256:5c5ef02f3c6226aa517687fe7780ee628b592294058cd2a26d0aa1f6e492fc9c

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=sha256:047b4a4ebda376bd6112af84a5398a68cf2a06da18f766041be35beed9772804

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=sha256:271c3fca1fca2aab52f5c917b412a3f5c0c78d34a4ef557c613d68dd0da73b4e

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.888872Z digest=sha256:35c9336e965eb4d4e0c66aa1404ea018b819d54239dd1f7dcb6ca3a51b734b31

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=sha256:7fba803311366febdce67ef3625010ad361d7ace353d2fd159cc142430d02643

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.897717Z digest=sha256:7ed68e51e2a140775f8052ad1439b959419788b5d986b54dddcee2aeb3cae595

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.900520Z digest=sha256:de1fab71e6a74f3a7dc2164c68590cf57d14e9d1e5488217eda2874a29cbc58b

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.903254Z digest=sha256:2c5663b9ca9ec7cd76f2d6d6962bd8d9ecc9c0f3872142dbb028870ebd3fb172

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.905907Z digest=sha256:87cd63bac187f25d3a365b2cfc39ba3cc5ff1e98ee3fcf77d6b00124bb36bd40

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.908618Z digest=sha256:17321e33232cc5fc3d0f82e26641c20660864187631a3b1c4c628009f4afb354

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=sha256:0a0b4abf16aa40d3e8fb85e36e07c045ee3e4c36cd4598f784ea437df694f9c4

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.914273Z digest=sha256:be2094ffd186ac61193be36576113f563c140d5799df5c8a0a12959329221246

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.917489Z digest=sha256:f07c276843e7a8594a3cb199fa2e71dca66fa7399e07aa34ad058085d53dd2b2

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 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T12:40:28.920086Z digest=sha256:0f41835131ada68433289c7998eee66bb5edfef5680ac043ba36e5b73f7a57da

Pith citing papers

No inbound Pith citation observations are available.