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Paper Citation Record · LEDGER

Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2003.01690.

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

pith.paper-citation-record.v1
2003.01690 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:30:21.286102Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

436
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 94c1bce4-f1b1-4293-ab35-5d2d95fd3129 · inbound

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

HEM: a margin-based loss for visual categorisation tasks Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-10T17:30:21.286102Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:30:21.286102Z digest=sha256:e276f8b7f0625a24ad9e5e7d6dd68edad41b8cca2f9f338b7c72eedd34efda6d

Observation 2c851804-4247-479b-8407-5900e1c61080 · inbound

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

Adversarial Examples Are Not Bugs, They Are Superposition Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-05T16:56:07.971877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T16:56:07.971877Z digest=sha256:7523217c8d13f5411a7575d9ea05a8bb1ab305fdcc7e2f2cc28484413749d507

Observation c672313d-f70b-48da-99cc-72b1794fda10 · inbound

NeuroTrace: Inference Provenance-Based Detection of Adversarial Examples cites this paper.

NeuroTrace: Inference Provenance-Based Detection of Adversarial Examples Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:51:02.043694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-10T12:30:35.538954Z digest=sha256:93d62476ca0723d8c4882af39cf80f0e7e36fa88941a02a5c797415abf594f72

Observation eccb6f1e-ebde-433e-af15-8b560b1c79f3 · inbound

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

Auto-ART: Structured Literature Synthesis and Automated Adversarial Robustness Testing Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:39:48.178264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-10T00:39:43.196010Z digest=sha256:f5f5f7dd1853ace29b6a9b509fba30acb1f00848798b222bc84fdb8d20c80d8e

Observation 8a5b8252-0bad-4ede-88da-4d85e7608ec6 · inbound

SORA: Free Second-Order Attacks in Fast Adversarial Training cites this paper.

SORA: Free Second-Order Attacks in Fast Adversarial Training Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

Reference 13

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T19:12:35.086523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-06-28T19:05:06.136594Z digest=sha256:d0f821ffe46ad27711d032f9be198f5a1f9eacacd776ecb96cda169191ed89c5

Observation abe10585-b5d0-4c84-b673-8daa8209ea1d · inbound

A combination of noise and bilateral filters achieve supralinear and scalable adversarial robustness in CNNs cites this paper.

A combination of noise and bilateral filters achieve supralinear and scalable adversarial robustness in CNNs Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-01T22:26:17.806860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-06-28T15:23:26.461740Z digest=sha256:e713a44e941ef537eeac840dba497c0a13993097905e80b2ef5b4cd6258e4bce

Observation 51d3bd4e-d395-40d1-a859-c1eb5d5d6a7d · inbound

Toward Calibrated, Fair, and accurate Deepfake Detection cites this paper.

Toward Calibrated, Fair, and accurate Deepfake Detection Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-06-28T07:11:45.169761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=arxiv_source observed=2026-06-28T07:05:18.026601Z digest=sha256:87e1b83fa35e0b9e4ea1ae8eeb17b93964b855b3ab324cf4dfac676d6c859fb6

Observation de3c4701-412d-4acb-8dd5-e3329bb092c8 · inbound

Securing Multimodal AI through Internal Information Decomposition cites this paper.

Securing Multimodal AI through Internal Information Decomposition Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-02T15:02:58.558426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T15:02:58.558426Z digest=sha256:a4d5e31edb42a911cc54592ef0ea94447ce936b9cb5e4540fb8c24258055c611