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Paper Citation Record · LEDGER

Certified Defenses against Adversarial Examples

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:1801.09344.

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

pith.paper-citation-record.v1
1801.09344 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:18:14.510095Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T16:23:39.422776Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation fe46f21d-0950-445d-a84b-d1e8e2c6de7e · inbound

Unsupervised dense retrieval with conterfactual contrastive learning cites this paper.

Unsupervised dense retrieval with conterfactual contrastive learning Certified Defenses against Adversarial Examples

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-10T23:18:14.510095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:18:14.510095Z digest=sha256:9a018d9a3f4df6af58d466eb41abde193c4c0ac4bff7f7389c1ee1da7c43f499

Observation 8379c6bc-44fe-45e9-bf26-bcd75a1b450b · inbound

Enhancing Adversarial Transferability via Component-Wise Transformation cites this paper.

Enhancing Adversarial Transferability via Component-Wise Transformation Certified Defenses against Adversarial Examples

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T17:51:49.825243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:51:49.825243Z digest=sha256:4a7e9d43e83283990ceadbb28cc81bde83f69e21b3cc38058999a024e7d9bedf

Observation c1eaec99-b880-4a1a-90f3-f45257c613b3 · inbound

Robust Representation Consistency Model via Contrastive Denoising cites this paper.

Robust Representation Consistency Model via Contrastive Denoising Certified Defenses against Adversarial Examples

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-10T16:32:20.794786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:32:20.794786Z digest=sha256:ffdc70f898505b0bb492b507ba3fd796af8375460e6e29f389b20f282b81f0e2

Observation 656b2c06-b0ba-4098-99a5-fa504cd04b4f · inbound

TorchLean: Formalizing Neural Networks in Lean cites this paper.

TorchLean: Formalizing Neural Networks in Lean Certified Defenses against Adversarial Examples

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-02T20:45:42.220213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T20:45:42.220213Z digest=sha256:5504199e821f9cd25c8046bb9f5dfe1e5b9858f325852b0e2e9e669d9e2c6cd3

Observation 63908227-aee4-4bed-a0a0-54e4b1eae2eb · inbound

Machine Learning Enhanced Laser Spectroscopy for Multi-Species Gas Detection in Complex and Harsh Environments cites this paper.

Machine Learning Enhanced Laser Spectroscopy for Multi-Species Gas Detection in Complex and Harsh Environments Certified Defenses against Adversarial Examples

Reference 198

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:11:10.307060Z

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=pdf_text observed=2026-05-09T18:33:03.300592Z digest=sha256:e97f1721c32b1defb3f0b21b7f461cbd9e973d3f40f6de1b569077af192fbbe0

Observation ed90e3c9-77d0-43a8-97be-14e4390c8e60 · inbound

A New Framework to Analyse the Distributional Robustness of Deep Neural Networks cites this paper.

A New Framework to Analyse the Distributional Robustness of Deep Neural Networks Certified Defenses against Adversarial Examples

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:53:59.204308Z

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=pdf_text observed=2026-05-21T05:51:22.877865Z digest=sha256:02ef47ecd145b231f3ed2767eab0ad6bd73e66975fdbb953ce1136c657cb3dd5

Observation f6724ee7-185f-41ee-8d25-374b9efd57c6 · inbound

Bridging Control with Neural Network Verifier alpha-beta-CROWN: A Tutorial cites this paper.

Bridging Control with Neural Network Verifier alpha-beta-CROWN: A Tutorial Certified Defenses against Adversarial Examples

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-06-29T16:23:39.424150Z

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=pdf_text observed=2026-06-29T16:19:18.692686Z digest=sha256:2fc4c4f9a421ed3395bc365775100c145eb3039dac37937081a37c9e1dada1a3