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Paper Citation Record · LEDGER

(Certified!!) Adversarial Robustness for Free!

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2206.10550.

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

pith.paper-citation-record.v1
2206.10550 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:05:47.704319Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T17:11:00.849680Z

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 88cf7be0-9393-4fd7-a0e1-ff6ef2627cdc · inbound

SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks cites this paper.

SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks (Certified!!) Adversarial Robustness for Free!

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-14T17:11:00.853655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T17:11:00.639293Z digest=sha256:57da4b9df2ccd6430a3687dcee7989ab7d02d0c6bf7c7ea33df7efb4fa74374e

Observation ef67f529-d726-42b8-b369-9095209760a9 · inbound

How Do Diffusion Models Improve Adversarial Robustness? cites this paper.

How Do Diffusion Models Improve Adversarial Robustness? (Certified!!) Adversarial Robustness for Free!

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T13:05:47.704319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:05:47.704319Z digest=sha256:26e520236aac93202ee9646d62c6237c6f20166ac3eee36c2a8c964af926ba62

Observation ced9d443-d030-4d80-9e68-cd6ad93b9790 · inbound

Robustifying Diffusion-Denoised Smoothing Against Covariate Shift cites this paper.

Robustifying Diffusion-Denoised Smoothing Against Covariate Shift (Certified!!) Adversarial Robustness for Free!

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-04T17:30:02.177309Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T17:30:02.177309Z digest=sha256:dc3f2a443b5ab7200d689c75f1eb87291a0a4d99954d6783a2f0a60b7cf00f7c