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Paper Citation Record · LEDGER

Robustness, Privacy, and Generalization of Adversarial Training

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2012.13573.

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

pith.paper-citation-record.v1
2012.13573 v1

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 2026-08-20T06:33:59.587034+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:45:34.210789Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T23:28:17.138479Z

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 df925e21-a384-4578-a1f6-623b493e2997 · inbound

Combining Machine Learning Defenses without Conflicts cites this paper.

Combining Machine Learning Defenses without Conflicts Robustness, Privacy, and Generalization of Adversarial Training

Reference 123

Resolution
unresolved
no resolver link, observed 2026-08-12T20:26:04.877289Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T20:26:04.877289Z digest=sha256:242cc6e3cecd60b51ded39b43da0066a55959239725cd71c0ac6bb1151d5b450

Observation 579ab869-79db-4238-b200-ce4bb8a178f7 · inbound

Learning from the Good Ones: Risk Profiling-Based Defenses Against Evasion Attacks on DNNs cites this paper.

Learning from the Good Ones: Risk Profiling-Based Defenses Against Evasion Attacks on DNNs Robustness, Privacy, and Generalization of Adversarial Training

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-15T22:45:34.210789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:45:34.210789Z digest=sha256:46a510eccca1a897e1c36fbbdc6769af344fe76d73e3779590b65c1fb3fff52d

Observation 627f9d01-9b2d-4684-a5bc-324276836ab4 · inbound

ROAST: Risk-aware Outlier-exposure for Adversarial Selective Training of Anomaly Detectors Against Evasion Attacks cites this paper.

ROAST: Risk-aware Outlier-exposure for Adversarial Selective Training of Anomaly Detectors Against Evasion Attacks Robustness, Privacy, and Generalization of Adversarial Training

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-14T23:28:17.141930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-14T23:24:12.883229Z digest=sha256:350030f05944799aa039dcdb1fd55a3913857900996bba850b0267af87765229