Paper Citation Record · LEDGER

Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2104.09425.

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

pith.paper-citation-record.v1
2104.09425 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T18:28:36.182405Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T21:18:59.597420Z

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 a1571c3f-9840-48cd-9fee-3f484376880a · inbound

Limited Reference, Reliable Generation: A Two-Component Framework for Tabular Data Generation in Low-Data Regimes cites this paper.

Limited Reference, Reliable Generation: A Two-Component Framework for Tabular Data Generation in Low-Data Regimes Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-04T18:28:36.182405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ae307d8-e640-43d7-a5ee-552632d005e8 · inbound

Sample-wise Adaptive Weighting for Transfer Consistency in Adversarial Distillation cites this paper.

Sample-wise Adaptive Weighting for Transfer Consistency in Adversarial Distillation Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-16T23:53:43.063273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2c097312-f756-4f75-9f68-495785ee139e · inbound

A Prototypical Signature Approach for Writer-Independent Offline Signature Verification cites this paper.

A Prototypical Signature Approach for Writer-Independent Offline Signature Verification Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?

Reference 296

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T21:18:59.599098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b3e4c437-9187-400f-abc8-4f71cec9ebf6 · inbound

Adversarial Frontiers: Minimum-Norm Attack Ensembles for Robustness Evaluation cites this paper.

Adversarial Frontiers: Minimum-Norm Attack Ensembles for Robustness Evaluation Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness?

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-01T11:41:31.621683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.