Paper Citation Record · LEDGER

What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2102.13624.

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

pith.paper-citation-record.v1
2102.13624 v2

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 2026-08-22T06:32:14.747728+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:44:11.688722Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T15:19:15.088323Z

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 841fd956-828e-46fa-b1b0-5814941a8fe0 · inbound

A Survey of Secure Semantic Communications cites this paper.

A Survey of Secure Semantic Communications What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning

Reference 134

Resolution: unresolved; no resolver link, observed 2026-08-10T22:44:11.688722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2012aa3-842b-4989-8d78-03b17c34d015 · inbound

A Survey on Backdoor Threats in Large Language Models (LLMs): Attacks, Defenses, and Evaluations cites this paper.

A Survey on Backdoor Threats in Large Language Models (LLMs): Attacks, Defenses, and Evaluations What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning

Reference 191

Resolution: unresolved; no resolver link, observed 2026-08-09T00:50:00.740246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b5eb096-652d-4554-86ee-d7a2c2a0c70d · inbound

A Survey on Data Security in Large Language Models cites this paper.

A Survey on Data Security in Large Language Models What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T05:05:00.878117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3b7be44-4436-4272-9f97-cb2dcf8266ae · inbound

Pruning Strategies for Backdoor Defense in LLMs cites this paper.

Pruning Strategies for Backdoor Defense in LLMs What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-05T15:19:15.093705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.