Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
What Doesn't Kill You Makes You Robust(er): How to Adversarially Train against Data Poisoning
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2102.13624.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T00:50:00.740246Z
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 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 2026-08-09T06:31:02.800959+00:00.