Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Exploiting the Vulnerability of Large Language Models via Defense-Aware Architectural Backdoor
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2409.01952.
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 2026-08-09T00:50:00.190369Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T06:32:27.438778Z
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 e1c18849-4f35-4f9d-a784-a13df1db80f0 · 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 Exploiting the Vulnerability of Large Language Models via Defense-Aware Architectural Backdoor
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T00:50:00.190369Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1b001968-0fd9-4685-b9f9-222e0f62c27f · inbound
Architectural Backdoors in Deep Learning: A Survey of Vulnerabilities, Detection, and Defense cites this paper.
Architectural Backdoors in Deep Learning: A Survey of Vulnerabilities, Detection, and Defense Exploiting the Vulnerability of Large Language Models via Defense-Aware Architectural Backdoor
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:39:19.954644Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1263514-38f9-4def-b6f3-2fbdb9d52d02 · inbound
BadSNN: Backdoor Attacks on Spiking Neural Networks via Adversarial Spiking Neuron cites this paper.
BadSNN: Backdoor Attacks on Spiking Neural Networks via Adversarial Spiking Neuron Exploiting the Vulnerability of Large Language Models via Defense-Aware Architectural Backdoor
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T06:32:27.440720Z
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.