Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Causality Analysis for Evaluating the Security of Large Language Models
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2312.07876.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T22:11:59.943595Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T10:21:04.472964Z
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 8a48cb0e-d279-4f54-b9c8-6f606ad9b48d · inbound
Layer-Level Self-Exposure and Patch: Affirmative Token Mitigation for Jailbreak Attack Defense cites this paper.
Layer-Level Self-Exposure and Patch: Affirmative Token Mitigation for Jailbreak Attack Defense Causality Analysis for Evaluating the Security of Large Language Models
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T22:11:59.943595Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 558f03a0-041d-4686-93bf-ee59e4c36982 · inbound
JBShield: Defending Large Language Models from Jailbreak Attacks through Activated Concept Analysis and Manipulation cites this paper.
JBShield: Defending Large Language Models from Jailbreak Attacks through Activated Concept Analysis and Manipulation Causality Analysis for Evaluating the Security of Large Language Models
Reference 61
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T12:25:30.721491Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8479be04-14a8-45ea-9259-4f873e25a8dc · inbound
Why Do Large Language Models Generate Harmful Content? cites this paper.
Why Do Large Language Models Generate Harmful Content? Causality Analysis for Evaluating the Security of Large Language Models
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T10:21:04.475898Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.