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Paper Citation Record · LEDGER

Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2311.09096.

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

pith.paper-citation-record.v1
2311.09096 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:46:40.713387Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T21:36:52.404748Z

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 e011b566-0d7c-43dd-bbdf-ed6e6ad276b1 · inbound

VLM-Guard: Safeguarding Vision-Language Models via Fulfilling Safety Alignment Gap cites this paper.

VLM-Guard: Safeguarding Vision-Language Models via Fulfilling Safety Alignment Gap Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T19:46:40.713387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T19:46:40.713387Z digest=sha256:9c239246a4784802f89b9682c3d50bb7845ba860fe4ff47725c85109c31ad94c

Observation 5e9e1492-e9a2-44d4-bf15-8c4e4266a8c3 · inbound

Towards an AI co-scientist cites this paper.

Towards an AI co-scientist Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:02:44.272813Z

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.

source=arxiv_source observed=2026-05-11T13:02:43.571234Z digest=sha256:a84f16667d2cdd877a4de7ac51af9ce57d215d2b592c7082f6b37849a05114d7

Observation d7d80884-9021-4501-b489-581405fd11f5 · inbound

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques cites this paper.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-06T16:24:29.495638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:24:29.495638Z digest=sha256:8fe9e20f5f19f9a414b97612ea487089b60a4030b52909f6e23304904b7bee5e

Observation c9d93443-48d4-44b2-a70e-26cad4fef8f2 · inbound

A Real-Time, Self-Tuning Moderator Framework for Adversarial Prompt Detection cites this paper.

A Real-Time, Self-Tuning Moderator Framework for Adversarial Prompt Detection Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T22:24:23.400378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:24:23.400378Z digest=sha256:d81d927ebbd2b55023e4bbd90ab07b7e34e0d5168f3777cc9950bca293e6d3cf

Observation 2b7a8093-461b-4ecc-ba4e-569bd2e286d8 · inbound

GUARD: Guideline Upholding Test through Adaptive Role-play and Jailbreak Diagnostics for LLMs cites this paper.

GUARD: Guideline Upholding Test through Adaptive Role-play and Jailbreak Diagnostics for LLMs Defending Large Language Models Against Jailbreaking Attacks Through Goal Prioritization

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-05-18T21:36:52.409545Z

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.

source=pdf_text observed=2026-05-18T21:34:51.665401Z digest=sha256:3d05d683bd69d336ce80f9a5735c5a453b91183127380f4ff7fc8fd1ee211c36