Paper Citation Record · LEDGER

Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2402.15180.

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

pith.paper-citation-record.v1
2402.15180 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:02:43.211841Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T10:57:16.524772Z

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 2fe70c4b-f7fc-4c78-8891-8845a5691583 · inbound

Jailbreak Attacks and Defenses Against Large Language Models: A Survey cites this paper.

Jailbreak Attacks and Defenses Against Large Language Models: A Survey Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:20:44.697101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b8eb9045-ce00-42b4-8d31-5e0cb97648ca · inbound

Revisiting Multi-Agent Debate as Test-Time Scaling: A Systematic Study of Conditional Effectiveness cites this paper.

Revisiting Multi-Agent Debate as Test-Time Scaling: A Systematic Study of Conditional Effectiveness Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T13:02:43.211841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bc3f7c1-24e2-4613-a87f-ad6c7de19e8b · inbound

Enhancing the Safety of Medical Vision-Language Models by Synthetic Demonstrations cites this paper.

Enhancing the Safety of Medical Vision-Language Models by Synthetic Demonstrations Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-19T10:57:16.527088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b88c5562-03a5-4f26-a6b7-0a5c1f784bd3 · inbound

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security cites this paper.

Secure Tug-of-War (SecTOW): Iterative Defense-Attack Training with Reinforcement Learning for Multimodal Model Security Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T12:09:39.696496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59b80ef8-a9d3-4ade-9607-bfd534c63dad · inbound

SoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses cites this paper.

SoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-04T09:25:44.871354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d22ec0c-7b69-40dc-8aee-72a222d00e69 · inbound

A Systematic Study of Training-Free Methods for Trustworthy Large Language Models cites this paper.

A Systematic Study of Training-Free Methods for Trustworthy Large Language Models Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:22:37.372133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 628cf611-9da9-4043-82fc-74f79ec7db3a · inbound

LoopTrap: Termination Poisoning Attacks on LLM Agents cites this paper.

LoopTrap: Termination Poisoning Attacks on LLM Agents Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:21:10.547786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e027582c-d013-4221-9c20-6890a882666f · inbound

SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text cites this paper.

SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T13:36:54.864997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.