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Paper Citation Record · LEDGER

RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2409.17458.

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

pith.paper-citation-record.v1
2409.17458 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:09:58.602890Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T19:00:30.428488Z

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 144e073f-4506-44e0-9c5e-f06ffb3a7060 · inbound

MTSA: Multi-turn Safety Alignment for LLMs through Multi-round Red-teaming cites this paper.

MTSA: Multi-turn Safety Alignment for LLMs through Multi-round Red-teaming RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T15:09:58.602890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:09:58.602890Z digest=sha256:64cd80c53eaee5190d2512c008ae7591797cdc681659c5a82b2a6b8da96b579c

Observation b251effc-877e-4481-8464-055748701496 · inbound

SafeWork-R1: Coevolving Safety and Intelligence under the AI-45$^{\circ}$ Law cites this paper.

SafeWork-R1: Coevolving Safety and Intelligence under the AI-45$^{\circ}$ Law RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T14:37:19.186707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:37:19.186707Z digest=sha256:e401f3abd0acd4572dc3e2dfb6c7d560defe4bd465bcbdab590794ce09736553

Observation 793aabd4-4600-4182-961d-6cb89978b446 · inbound

RedCoder: Automated Multi-Turn Red Teaming for Code LLMs cites this paper.

RedCoder: Automated Multi-Turn Red Teaming for Code LLMs RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T23:00:44.749219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:00:44.749219Z digest=sha256:e5ec8a9315bdc5f43c62ef7dc11774e48e78d9fe351d1364dbe1ab6ce77dcb53

Observation 02d28bb0-53a2-4aaf-b1ed-3ea0676b1b25 · inbound

Towards terahertz nanomechanics cites this paper.

Towards terahertz nanomechanics RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T01:03:50.595772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T01:03:50.595772Z digest=sha256:e0a2939d93d829100fd1f84d8f59c722b4ca32eac2953d22f88720b091bd22bf

Observation 04bedc4c-5f67-4f2b-a154-5e9ecf81bdc3 · inbound

ASTRA: Autonomous Spatial-Temporal Red-teaming for AI Software Assistants cites this paper.

ASTRA: Autonomous Spatial-Temporal Red-teaming for AI Software Assistants RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T01:04:34.171238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T01:04:34.171238Z digest=sha256:d35a9677386d0525528493b09f09b590e2d1a1755c468ebece41128f648dbda3

Observation 72cb0e55-3ef8-44af-b1be-3c2f0f1f0849 · 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 RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-04T09:25:43.834739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:25:43.834739Z digest=sha256:65836e223a6a379cbb1f03c6fc462d7480e23c6a0334b7395430eb04b16874fd

Observation 63e65d28-5242-49c3-a9ac-81feefe9d0bc · inbound

ASTRA: An Automated Framework for Strategy Discovery, Retrieval, and Evolution for Jailbreaking LLMs cites this paper.

ASTRA: An Automated Framework for Strategy Discovery, Retrieval, and Evolution for Jailbreaking LLMs RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:55:38.040599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T01:54:22.995178Z digest=sha256:7c057f602fb404fa804c5ddc0ae2bba1986b3f4de2a0108399421b41254cdee7

Observation 5b84a080-d06b-415f-9730-b4d369dbdc81 · inbound

Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs cites this paper.

Evolve the Method, Not the Prompts: Evolutionary Synthesis of Jailbreak Attacks on LLMs RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-21T19:00:30.430635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T18:58:53.183734Z digest=sha256:92af7df690144a2531669791e7590537cbef9bba6108a854b25a8a494b2dd42c

Observation 593cc320-5c2f-4b81-a19c-939356755c61 · inbound

SkillTrojan: Backdoor Attacks on Skill-Based Agent Systems cites this paper.

SkillTrojan: Backdoor Attacks on Skill-Based Agent Systems RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:31:01.996380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T17:36:19.694339Z digest=sha256:0a86beb961af23c9966fb0326026fffc17b6022fa953d80219ed83194b887739

Observation 2802c7a5-7496-43c9-8516-3cc02f1f917a · inbound

MultiBreak: A Scalable and Diverse Multi-turn Jailbreak Benchmark for Evaluating LLM Safety cites this paper.

MultiBreak: A Scalable and Diverse Multi-turn Jailbreak Benchmark for Evaluating LLM Safety RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T09:31:01.171116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-10T16:00:32.413225Z digest=sha256:cb47b58893d28d2d453072437d1e92325880c1969058af0b207c7787f50a0b5d

Observation b15ac3db-aece-42e1-aa4a-759eb576099d · inbound

Stateful Cooperative Agents Safeguarding LLMs Against Evolving Multi-Turn Attacks cites this paper.

Stateful Cooperative Agents Safeguarding LLMs Against Evolving Multi-Turn Attacks RED QUEEN: Safeguarding Large Language Models against Concealed Multi-Turn Jailbreaking

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-04T01:16:13.794829Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T01:16:13.794829Z digest=sha256:b026ba75b8506122a62affdac2c0fe2df75a8890ca07cd58fc73bcaed8f93dba