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Paper Citation Record · LEDGER

Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2402.18104.

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

pith.paper-citation-record.v1
2402.18104 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:34:05.971739Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T02:20:44.746080Z

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 cfa7e491-b079-4fc0-8d3f-dd8f6da43f78 · inbound

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

Jailbreak Attacks and Defenses Against Large Language Models: A Survey Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:20:44.749063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-15T02:20:44.368219Z digest=sha256:491172f8138ca47d51ae88446a03080845fd2aa9ccaadc491a6f239bba4abca9

Observation fd54ec90-da97-4263-bbf1-23b7d567b031 · inbound

Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents cites this paper.

Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction

Reference 167

Resolution
unresolved
no resolver link, observed 2026-08-12T20:36:02.100394Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:36:02.100394Z digest=sha256:8cf2e90e08dfbc9005a6090753729098d40dcc81829266c850baa887c526a10a

Observation 706d9c35-ea39-43a2-b58f-7d8b1680a4c4 · inbound

Model-Editing-Based Jailbreak against Safety-aligned Large Language Models cites this paper.

Model-Editing-Based Jailbreak against Safety-aligned Large Language Models Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-11T18:11:05.993725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:11:05.993725Z digest=sha256:c01324931bf00f6e559bcf8d44bb68e0169e8d92d5bc250c39ba147e1756c0d5

Observation 0b1b1209-5caa-4588-a0ba-a542ca732beb · inbound

KDA: A Knowledge-Distilled Attacker for Generating Diverse Prompts to Jailbreak LLMs cites this paper.

KDA: A Knowledge-Distilled Attacker for Generating Diverse Prompts to Jailbreak LLMs Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-09T04:22:00.505854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T04:22:00.505854Z digest=sha256:65f99c647b41c449208e6683aeb105c2ee998984ebf2306a7399145ded37fce1

Observation e20d42c4-07c8-4bfb-9e08-55bd51ca902f · inbound

Jailbreak Detection in Clinical Training LLMs Using Feature-Based Predictive Models cites this paper.

Jailbreak Detection in Clinical Training LLMs Using Feature-Based Predictive Models Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-16T11:34:05.971739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:34:05.971739Z digest=sha256:8cd93880a5a541f7c40910260c4aa11a7f33c8b244b0099168c29a98002ff0c2

Observation 86072d83-b4f7-4e73-ae34-bf490e2b7dc0 · inbound

SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation cites this paper.

SoK: The Privacy Paradox of Large Language Models: Advancements, Privacy Risks, and Mitigation Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-07T00:46:10.197111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:46:10.197111Z digest=sha256:0848be723dedb7531e9f07db07feeb5c969d28f5211c99ad819056c93703ecd6

Observation baa84667-355f-4ecc-a18b-25861e850d3b · inbound

MOCHA: Are Code Language Models Robust Against Multi-Turn Malicious Coding Prompts? cites this paper.

MOCHA: Are Code Language Models Robust Against Multi-Turn Malicious Coding Prompts? Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T14:17:34.069998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:17:34.069998Z digest=sha256:d1a3ee2550f701ffc59f55eee1e23143aa50dfed40fc522dfc595c64cd477b76

Observation 14348ef6-23eb-4fc7-95c7-32497fdfcd76 · inbound

Layer-Wise Perturbations via Sparse Autoencoders for Adversarial Text Generation cites this paper.

Layer-Wise Perturbations via Sparse Autoencoders for Adversarial Text Generation Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-05T20:31:40.561131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:31:40.561131Z digest=sha256:2616cfdcb952513bb188f2ce79e1c8182d7898722355043117fac2b5b0b8dcb2

Observation 85e85fed-f946-4490-8a21-e8e5b09fb212 · inbound

Behind the Mask: Benchmarking Camouflaged Jailbreaks in Large Language Models cites this paper.

Behind the Mask: Benchmarking Camouflaged Jailbreaks in Large Language Models Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T05:29:20.697468Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T05:29:20.697468Z digest=sha256:151e0ddfb2dcf4afa3ea07e837040a9a1335b0bf9ee105a14b37d502c83aa9f7

Observation 7d03a866-8998-4115-942f-ca7cbea3c008 · inbound

AntiDote: Bi-level Adversarial Training for Tamper-Resistant LLMs cites this paper.

AntiDote: Bi-level Adversarial Training for Tamper-Resistant LLMs Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-15T16:25:35.786739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T16:25:35.786739Z digest=sha256:b5239d803c81d1296c3b20c862d98d9b035d2ad9082ff7f5f3b7ef43eda84297