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Paper Citation Record · LEDGER

DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 29 inbound Pith citation observations for arXiv:2402.16914.

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

pith.paper-citation-record.v1
2402.16914 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 29 of 29 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:22:02.318012Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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  • unresolved0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 69f8b7c4-46ed-478b-915b-d3aa6d6d92af · inbound

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

Jailbreak Attacks and Defenses Against Large Language Models: A Survey DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 51

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T02:20:44.730853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-15T02:20:44.368219Z digest=sha256:8a225724ebe57b2d660940116695854d7a10dfe87dcad0cd8f6c3735dfd0df88

Observation 3fbafe84-8082-47b3-8d47-fd9ef341edcd · inbound

Preventing Jailbreak Prompts as Malicious Tools for Cybercriminals: A Cyber Defense Perspective cites this paper.

Preventing Jailbreak Prompts as Malicious Tools for Cybercriminals: A Cyber Defense Perspective DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 17

Resolution
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no resolver link, observed 2026-08-12T12:56:34.353697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:56:34.353697Z digest=sha256:267cd13c245d27f1be851968e7d5a760667f9a63a462e1be5b0f1711661d3024

Observation 65ff9f53-2e30-4241-8a56-2919a4e1854e · inbound

Prompt-based Unifying Inference Attack on Graph Neural Networks cites this paper.

Prompt-based Unifying Inference Attack on Graph Neural Networks DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 22

Resolution
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no resolver link, observed 2026-08-11T11:12:06.443384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T11:12:06.443384Z digest=sha256:9400d9f6fdd59ac95c359067f1a64c64149de173717ba9446871466a99c64afb

Observation 27dfe993-1704-4c34-b01a-3ff8c08294e1 · inbound

On the Validity of Traditional Vulnerability Scoring Systems for Adversarial Attacks against LLMs cites this paper.

On the Validity of Traditional Vulnerability Scoring Systems for Adversarial Attacks against LLMs DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-10T23:40:18.890566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T23:40:18.890566Z digest=sha256:1e0435782344a6ea60f7a56eec0530d9270e7c9b6b242373b8a9650f460d8381

Observation 0c83e0ae-e84b-4d66-aa77-d32bf75a8b52 · 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 DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 16

Resolution
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no resolver link, observed 2026-08-09T04:22:00.481354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T04:22:00.481354Z digest=sha256:57c254e69990288eb828ab9790d2791d90eb657eb3b124cc69ea4e742d70dde5

Observation 22cabf06-0865-4a26-b598-885d7c8a2b06 · 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 DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-08T12:25:30.613261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T12:25:30.613261Z digest=sha256:58eac2325812d4f6f0ecddd334003e8082fcf9a2f986ea701e6f76796430c493

Observation 58197cf4-a898-48e8-a7ed-4b90456f2831 · inbound

Jailbreaking to Jailbreak cites this paper.

Jailbreaking to Jailbreak DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-08T17:02:47.346647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:02:47.346647Z digest=sha256:0a63827760b482515e5eaa7a1e3a985277889a0c17befb8fc635dabeee406131

Observation 325eef15-5183-4a9c-bb2d-cea0fd84d919 · inbound

Insights from Verification: Training a Verilog Generation LLM with Reinforcement Learning with Testbench Feedback cites this paper.

Insights from Verification: Training a Verilog Generation LLM with Reinforcement Learning with Testbench Feedback DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-16T11:22:02.318012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:22:02.318012Z digest=sha256:d3e573543e0ee14c38f222352af840ef5c0be94f221e6a2b008e75db3c64878b

Observation be1b1c36-5fe8-4511-bd4c-667aa5f72602 · inbound

NeuRel-Attack: Neuron Relearning for Safety Disalignment in Large Language Models cites this paper.

NeuRel-Attack: Neuron Relearning for Safety Disalignment in Large Language Models DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-16T05:33:11.803668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T05:33:11.803668Z digest=sha256:f6421c8c6aa0b6d4e2cfac3ec0145e5a3c46d3b9679d78d60471eebccc50c38f

Observation 9ed957d2-2887-409b-bdcb-8842dc65627e · inbound

One Model Transfer to All: On Robust Jailbreak Prompts Generation against LLMs cites this paper.

One Model Transfer to All: On Robust Jailbreak Prompts Generation against LLMs DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T14:48:16.908261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:48:16.908261Z digest=sha256:234634ab6a0104e7a4bde7b86cb5d4fa45fc517c4f8f435b02b55e2781840304

Observation bdcec99b-775e-4fe4-8083-8ac83e1925fc · inbound

From Hallucinations to Jailbreaks: Rethinking the Vulnerability of Large Foundation Models cites this paper.

From Hallucinations to Jailbreaks: Rethinking the Vulnerability of Large Foundation Models DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 23

Resolution
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no resolver link, observed 2026-08-07T12:34:35.024627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:34:35.024627Z digest=sha256:27c2cd49e15f94cfb27e718ebe02a39655c0f46c5f25303beae3121ba6459092

Observation 6111a5ee-8cf9-4dd6-95c9-dd4bd41c45f8 · inbound

Benchmarking Misuse Mitigation Against Covert Adversaries cites this paper.

Benchmarking Misuse Mitigation Against Covert Adversaries DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 20

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T10:32:14.751197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-19T10:29:05.104520Z digest=sha256:4a4dbb97c5af6693ef7823c5619e291a25a5baa2abdffe753a436bc94ee59c0a

Observation 65c9f057-029c-4115-b33d-15030852ea12 · inbound

InfoFlood: Jailbreaking Large Language Models with Information Overload cites this paper.

InfoFlood: Jailbreaking Large Language Models with Information Overload DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T01:02:29.162442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T01:02:29.162442Z digest=sha256:769d4ddd39b102ac6b7acfb31acfb05c40f9330498909f4a81f8373281e9d7ee

Observation 63ff88c9-2fe1-477a-bfc4-a26e7a7ff2b1 · inbound

Beyond Surface-Level Detection: Towards Cognitive-Driven Defense Against Jailbreak Attacks via Meta-Operations Reasoning cites this paper.

Beyond Surface-Level Detection: Towards Cognitive-Driven Defense Against Jailbreak Attacks via Meta-Operations Reasoning DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 163

Resolution
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no resolver link, observed 2026-08-06T04:47:25.566053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T04:47:25.566053Z digest=sha256:bda31024f74144eb670666a0f855529e0da3dea1d79db0904ed4a92e85c6981b

Observation 794a4aee-da99-493c-bdb2-f259682c4ea4 · inbound

Towards terahertz nanomechanics cites this paper.

Towards terahertz nanomechanics DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 17

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no resolver link, observed 2026-08-06T01:03:50.785477Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T01:03:50.785477Z digest=sha256:7c61a6dbc2b0b51989aebe6dc5feb28dd5413579be417ee1fd7108120c6c86c9

Observation f7dd2d6d-07a6-4e11-bcc4-66ccb503affb · inbound

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

ASTRA: Autonomous Spatial-Temporal Red-teaming for AI Software Assistants DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T01:04:34.437507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T01:04:34.437507Z digest=sha256:3bb13ee4d878f8318700cb50700787eba2478fb722e59e8c576d40ebe86a06db

Observation 79ee3035-118a-407b-8085-916f7b3b6269 · inbound

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

Layer-Wise Perturbations via Sparse Autoencoders for Adversarial Text Generation DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-05T20:31:40.480555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:31:40.480555Z digest=sha256:8c8e701f0cfb94792eed88e08a66bc2f832daef6908bb933b10eeb9ff904ee50

Observation 5c51fca5-3ace-4ed8-aead-76b29948150c · 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 DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-18T21:36:52.445155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-18T21:34:51.665401Z digest=sha256:9b94f1a62849096509344a7a5abbe33c70177a52a70e1c97eb4adcf0218c1333

Observation 05f5aa85-235d-4b43-83a1-80be2b3a3484 · 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 DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 103

Resolution
unresolved
no resolver link, observed 2026-08-04T09:25:46.386991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:25:46.386991Z digest=sha256:5048c93df0b6285bde957cdf828fcbf8318d8bf1d6936f5fc6e91d802cec227d

Observation 1358916c-c128-4aaa-952c-d057c3118ff8 · 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 DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:55:38.022340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-18T01:54:22.995178Z digest=sha256:041332bbe7555177dd78ec70c0a16b445a213c9392411667b0c8c26dac9121e9

Observation 2fdb3514-3a79-4c03-adeb-e4f553ad2c83 · inbound

SelfGrader: LLM Jailbreak Detection via Anchored Token-Level Logits cites this paper.

SelfGrader: LLM Jailbreak Detection via Anchored Token-Level Logits DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 14

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verified exact
arxiv_id, observed 2026-05-13T21:48:19.357903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-13T21:43:46.728512Z digest=sha256:caec75078b614cb53fa6916ab25154e9534608eb9bab1377159a68bda51f7dbf

Observation 56618874-883d-450c-bca1-d6ab31f4e38e · inbound

Jailbreaking the Matrix: Nullspace Steering for Controlled Model Subversion cites this paper.

Jailbreaking the Matrix: Nullspace Steering for Controlled Model Subversion DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 27

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arxiv_id, observed 2026-05-11T10:46:04.389761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-05-10T15:19:46.920899Z digest=sha256:cf13b52565ef35a0f4f1e479bc93b7032146815279ac9552c04c3496725bc7f5

Observation 7f80f370-27fb-45cd-a195-dcbfab3574cb · inbound

Babel: Jailbreaking Safety Attention via Obfuscation Distribution Optimized Sampling cites this paper.

Babel: Jailbreaking Safety Attention via Obfuscation Distribution Optimized Sampling DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 6

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arxiv_id, observed 2026-05-20T10:08:11.950847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-20T10:08:07.648295Z digest=sha256:21f6de7eefdc44fc09a2238a9a83c6e76aede72e0673be0845c0112ccf0601bd

Observation 804aa57b-651c-4ab0-9cf5-405387b1f017 · inbound

Adversarial Reframing: A Framework for Targeted Generation in Language Models cites this paper.

Adversarial Reframing: A Framework for Targeted Generation in Language Models DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 29

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verified exact
arxiv_id, observed 2026-05-22T09:36:21.023614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-22T09:35:51.862736Z digest=sha256:e014495e81abca0d51a6edcb6f5ea754375a3314473160bcf8f7a834b1526d2d

Observation c0c8629c-bc02-4d69-9b40-8917f8c631d9 · inbound

Stateful Online Monitoring Catches Distributed Agent Attacks cites this paper.

Stateful Online Monitoring Catches Distributed Agent Attacks DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 19

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metadata mismatch
arxiv_id, observed 2026-06-28T22:02:41.101220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-06-28T21:54:44.072929Z digest=sha256:d630c25431042bb78647cf0f8187de6ab1d2695c51ea38f671fbec4e730532ee

Observation 36b603ad-917a-4335-93e8-65593a4459bf · inbound

Defending Jailbreak Attacks on Large Language Models via Manifold Trajectory Kinetics cites this paper.

Defending Jailbreak Attacks on Large Language Models via Manifold Trajectory Kinetics DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 35

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arxiv_id, observed 2026-07-02T17:37:14.898011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-27T21:55:48.561400Z digest=sha256:1dbd4243818f697b83b7df1c55c57f65482654077c1fab46feedc697652936e2

Observation 70d33fdf-3407-4a96-9b21-f4d32dec0fea · inbound

AMT-X: Phase-Structured Multi-Turn Red-Teaming with Checklist-Gated Evaluation cites this paper.

AMT-X: Phase-Structured Multi-Turn Red-Teaming with Checklist-Gated Evaluation DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 17

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no resolver link, observed 2026-07-14T06:40:17.865408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T06:40:17.865408Z digest=sha256:d3d2be108ccf9bd29809757420569339944f7a76f39ba7fa7b11aea005ece3ac

Observation 1f1fa684-7095-42ea-8e95-324843271df6 · inbound

When Local Monitors Miss Compositional Harm: Diagnosing Distributed Backdoors in Multi-Agent Systems cites this paper.

When Local Monitors Miss Compositional Harm: Diagnosing Distributed Backdoors in Multi-Agent Systems DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 67

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no resolver link, observed 2026-07-14T03:26:15.676915Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T03:26:15.676915Z digest=sha256:4fe37cfaf623b8cc76caedc9c4a2b0010a7296776f85d2fc035b1eab84fcd76c

Observation 1e9e90e8-0057-4eb7-8723-13533a0dad87 · inbound

Reason Before You Retrieve: Agentic Planning for Multi-modal RAG cites this paper.

Reason Before You Retrieve: Agentic Planning for Multi-modal RAG DrAttack: Prompt Decomposition and Reconstruction Makes Powerful LLM Jailbreakers

Reference 113

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no resolver link, observed 2026-08-02T10:20:56.084051Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T10:20:56.084051Z digest=sha256:43d6a116dacce77c15b3eb87d309b9509700612248143c3b7777837798950021