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Paper Citation Record · LEDGER

Coercing LLMs to do and reveal (almost) anything

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2402.14020.

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

pith.paper-citation-record.v1
2402.14020 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 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 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:57:45.194846Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T21:27:24.512005Z

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 cd290381-df30-48d8-868b-117460a444ed · inbound

The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions cites this paper.

The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions Coercing LLMs to do and reveal (almost) anything

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:59:30.826587Z

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=2026-05-12T10:59:30.728091Z digest=sha256:ed02e3987c90017132429ef860dedacdd2f64460869d0bbb261d621c6d65e7b4

Observation 12ec3800-2704-4bd4-a5a2-56b77f154a14 · inbound

AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents cites this paper.

AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents Coercing LLMs to do and reveal (almost) anything

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:35:13.433785Z

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=2026-05-13T06:35:13.331872Z digest=sha256:8e20797de161197ad98125cbb1d0dd347c443fbb51c1ee65efc94f1398d1b152

Observation 0bc3445d-7ec7-4429-964c-af6cfaf3befd · inbound

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

Jailbreak Attacks and Defenses Against Large Language Models: A Survey Coercing LLMs to do and reveal (almost) anything

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:20:44.635844Z

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=2026-05-15T02:20:44.368219Z digest=sha256:3e98b2803fead426a39cb1a43f38f053f78259718b9cac24cde5974be9af08e2

Observation 57b01058-6c8b-42c8-9043-01a0ba6bcd20 · inbound

Has My System Prompt Been Used? Large Language Model Prompt Membership Inference cites this paper.

Has My System Prompt Been Used? Large Language Model Prompt Membership Inference Coercing LLMs to do and reveal (almost) anything

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T19:57:45.194846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T19:57:45.194846Z digest=sha256:16d6824f52a5b25c7fd52cce0deae0f1463ee0433ab5ea4b2345f8dbc77add57

Observation 92948dc0-135c-4145-8b20-f772f0df3aee · inbound

How much do language models memorize? cites this paper.

How much do language models memorize? Coercing LLMs to do and reveal (almost) anything

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:38.140735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:38.140735Z digest=sha256:40a4d41fcd3f12a2e399e40ab024a539450a084a66430d415ca742d0710f0b5a

Observation 09349338-0f64-4061-acc9-94f085aad380 · inbound

LingoLoop Attack: Trapping MLLMs via Linguistic Context and State Entrapment into Endless Loops cites this paper.

LingoLoop Attack: Trapping MLLMs via Linguistic Context and State Entrapment into Endless Loops Coercing LLMs to do and reveal (almost) anything

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-19T09:22:16.163991Z

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=2026-05-19T09:18:26.804728Z digest=sha256:49358820a9d35d2791dcae69707438d06c606f2559a70124c80a233df09fdcc9

Observation bca3bd7a-4616-4ea7-b834-2a00be8cf647 · inbound

FLEXITOKENS: Flexible Tokenization for Evolving Language Models cites this paper.

FLEXITOKENS: Flexible Tokenization for Evolving Language Models Coercing LLMs to do and reveal (almost) anything

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-19T05:12:05.171780Z

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=2026-05-19T05:10:19.093601Z digest=sha256:614a1d3c2d8eaccd0e3e4c48f3bab3c3e2512df482a4bd49827469cb771ba35d

Observation cce640ef-1e5a-40f6-8868-169d6e4f26dd · inbound

Train It and Forget It: Merge Lists are Unnecessary for BPE Inference in Language Models cites this paper.

Train It and Forget It: Merge Lists are Unnecessary for BPE Inference in Language Models Coercing LLMs to do and reveal (almost) anything

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-05T22:43:22.242905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T22:43:22.242905Z digest=sha256:ff76d823ecd731ae4aa6354f66dd2735cea2aae2bd84fca95bfa22dedd6efb33

Observation a4c1acff-d1c7-4c9a-8f25-cb5f0c6c7363 · 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 Coercing LLMs to do and reveal (almost) anything

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-04T09:25:40.590605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:25:40.590605Z digest=sha256:a79cc099337c6491d372950b18ee371cbf68c541ec009bad58360cefa2384a37

Observation 79aef304-9d93-4235-ae5f-604d7b8bcbe0 · inbound

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts cites this paper.

Cram Less to Fit More: Training Data Pruning Improves Memorization of Facts Coercing LLMs to do and reveal (almost) anything

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:15:59.157070Z

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=2026-05-10T17:42:31.465077Z digest=sha256:b8eab2e9d52301b75ec7c3587b8c5f04728e34828acee53a90acae951c0031f7

Observation 28274681-124a-4cd6-90b5-0873dad029a5 · inbound

Attention Is Where You Attack cites this paper.

Attention Is Where You Attack Coercing LLMs to do and reveal (almost) anything

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:31:05.088730Z

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=2026-05-09T19:54:41.445447Z digest=sha256:9ac1a24febfa960d991477cc516667f9db2c2ba690e55cf875c23945ed01771b

Observation b0305075-457a-4fc8-bb2c-8f2b48a0aa0a · inbound

On the Hardness of Junking LLMs cites this paper.

On the Hardness of Junking LLMs Coercing LLMs to do and reveal (almost) anything

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:21:10.172661Z

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=2026-05-08T17:38:32.028947Z digest=sha256:1f410dceade27653658f06bdf9f7c5867941f8dcf9e59061528adbf034ba92f0

Observation e6d6199e-a474-4b31-a99b-b733d08f4d04 · inbound

POISE: Position-Aware Undetectable Skill Injection on LLM Agents cites this paper.

POISE: Position-Aware Undetectable Skill Injection on LLM Agents Coercing LLMs to do and reveal (almost) anything

Reference 47

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T21:17:24.414483Z

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=2026-06-27T19:52:23.006490Z digest=sha256:708923f05ff69a25e9fac36af6d7c9162389c156291874695de24c45771027b4

Observation ec6e5f5a-22ba-4800-820b-189843765a97 · inbound

RecurGuard: Runtime Monitoring for Reasoning-Token Consumption Attacks cites this paper.

RecurGuard: Runtime Monitoring for Reasoning-Token Consumption Attacks Coercing LLMs to do and reveal (almost) anything

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-07-02T21:27:24.513488Z

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=2026-06-27T19:45:30.671490Z digest=sha256:4a20e908e99c606104528b0b7f5234cb26ca5d6e7e29f125bfccdf75d33b2640