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Paper Citation Record · LEDGER

Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2403.03792.

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

pith.paper-citation-record.v1
2403.03792 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 2026-08-21T06:32:19.484+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:38:39.445465Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T06:17:41.932219Z

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 c79b8249-09cf-4b2b-b2aa-d2490ca9d575 · 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 Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-13T06:35:13.490917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-13T06:35:13.331872Z digest=sha256:81fb4d733f52a0b12e1763a9591f9de4fe9b33579754e88a6d2aa722a3c577d0

Observation c8ebc6a3-9899-4fe2-a37f-29e2aa065586 · inbound

Trustworthiness in Retrieval-Augmented Generation Systems: A Survey cites this paper.

Trustworthiness in Retrieval-Augmented Generation Systems: A Survey Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Reference 81

Resolution
verified exact
arxiv_id, observed 2026-05-23T21:08:25.793746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-23T21:08:11.787013Z digest=sha256:8a8e9cb93ed97e9317bcf0fa536239a240e284fc2ac062ef9f6e2458cb2636eb

Observation 933761b1-e20d-4097-9755-dcd55dc6ad8e · 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 Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Reference 202

Resolution
unresolved
no resolver link, observed 2026-08-12T20:36:02.276204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T20:36:02.276204Z digest=sha256:6ea8571d33774b54ab089065182b6f94106c2aee1789b3306f7e1e7cba2f2521

Observation 27a7fa14-653a-47e3-aebd-1be0f2c28992 · inbound

Fun-tuning: Characterizing the Vulnerability of Proprietary LLMs to Optimization-based Prompt Injection Attacks via the Fine-Tuning Interface cites this paper.

Fun-tuning: Characterizing the Vulnerability of Proprietary LLMs to Optimization-based Prompt Injection Attacks via the Fine-Tuning Interface Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-10T19:44:46.798448Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:44:46.798448Z digest=sha256:f159b2d4ed5d7846d4d4ad5728346b7b43c21baf555a1b866792f5580565b8b9

Observation 6eec70c6-d9d9-4528-b7ec-176ac6786d63 · inbound

ACE: A Security Architecture for LLM-Integrated App Systems cites this paper.

ACE: A Security Architecture for LLM-Integrated App Systems Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-22T18:06:54.283250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-22T18:05:50.363944Z digest=sha256:d1fc128ad0d37bf8d9cb912e88a5963acfd10f79bb007c472b6762a95b60d470

Observation f6b4a58d-65c1-493d-958c-8d4c6907811e · inbound

OET: Optimization-based prompt injection Evaluation Toolkit cites this paper.

OET: Optimization-based prompt injection Evaluation Toolkit Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-16T04:38:39.445465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:38:39.445465Z digest=sha256:b8d150c8b5f9c9f261ce351c1110d91f8e8618c900d13b2e65be553ff4b75a73

Observation c6fa50bd-3b22-4322-b72c-ce82f7a1333f · inbound

Security Concerns for Large Language Models: A Survey cites this paper.

Security Concerns for Large Language Models: A Survey Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T14:27:03.612380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:27:03.612380Z digest=sha256:c458ab6b0fd14e565eb42fbd20acc880c9b3f3da9a3b81d1bb60c96472d019fb

Observation dbc0bacd-8c3f-4cba-a325-a0d8f8378f07 · inbound

Evaluation of Prompt Injection Defenses in Large Language Models cites this paper.

Evaluation of Prompt Injection Defenses in Large Language Models Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:21:12.084417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-08T05:50:20.608166Z digest=sha256:941e5b6e6ccb9a4549d265cff2f6f1187758094e7950db289bf9d70a109e0820

Observation ac41caa6-ad5a-4e55-96bc-c81b4b2ceda0 · inbound

Evaluation of Prompt Injection Defenses in Large Language Models cites this paper.

Evaluation of Prompt Injection Defenses in Large Language Models Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-14T21:19:28.492228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-14T21:05:23.800356Z digest=sha256:e0be13ec638de1d172fdda28562422ca2591c40e2301382d1407cbae33c0443a

Observation 64bd7d9f-4c8d-4548-8f2e-014e775cf0b1 · inbound

Assessing Automated Prompt Injection Attacks in Agentic Environments cites this paper.

Assessing Automated Prompt Injection Attacks in Agentic Environments Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-07-03T06:17:41.936259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-27T12:47:09.467463Z digest=sha256:604320dba5118faffd56f10b062ba087ab6b1b2d5c7f6ebd2c28ace8f9243b4a

Observation 3c4625b0-ef24-4a83-aa75-9f0957dfb8b8 · inbound

Beyond Handcrafted Security: Towards Self-Evolving Defense for LLM Agents cites this paper.

Beyond Handcrafted Security: Towards Self-Evolving Defense for LLM Agents Neural Exec: Learning (and Learning from) Execution Triggers for Prompt Injection Attacks

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-15T19:23:24.310635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:23:24.310635Z digest=sha256:edf80d317dc01ffda2eb8c64247cd3e65f4dd74d593232defb2b5b691a3accec