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Paper Citation Record · LEDGER

DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2312.04730.

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

pith.paper-citation-record.v1
2312.04730 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:51:08.283547Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T23:57:17.070864Z

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 d4eab460-2271-4564-b278-007c8904bd2f · inbound

XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants cites this paper.

XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions

Reference 67

Resolution
verified exact
arxiv_id, observed 2026-05-22T23:57:17.074337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T23:55:14.887237Z digest=sha256:03c36fa962112022cd33a1198d5f56881aad6f68f7d35539a3a4c3a9e14b5b62

Observation 937e60db-bb68-4755-864e-e46940ef7d65 · inbound

Chain-of-Code Collapse: Reasoning Failures in LLMs via Adversarial Prompting in Code Generation cites this paper.

Chain-of-Code Collapse: Reasoning Failures in LLMs via Adversarial Prompting in Code Generation DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T05:51:08.283547Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:51:08.283547Z digest=sha256:af887a9ccb792deed05efdb6751c0a9ca501b133ee351edf359620bb64247733

Observation 9c1d2248-9164-4014-a77f-3ee2127b9e30 · 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? DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-06T14:17:34.165989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:17:34.165989Z digest=sha256:ce3a225f0c889b3ac521f7f1de6b4d65c375bd81ced234138abf299d0a2256a2

Observation cbc77a68-d9ca-4d9d-a33d-29c36136f676 · inbound

When Prompts Go Wrong: Evaluating Code Model Robustness to Ambiguous, Contradictory, and Incomplete Task Descriptions cites this paper.

When Prompts Go Wrong: Evaluating Code Model Robustness to Ambiguous, Contradictory, and Incomplete Task Descriptions DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T13:38:53.175435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:38:53.175435Z digest=sha256:824a299a852d779afa765847aa46235660164a163d527def31f6c59c97f5c6d0

Observation 74c7822b-14eb-404c-b1ed-50d1f6456530 · inbound

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

RedCoder: Automated Multi-Turn Red Teaming for Code LLMs DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T23:00:44.825846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:00:44.825846Z digest=sha256:3dfaa95c374094245b3ed87e05dfface5b1cbe4e796aaa4ffe5a140c6ac120f6

Observation edadc5a6-04e6-4541-8790-ec8afb6e8bf6 · inbound

A First Look at the Security Issues in the Model Context Protocol Ecosystem cites this paper.

A First Look at the Security Issues in the Model Context Protocol Ecosystem DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-05-18T06:12:26.265767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T06:10:58.928119Z digest=sha256:1c1eb178706a530ac153ae93deaa1a663e6cf378c8885081ad653d184678fbf3

Observation ad624bf0-2d03-4299-b408-e64053beb4b3 · inbound

Fragile Thoughts: How Large Language Models Handle Chain-of-Thought Perturbations cites this paper.

Fragile Thoughts: How Large Language Models Handle Chain-of-Thought Perturbations DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-16T03:47:15.299667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T03:43:18.987241Z digest=sha256:9a8a9c3f46f1c9314c14ff59d02ae94592162d029e604329c997edeaa048699e

Observation 7bed2130-f027-49f9-ab0d-c1d6e23eae1f · inbound

IssueTrojanBench: Benchmarking AI Coding Agents Against Malicious Issue Requests cites this paper.

IssueTrojanBench: Benchmarking AI Coding Agents Against Malicious Issue Requests DeceptPrompt: Exploiting LLM-driven Code Generation via Adversarial Natural Language Instructions

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-01T09:30:49.040148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T09:30:49.040148Z digest=sha256:123507446b0af4162fa0c44ba94cfa567644e42fd9cc9b8f1c587d698a055398