Paper Citation Record · LEDGER

Effective Prompt Extraction from Language Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2307.06865.

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

pith.paper-citation-record.v1
2307.06865 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T10:29:50.030145Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T02:09:22.506605Z

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 4db456cc-9efe-49f5-a210-6165cfae99fd · inbound

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

The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions Effective Prompt Extraction from Language Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:59:30.805076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fe3e80c8-957a-4412-8773-ea7dc1347c39 · inbound

Large Language Model Adversarial Landscape Through the Lens of Attack Objectives cites this paper.

Large Language Model Adversarial Landscape Through the Lens of Attack Objectives Effective Prompt Extraction from Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:50.030145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 726465f1-fea4-48ee-aa54-e9212ed584aa · inbound

A Critical Evaluation of Defenses against Prompt Injection Attacks cites this paper.

A Critical Evaluation of Defenses against Prompt Injection Attacks Effective Prompt Extraction from Language Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T14:36:12.778478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 781d88b3-dd71-4560-9cef-d771f702c936 · inbound

System Prompt Extraction Attacks and Defenses in Large Language Models cites this paper.

System Prompt Extraction Attacks and Defenses in Large Language Models Effective Prompt Extraction from Language Models

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T13:28:19.348303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3dad23e-9e63-4c18-91ce-83eb66e6beb1 · inbound

Privacy and Security Threat for OpenAI GPTs cites this paper.

Privacy and Security Threat for OpenAI GPTs Effective Prompt Extraction from Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T10:54:53.607765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56c55de3-6bd7-488f-9404-b8f277e4f2f1 · inbound

Federated In-Context Learning: Iterative Refinement for Improved Answer Quality cites this paper.

Federated In-Context Learning: Iterative Refinement for Improved Answer Quality Effective Prompt Extraction from Language Models

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-07T05:42:38.779335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c396fbc-a2e3-4865-937a-7b29a1f4bee4 · inbound

Securing AI Systems: A Guide to Known Attacks and Impacts cites this paper.

Securing AI Systems: A Guide to Known Attacks and Impacts Effective Prompt Extraction from Language Models

Reference 102

Resolution: unresolved; no resolver link, observed 2026-08-06T21:50:30.639123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37b968f7-a4bb-4b4a-b8ab-a89b36422804 · inbound

Many-Tier Instruction Hierarchy in LLM Agents cites this paper.

Many-Tier Instruction Hierarchy in LLM Agents Effective Prompt Extraction from Language Models

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:16:01.772646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e6eb5e7c-4031-4342-9e42-e72258efb3d9 · inbound

Measuring Real-World Prompt Injection Attacks in LLM-based Resume Screening cites this paper.

Measuring Real-World Prompt Injection Attacks in LLM-based Resume Screening Effective Prompt Extraction from Language Models

Reference 49

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T11:23:21.336479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9bcd56b2-be73-4510-a139-d55e28d555e6 · inbound

RogueMerge: Robust and Unified Attacks against LLM Model Merging cites this paper.

RogueMerge: Robust and Unified Attacks against LLM Model Merging Effective Prompt Extraction from Language Models

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-02T03:26:28.971990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d9cc16ba-6afd-4338-9490-5bb763ea5a77 · inbound

Understanding and Mitigating Prompt Leaking Attacks in Real-World LLM-Based Applications cites this paper.

Understanding and Mitigating Prompt Leaking Attacks in Real-World LLM-Based Applications Effective Prompt Extraction from Language Models

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:59:20.721166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 506729e8-1c85-4b38-b5f1-45d4fa7531fa · inbound

A Layered Security Framework Against Prompt Injection in RAG-Based Chatbots cites this paper.

A Layered Security Framework Against Prompt Injection in RAG-Based Chatbots Effective Prompt Extraction from Language Models

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-04T02:09:22.508194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e8475828-cbb4-4a10-93df-e90e0ecbd824 · inbound

Agent Data Injection Attacks are Realistic Threats to AI Agents cites this paper.

Agent Data Injection Attacks are Realistic Threats to AI Agents Effective Prompt Extraction from Language Models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-07-11T08:31:36.099368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.