Paper Citation Record · LEDGER

Prompt Packer: Deceiving LLMs through Compositional Instruction with Hidden Attacks

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2310.10077.

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

pith.paper-citation-record.v1
2310.10077 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T13:11:27.260452Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T12:14:38.998402Z

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 5b9b63b7-3f9e-4f73-9d10-ea95c06d4068 · inbound

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods cites this paper.

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods Prompt Packer: Deceiving LLMs through Compositional Instruction with Hidden Attacks

Reference 104

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:08:36.866732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation caf971d1-5ca7-4911-aba2-6ddc5ee77a8d · inbound

Lightweight Safety Classification Using Pruned Language Models cites this paper.

Lightweight Safety Classification Using Pruned Language Models Prompt Packer: Deceiving LLMs through Compositional Instruction with Hidden Attacks

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T13:11:27.260452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cacf353-321e-4d36-9d25-b7196a6890ef · 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 Prompt Packer: Deceiving LLMs through Compositional Instruction with Hidden Attacks

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T12:25:30.594472Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe2cd443-3b7e-4d0c-9503-2cb97d75e89d · inbound

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems cites this paper.

LLM in the Middle: A Systematic Review of Threats and Mitigations to Real-World LLM-based Systems Prompt Packer: Deceiving LLMs through Compositional Instruction with Hidden Attacks

Reference 146

Resolution: unresolved; no resolver link, observed 2026-08-04T17:46:19.368728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2da7b82c-53f1-4821-8fa7-cb39e8c4402e · inbound

Large Language Model Selection with Limited Annotations cites this paper.

Large Language Model Selection with Limited Annotations Prompt Packer: Deceiving LLMs through Compositional Instruction with Hidden Attacks

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-06-30T12:14:38.999951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fe51e06e-10b0-4e4d-9a84-ada7ed86d0fe · inbound

When AI Meets Wall Street: A Survey on Trustworthy AI in Fintech cites this paper.

When AI Meets Wall Street: A Survey on Trustworthy AI in Fintech Prompt Packer: Deceiving LLMs through Compositional Instruction with Hidden Attacks

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-06-29T14:43:31.592525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.