Paper Citation Record · LEDGER

Instructional Fingerprinting of Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2401.12255.

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

pith.paper-citation-record.v1
2401.12255 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 2026-08-07T06:34:17.273281+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:45:37.457976Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:56:28.016542Z

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 acd51f7f-cb9a-4a40-80f4-9b9d8ad5cf02 · inbound

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities cites this paper.

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities Instructional Fingerprinting of Large Language Models

Reference 261

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:16:04.787476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation dd9a6fae-2379-4d6a-b312-d5937adc116f · inbound

Gradient-Based Model Fingerprinting for LLM Similarity Detection and Family Classification cites this paper.

Gradient-Based Model Fingerprinting for LLM Similarity Detection and Family Classification Instructional Fingerprinting of Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T11:45:37.457976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4985b978-420f-4755-8b68-77b01ce290fc · inbound

MEraser: An Effective Fingerprint Erasure Approach for Large Language Models cites this paper.

MEraser: An Effective Fingerprint Erasure Approach for Large Language Models Instructional Fingerprinting of Large Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-07T00:51:19.061966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d71d491-0fd2-47e7-8851-a7c988f11eb6 · inbound

A Survey on Model Extraction Attacks and Defenses for Large Language Models cites this paper.

A Survey on Model Extraction Attacks and Defenses for Large Language Models Instructional Fingerprinting of Large Language Models

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-06T22:23:13.891780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3bf314fe-c521-4e9b-9647-a265a22f629b · inbound

A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives cites this paper.

A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives Instructional Fingerprinting of Large Language Models

Reference 230

Resolution: unresolved; no resolver link, observed 2026-08-05T18:12:38.068290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd007d47-9eff-4cdc-9b97-4f308ca50bf3 · inbound

Unlocking the Effectiveness of LoRA-FP for Seamless Transfer Implantation of Fingerprints in Downstream Models cites this paper.

Unlocking the Effectiveness of LoRA-FP for Seamless Transfer Implantation of Fingerprints in Downstream Models Instructional Fingerprinting of Large Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-05T13:17:08.292557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a0357a2-7108-45dd-8bd0-d0e751509a43 · inbound

PREE: Towards Harmless and Adaptive Fingerprint Editing in Large Language Models via Knowledge Prefix Enhancement cites this paper.

PREE: Towards Harmless and Adaptive Fingerprint Editing in Large Language Models via Knowledge Prefix Enhancement Instructional Fingerprinting of Large Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-05T13:11:20.558675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a370fcd6-3b6d-46eb-813d-c78f423b7960 · inbound

CTCC: A Robust and Stealthy Fingerprinting Framework for Large Language Models via Cross-Turn Contextual Correlation Backdoor cites this paper.

CTCC: A Robust and Stealthy Fingerprinting Framework for Large Language Models via Cross-Turn Contextual Correlation Backdoor Instructional Fingerprinting of Large Language Models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-05T05:54:46.835825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bf2f20c3-e678-4d9a-9621-ceb3ff20c7fc · inbound

SeedPrints: Fingerprints Can Even Tell Which Seed Your Large Language Model Was Trained From cites this paper.

SeedPrints: Fingerprints Can Even Tell Which Seed Your Large Language Model Was Trained From Instructional Fingerprinting of Large Language Models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-18T12:01:21.094200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f345ad0c-4a26-40ab-a361-607cc107ed55 · inbound

Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption cites this paper.

Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption Instructional Fingerprinting of Large Language Models

Reference 58

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T05:25:54.307000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 489c242c-c33a-4089-a4cb-f0cc35d1d9ee · inbound

FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences cites this paper.

FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences Instructional Fingerprinting of Large Language Models

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T01:56:28.018767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.