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Paper Citation Record · LEDGER

PersonaMark: Personalized LLM watermarking for model protection and user attribution

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2409.09739.

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

pith.paper-citation-record.v1
2409.09739 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T21:12:22.701113Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T21:53:59.612680Z

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 4fd8acf1-52b3-4a50-8063-13edfbb16be1 · inbound

Survey on AI-Generated Media Detection: From Non-MLLM to MLLM cites this paper.

Survey on AI-Generated Media Detection: From Non-MLLM to MLLM PersonaMark: Personalized LLM watermarking for model protection and user attribution

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-08T21:12:22.701113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T21:12:22.701113Z digest=sha256:1a7c9e7ae711cb1b114f475e3c7336ae669f2bf2eda1552c63ce7e72962d6cba

Observation c5a768ec-1d06-4edb-92ef-b95b61d051ac · 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 PersonaMark: Personalized LLM watermarking for model protection and user attribution

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-06T22:23:15.269056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:23:15.269056Z digest=sha256:fb5e21f08b3aeb72695db0783d81c3c2cb1bf80b24def614de7d612a0c961e2e

Observation 0c054a9a-0633-4102-ad9c-940b89322868 · inbound

SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness cites this paper.

SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness PersonaMark: Personalized LLM watermarking for model protection and user attribution

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-06-29T21:53:59.614068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-29T21:46:56.921674Z digest=sha256:c8db256dc104ae15392ba50655679d388bd58fb56ce33aeae2053c279f830c2f

Observation 2ead7ae9-2f56-4ca4-8bdb-76c234d6e6d5 · inbound

SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness cites this paper.

SAMark: A Self-Anchored Text Watermarking with Paragraph-Level Paraphrase Robustness PersonaMark: Personalized LLM watermarking for model protection and user attribution

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-02T13:13:38.338643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:13:38.338643Z digest=sha256:ff5e2096668eface44b0752be0efc0b988660ab831a87702ceb95f76b6a491c3

Observation 69db7c29-f8f6-4e98-8d65-78673fdbc1ba · inbound

Observation-Level Watermarking and Detection for Tabular Data cites this paper.

Observation-Level Watermarking and Detection for Tabular Data PersonaMark: Personalized LLM watermarking for model protection and user attribution

Reference 25

Resolution
unresolved
no resolver link, observed 2026-07-14T10:52:33.767274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T10:52:33.767274Z digest=sha256:8be99d90b57595a9ca22e6532caa3c3deda7c6111ee5f423fa8ee6cbbd554b6b