Paper Citation Record · LEDGER

Watermarking Techniques for Large Language Models: A Survey

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2409.00089.

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

pith.paper-citation-record.v1
2409.00089 v1

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 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:30:13.820538Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T04:09:34.592296Z

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 cdcda08a-356b-4496-9ab1-61e08432b8e4 · inbound

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption cites this paper.

SECNEURON: Reliable and Flexible Abuse Control in Local LLMs via Hybrid Neuron Encryption Watermarking Techniques for Large Language Models: A Survey

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T10:30:13.820538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b66ec76-4704-4d84-bb8a-678e90af440b · inbound

Watermarking Large Language Model-based Time Series Forecasting cites this paper.

Watermarking Large Language Model-based Time Series Forecasting Watermarking Techniques for Large Language Models: A Survey

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T13:21:26.144007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e02fe4e0-59a6-46d0-84a1-70a0e9acd6d4 · inbound

Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends cites this paper.

Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends Watermarking Techniques for Large Language Models: A Survey

Reference 94

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:46:53.297861Z

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.

Observation c6ac6c94-70ae-42df-8dfb-db2441657320 · inbound

Green-Red Watermarking for Recommender Systems cites this paper.

Green-Red Watermarking for Recommender Systems Watermarking Techniques for Large Language Models: A Survey

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:26:17.378098Z

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.

Observation 50f5c2c6-18fb-4a73-b8e6-660e80b6ad98 · inbound

PeerCheck: Enhancing LLM-Generated Academic Reviews Towards Human-Level Quality cites this paper.

PeerCheck: Enhancing LLM-Generated Academic Reviews Towards Human-Level Quality Watermarking Techniques for Large Language Models: A Survey

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-07-04T04:09:34.594933Z

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.