Paper Citation Record · LEDGER

DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated Text

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2305.05773.

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

pith.paper-citation-record.v1
2305.05773 v2

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 2026-08-12T06:34:41.77262+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T21:57:16.281145Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T22:46:53.070821Z

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 56f36dae-3028-4660-8d38-194823b7f927 · inbound

Detecting AI-Generated Text in Educational Content: Leveraging Machine Learning and Explainable AI for Academic Integrity cites this paper.

Detecting AI-Generated Text in Educational Content: Leveraging Machine Learning and Explainable AI for Academic Integrity DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated Text

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T21:57:16.281145Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ffb4e76-0a63-465c-997b-7eb0dfb0d33f · inbound

RAG-WM: An Efficient Black-Box Watermarking Approach for Retrieval-Augmented Generation of Large Language Models cites this paper.

RAG-WM: An Efficient Black-Box Watermarking Approach for Retrieval-Augmented Generation of Large Language Models DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated Text

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-10T21:18:37.670075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df5643bf-a7d8-4390-9879-6ca3b339deb4 · inbound

BiMarker: Enhancing Text Watermark Detection for Large Language Models with Bipolar Watermarks cites this paper.

BiMarker: Enhancing Text Watermark Detection for Large Language Models with Bipolar Watermarks DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated Text

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T17:36:52.835976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ef5afb1-9dd0-461d-bfd1-6373981e269e · inbound

Invisible Entropy: Towards Safe and Efficient Low-Entropy LLM Watermarking cites this paper.

Invisible Entropy: Towards Safe and Efficient Low-Entropy LLM Watermarking DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated Text

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T15:43:39.272750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43c68373-22b5-4c47-86e8-eb669950b295 · 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 DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated Text

Reference 107

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:46:53.073485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 8f8c5357-dc16-48a1-841c-94c58cbdf81f · inbound

Can Watermarking Techniques Help Prevent LLM Model Stealing? cites this paper.

Can Watermarking Techniques Help Prevent LLM Model Stealing? DeepTextMark: A Deep Learning-Driven Text Watermarking Approach for Identifying Large Language Model Generated Text

Reference 72

Resolution: unresolved; no resolver link, observed 2026-07-14T09:13:20.561611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.