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Paper Citation Record · LEDGER

Necessary and Sufficient Watermark for Large Language Models

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2310.00833.

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

pith.paper-citation-record.v1
2310.00833 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:29:13.846188Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T17:29:59.992005Z

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 d3c112b8-51df-402d-b622-f182eca2e21f · inbound

Toward Copyright Integrity and Verifiability via Multi-Bit Watermarking for Intelligent Transportation Systems cites this paper.

Toward Copyright Integrity and Verifiability via Multi-Bit Watermarking for Intelligent Transportation Systems Necessary and Sufficient Watermark for Large Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-08T19:29:13.846188Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:29:13.846188Z digest=sha256:3fd1530881624d2f916b099342a4b4ed610caadab607f1e375054431add0050b

Observation 39275d56-5c6c-4376-b196-abfc3395d3f5 · 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 Necessary and Sufficient Watermark for Large Language Models

Reference 135

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:46:52.877740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-18T22:45:31.935618Z digest=sha256:e3f13558929bbcf5877677f85191553e2a91b8c6fefcea9dd88dfd547eb90cf4

Observation e4e7e72d-721d-4b60-b498-b394f0739300 · inbound

RLCracker: Evaluating the Worst-Case Vulnerability of LLM Watermarks with Adaptive RL Attacks cites this paper.

RLCracker: Evaluating the Worst-Case Vulnerability of LLM Watermarks with Adaptive RL Attacks Necessary and Sufficient Watermark for Large Language Models

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-18T14:26:27.994326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-18T14:25:25.576642Z digest=sha256:f6d4e7383b53f8e5a62b1ac985e450a36d09d234838fee2255b7d3a143a9d10a

Observation 0b75df44-6f4e-4385-b6ca-97db3f5b04e1 · inbound

Optimal Multi-bit Generative Watermarking Schemes Under Worst-Case False-Alarm Constraints cites this paper.

Optimal Multi-bit Generative Watermarking Schemes Under Worst-Case False-Alarm Constraints Necessary and Sufficient Watermark for Large Language Models

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:10:57.868131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T16:48:41.367877Z digest=sha256:069734e30c0b7bbfdd69b3da7612ae47231a377205d986006fd1e21b12a94c38

Observation cda8d567-44e6-4da2-9a62-9788a2b59bfe · inbound

Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking cites this paper.

Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking Necessary and Sufficient Watermark for Large Language Models

Reference 61

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T15:31:06.095276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-09T19:52:21.350072Z digest=sha256:adee5aa24471b35f2e8b765c2aa3b2354ca3e19e67aebbb31afab7dd6acf68d2

Observation 8fd11086-3ab7-4fc7-920c-a02ecd74cc26 · inbound

Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking cites this paper.

Block-wise Codeword Embedding for Reliable Multi-bit Text Watermarking Necessary and Sufficient Watermark for Large Language Models

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-07-01T08:25:33.371908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-01T08:18:41.830466Z digest=sha256:5577cadd339fa872a4c9f198c8f9a4c8cd42a05beb7d9653ddc05a1611b75998

Observation a2c06fc3-2578-4e96-b72e-a5e470b689a4 · inbound

PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks cites this paper.

PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks Necessary and Sufficient Watermark for Large Language Models

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:17:02.383112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-13T01:13:55.067785Z digest=sha256:bcff5593c68e3dd4ee9291ba4e158bbb52673c859a2ae9218009d1a7ef5cea6f

Observation d959604c-0565-4316-a1a1-574cd6d10f30 · inbound

PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks cites this paper.

PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks Necessary and Sufficient Watermark for Large Language Models

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-06-30T23:45:08.368796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-30T23:37:21.982973Z digest=sha256:50ec9de4b1b7bc91ddb5d19ad57fb8b6b0c1cf5b069ab6d6d949628f09560a85

Observation 6c792f69-4c87-4c31-996a-5bbcbce6a896 · inbound

CORE-BREW: LLR-Based Soft Decoding for Robust Multi-Bit LLM Watermarking cites this paper.

CORE-BREW: LLR-Based Soft Decoding for Robust Multi-Bit LLM Watermarking Necessary and Sufficient Watermark for Large Language Models

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-07-04T17:29:59.993673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-25T23:42:44.418673Z digest=sha256:04cbb2dc34cea91e3884274f4d32e53103878a9b2aa679f14d219852031d0aec

Observation adc6f1cd-c4f7-4a5e-8653-de2cb11e0d57 · inbound

Toward Stronger Code Watermarking: A Grammar-Driven Approach to Optimizing the Trade-off Between Quality and Detectability cites this paper.

Toward Stronger Code Watermarking: A Grammar-Driven Approach to Optimizing the Trade-off Between Quality and Detectability Necessary and Sufficient Watermark for Large Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-07-14T13:29:55.682502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T13:29:55.682502Z digest=sha256:71bb003363e5e1f6280dfedac366d30884f4dc51bc95cbb137992ab743272e43