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Paper Citation Record · LEDGER

Watermarking Low-entropy Generation for Large Language Models: An Unbiased and Low-risk Method

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2405.14604.

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

pith.paper-citation-record.v1
2405.14604 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:40:42.297444Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T07:43:14.293758Z

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 aaccd686-180b-4166-a723-df7da04ba9a1 · inbound

Topic-Based Watermarks for Large Language Models cites this paper.

Topic-Based Watermarks for Large Language Models Watermarking Low-entropy Generation for Large Language Models: An Unbiased and Low-risk Method

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-24T02:03:43.941704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-24T02:03:15.833131Z digest=sha256:dfc34679127ff07f858f7bd49d9480bbe3d871c038ac1ba817aa9db7f7e94509

Observation d9bc650f-6040-4afc-b58a-aa4d6cdb5963 · inbound

MorphMark: Flexible Adaptive Watermarking for Large Language Models cites this paper.

MorphMark: Flexible Adaptive Watermarking for Large Language Models Watermarking Low-entropy Generation for Large Language Models: An Unbiased and Low-risk Method

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-15T21:40:42.297444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:40:42.297444Z digest=sha256:ecc35af52374d386cb114c2038298ccfb9127c1aabf3789667dee192a095777b

Observation 0757ecd5-4e04-47fb-8d17-dfe36c370fc8 · inbound

A Watermark for Auto-Regressive Image Generation Models cites this paper.

A Watermark for Auto-Regressive Image Generation Models Watermarking Low-entropy Generation for Large Language Models: An Unbiased and Low-risk Method

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T04:19:02.712147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:19:02.712147Z digest=sha256:8bffef2ebdfe1d8b4783f77ef9557015485ae6f28f97c16980eb914bc2688cbf

Observation 3c2c6c09-d03c-4594-9787-6d34d5e76916 · inbound

MATRIX: Multi-Layer Code Watermarking via Dual-Channel Constrained Parity-Check Encoding cites this paper.

MATRIX: Multi-Layer Code Watermarking via Dual-Channel Constrained Parity-Check Encoding Watermarking Low-entropy Generation for Large Language Models: An Unbiased and Low-risk Method

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-10T09:08:26.646816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T08:23:04.201981Z digest=sha256:ba6c29cd7492109fac4e7d246db747723908c5b89f8ff960b2ba7502e441eaa0

Observation 55b864dc-4552-4ba7-9ced-7325e3f41f4a · inbound

Trustworthy AI: Ensuring Reliability and Accountability from Models to Agents cites this paper.

Trustworthy AI: Ensuring Reliability and Accountability from Models to Agents Watermarking Low-entropy Generation for Large Language Models: An Unbiased and Low-risk Method

Reference 111

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:21:16.289177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-12T02:21:12.882825Z digest=sha256:4b113054c624c215ac221f3654abfb24d0a787d7ab9faff708f749b4b5704c66

Observation 184cb8a2-3fe3-4929-b142-bd95021bea21 · inbound

Linear Ensembles Wash Away Watermarks: On the Fragility of Distributional Perturbations in LLMs cites this paper.

Linear Ensembles Wash Away Watermarks: On the Fragility of Distributional Perturbations in LLMs Watermarking Low-entropy Generation for Large Language Models: An Unbiased and Low-risk Method

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-06-29T07:43:14.296226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-29T07:35:13.730366Z digest=sha256:117407d0f245f3fb247d46d316a6f30b0c49ac4a932cb03776e468873f5d27d1

Observation e10d44e0-c09f-4552-8850-be6eb03828d3 · 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 Watermarking Low-entropy Generation for Large Language Models: An Unbiased and Low-risk Method

Reference 25

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=sha256:2acd8f89e419f5603c2f7c49f7bbabf0176af68c81dcf4350fb6bbb80f7278cd