Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 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 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:19:02.712147Z

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 2026-08-07T06:34:17.273281+00:00.

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.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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 2026-08-07T06:34:17.273281+00:00.

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.