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Paper Citation Record · LEDGER

Learning to Watermark LLM-generated Text via Reinforcement Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2403.10553.

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

pith.paper-citation-record.v1
2403.10553 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:15:25.679454Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T22:46:52.927954Z

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 e0a54214-8c94-4269-b504-322656de6949 · inbound

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey cites this paper.

Towards Trustworthy Retrieval Augmented Generation for Large Language Models: A Survey Learning to Watermark LLM-generated Text via Reinforcement Learning

Reference 208

Resolution
unresolved
no resolver link, observed 2026-08-08T19:15:25.679454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:15:25.679454Z digest=sha256:d836e7baafb5e505a74e0472fe64a025f03db0a24e70139ec9b6e9374f046e81

Observation 8f2e745a-78e4-4f08-b6a8-b611580af594 · inbound

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

Invisible Entropy: Towards Safe and Efficient Low-Entropy LLM Watermarking Learning to Watermark LLM-generated Text via Reinforcement Learning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T15:43:40.335605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:43:40.335605Z digest=sha256:895fc36932fcf744523c648535df7e6d328bf074fb43e394482863574c367e48

Observation 853469cd-e590-4e7b-bbfa-08e24bdb43ff · inbound

Authorship Attribution in Multilingual Machine-Generated Texts cites this paper.

Authorship Attribution in Multilingual Machine-Generated Texts Learning to Watermark LLM-generated Text via Reinforcement Learning

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-06T05:33:51.160002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T05:33:51.160002Z digest=sha256:9a94b52eecf702685596ccbbc87e3f621730897efafbb7e2576996e7d090a08f

Observation 0ab9ab70-da00-4a53-86bc-28fbda98c808 · 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 Learning to Watermark LLM-generated Text via Reinforcement Learning

Reference 159

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:46:52.931299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T22:45:31.935618Z digest=sha256:d86a27e99639389d38ddf7e8b4c1def9861270c6b7c698a23fa7b95fe0e7ab28

Observation 69ddb06c-0b96-428f-9257-46d15bc43762 · inbound

Optimizing Token Choice for Code Watermarking: An RL Approach cites this paper.

Optimizing Token Choice for Code Watermarking: An RL Approach Learning to Watermark LLM-generated Text via Reinforcement Learning

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-05T19:46:12.333988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T19:46:12.333988Z digest=sha256:f1b706148ddca6f2eaf1fccdd9410d33ceb79d09c8a44626edcd44b536498091

Observation 53c2a9b5-1d1d-4b6b-8e4f-265196b2009a · inbound

Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption cites this paper.

Position: LLM Watermarking Should Align Stakeholders' Incentives for Practical Adoption Learning to Watermark LLM-generated Text via Reinforcement Learning

Reference 60

Resolution
verified exact
arxiv_id, observed 2026-05-18T05:25:54.539756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-18T05:24:25.622071Z digest=sha256:e6f07f69825b0b9617f948d3f1cd73144a19271280c8974ebb1c228210b56ee4

Observation 651f162b-f6f5-4a0a-9997-651becacca5b · 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 Learning to Watermark LLM-generated Text via Reinforcement Learning

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:10:58.137557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T16:48:41.367877Z digest=sha256:39d4e6b990aff11100744bed5871d1162fbb526fa6ecc5fd9e7ed0b0648ba956

Observation fd73aa99-2b9c-4aa1-a9a5-25bdad3842b8 · inbound

Beyond A Fixed Seal: Adaptive Stealing Watermark in Large Language Models cites this paper.

Beyond A Fixed Seal: Adaptive Stealing Watermark in Large Language Models Learning to Watermark LLM-generated Text via Reinforcement Learning

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T08:25:59.484231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T16:39:50.659037Z digest=sha256:a9d0baa2eda5254caac669a29bf6ee9e9d2d247ad6870c1fb35fe4c40c4d34de

Observation b17b3470-94f6-4e77-a974-5eef65504d87 · inbound

Fundamental Trade-Offs in Multi-Bit Watermarking of Stochastic Processes cites this paper.

Fundamental Trade-Offs in Multi-Bit Watermarking of Stochastic Processes Learning to Watermark LLM-generated Text via Reinforcement Learning

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:56:25.816731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-12T01:32:57.175350Z digest=sha256:64a44e6f4231914508360c05d211a4bbb7a40ff1c94c24e08302bbba09914ec6