Paper Citation Record · LEDGER

Optimizing Token Choice for Code Watermarking: An RL Approach

As of 8 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2508.11925.

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

pith.paper-citation-record.v1
2508.11925 v3

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:46:12.352279Z

measured 27 of 27 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

verified exact0
verified fuzzy10
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bcd112e2-8c46-4071-9066-b032630730c0 · outbound

This paper cites GPT-4 Technical Report.

Optimizing Token Choice for Code Watermarking: An RL Approach GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.233978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bf75437-1660-427a-8f81-9d84576350ab · outbound

This paper cites Program Synthesis with Large Language Models.

Optimizing Token Choice for Code Watermarking: An RL Approach Program Synthesis with Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.238824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1a3d605-f68d-412c-aeef-a30a2469eb30 · outbound

This paper cites Evaluating L arge L anguage M odels trained on code.

Optimizing Token Choice for Code Watermarking: An RL Approach Evaluating L arge L anguage M odels trained on code

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:12.838106Z

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 f665ee2f-6e63-41bb-95fe-658182279196 · outbound

This paper cites Scalable watermarking for identifying large language model outputs.

Optimizing Token Choice for Code Watermarking: An RL Approach Scalable watermarking for identifying large language model outputs

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:12.823436Z

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 09d8da1d-bd3c-4af0-87e9-2147fbaaf54c · outbound

This paper cites GLTR : Statistical detection and visualization of generated text.

Optimizing Token Choice for Code Watermarking: An RL Approach GLTR : Statistical detection and visualization of generated text

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:12.808109Z

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 735b8595-ef19-4e83-a55e-98cd7702b150 · outbound

This paper cites CodeIP: A Grammar-Guided Multi-Bit Watermark for Large Language Models of Code.

Optimizing Token Choice for Code Watermarking: An RL Approach CodeIP: A Grammar-Guided Multi-Bit Watermark for Large Language Models of Code

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.257202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb75da16-f2b2-47be-a2e9-5bbed6bf2334 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Optimizing Token Choice for Code Watermarking: An RL Approach DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.262192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d520ba5e-77eb-4a1a-8a6d-42edb7f65d42 · outbound

This paper cites A survey of static software watermarking.

Optimizing Token Choice for Code Watermarking: An RL Approach A survey of static software watermarking

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:12.793610Z

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 4de69560-80f4-48d4-acc1-fa3fb05dac70 · outbound

This paper cites A watermark for large language models.

Optimizing Token Choice for Code Watermarking: An RL Approach A watermark for large language models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:12.778179Z

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 146c12d7-0a35-4af1-826f-b26e0455cf2b · outbound

This paper cites Paraphrasing evades detectors of AI -generated text, but retrieval is an effective defense.

Optimizing Token Choice for Code Watermarking: An RL Approach Paraphrasing evades detectors of AI -generated text, but retrieval is an effective defense

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:12.761214Z

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 55dd15ed-7a7e-4986-a198-4fff23c89ea4 · outbound

This paper cites Robust Distortion-free Watermarks for Language Models.

Optimizing Token Choice for Code Watermarking: An RL Approach Robust Distortion-free Watermarks for Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.279986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1f10506-9bde-4298-8483-82b5d85aa166 · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

Optimizing Token Choice for Code Watermarking: An RL Approach Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.284413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32a6838c-8959-4489-af44-285408d1d073 · outbound

This paper cites Who Wrote this Code? Watermarking for Code Generation.

Optimizing Token Choice for Code Watermarking: An RL Approach Who Wrote this Code? Watermarking for Code Generation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.289688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbfed843-9b65-486c-8320-b011993c5eb9 · outbound

This paper cites Efficient and Universal Watermarking for LLM-Generated Code Detection.

Optimizing Token Choice for Code Watermarking: An RL Approach Efficient and Universal Watermarking for LLM-Generated Code Detection

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.293801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 356f6fa1-6a4e-4e84-a432-b04375a4b742 · outbound

This paper cites Protecting intellectual property of large language model-based code generation APIs via watermarks.

Optimizing Token Choice for Code Watermarking: An RL Approach Protecting intellectual property of large language model-based code generation APIs via watermarks

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:12.745831Z

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 b778444c-9c88-4a72-b2b9-a6148f60cea5 · outbound

This paper cites A Survey of Text Watermarking in the Era of Large Language Models.

Optimizing Token Choice for Code Watermarking: An RL Approach A Survey of Text Watermarking in the Era of Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.302815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81287eb7-4456-43e5-85f0-003f078d7d76 · outbound

This paper cites Xmark : Dynamic software watermarking using collatz conjecture.

Optimizing Token Choice for Code Watermarking: An RL Approach Xmark : Dynamic software watermarking using collatz conjecture

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:12.730100Z

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 2975049e-6065-49c5-84fb-eb6db1d712f3 · outbound

This paper cites DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature.

Optimizing Token Choice for Code Watermarking: An RL Approach DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.311856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7a25bfc-197b-4b28-9b9a-f3e31deab79f · outbound

This paper cites Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark.

Optimizing Token Choice for Code Watermarking: An RL Approach Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.316399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c345f8b-30ac-4cc9-b959-694e0e10b63f · outbound

This paper cites Language models are unsupervised multitask learners.

Optimizing Token Choice for Code Watermarking: An RL Approach Language models are unsupervised multitask learners

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:12.714933Z

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 4a2b3f39-65c2-45f4-89c6-6ec0ee4187c8 · outbound

This paper cites An axiomatic approach to default risk and model uncertainty in rating systems.

Optimizing Token Choice for Code Watermarking: An RL Approach An axiomatic approach to default risk and model uncertainty in rating systems

Reference 21

Resolution: metadata mismatch; local_arxiv, observed 2026-08-05T19:46:12.488327Z

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 b6f3c9c7-ebfd-4d4e-bad3-914030430b4d · outbound

This paper cites Reparameterizable subset sampling via continuous relaxations.

Optimizing Token Choice for Code Watermarking: An RL Approach Reparameterizable subset sampling via continuous relaxations

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:46:12.698705Z

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 69ddb06c-0b96-428f-9257-46d15bc43762 · outbound

This paper cites Learning to Watermark LLM-generated Text via Reinforcement Learning.

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.

Observation acb263b8-7cd9-45d6-8c82-d23818f0928e · outbound

This paper cites Towards Code Watermarking with Dual-Channel Transformations.

Optimizing Token Choice for Code Watermarking: An RL Approach Towards Code Watermarking with Dual-Channel Transformations

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.338361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6aa7d6f-a85b-493a-965a-352aae1999d8 · outbound

This paper cites SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild.

Optimizing Token Choice for Code Watermarking: An RL Approach SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.342641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85fbae2e-bf6a-4900-8964-d2734082a871 · outbound

This paper cites SoK: Watermarking for AI-Generated Content.

Optimizing Token Choice for Code Watermarking: An RL Approach SoK: Watermarking for AI-Generated Content

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.347126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd6835c7-3303-4b0a-859d-e05e37add1d3 · outbound

This paper cites A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends.

Optimizing Token Choice for Code Watermarking: An RL Approach A Survey of Large Language Models for Code: Evolution, Benchmarking, and Future Trends

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T19:46:12.352279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.