Paper Citation Record · LEDGER

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness

As of 11 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 3 inbound Pith citation observations for arXiv:2506.07403.

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

pith.paper-citation-record.v1
2506.07403 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:41:02.631983Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T13:52:08.772681Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:56:57.447009Z

Reference resolution

36 of 36 outbound references displayed

verified exact1
verified fuzzy18
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 70162413-a076-4a3f-9bd3-5269aa91f692 · outbound

This paper cites Academic integrity considerations of ai large language models in the post- pandemic era: Chatgpt and beyond.Journal of University Teaching and Learning Practice, 20 (2), 2023.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Academic integrity considerations of ai large language models in the post- pandemic era: Chatgpt and beyond.Journal of University Teaching and Learning Practice, 20 (2), 2023

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:03.041272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f26201ea-10a1-4b5b-a68a-22c424114b2a · outbound

This paper cites Copyright Protection in Generative AI: A Technical Perspective.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Copyright Protection in Generative AI: A Technical Perspective

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.515646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b88e46d3-c768-4e55-b0c3-4414f064c552 · outbound

This paper cites The Ethical Need for Watermarks in Machine-Generated Language.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness The Ethical Need for Watermarks in Machine-Generated Language

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.519817Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 609f2e5f-a86e-406d-8cd5-4a5684c7c963 · outbound

This paper cites Building Intelligence Identification System via Large Language Model Watermarking: A Survey and Beyond.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Building Intelligence Identification System via Large Language Model Watermarking: A Survey and Beyond

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-07T05:41:02.802664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6fe370b9-f89c-4ef7-aee2-1d8fe97ae7ae · outbound

This paper cites A Watermark for Large Language Models.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness A Watermark for Large Language Models

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:03.030353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 325a73c8-c81f-46d6-b555-a9c9054c4d73 · outbound

This paper cites Watermarking gpt outputs, 2022.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Watermarking gpt outputs, 2022

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:03.020393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e363e2fb-1361-4075-b59a-de2ef22eb0a7 · outbound

This paper cites Provable Robust Watermarking for AI-Generated Text.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Provable Robust Watermarking for AI-Generated Text

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.535856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee675f26-86b8-4058-9c2a-db8a7aa34b5b · outbound

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

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Who Wrote this Code? Watermarking for Code Generation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.539656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9a82dbb-c3cd-4d6f-94c3-a408fce16be2 · outbound

This paper cites An Entropy-based Text Watermarking Detection Method.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness An Entropy-based Text Watermarking Detection Method

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.543118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8430ca6b-6fd4-4cc9-84b2-355165bf1afc · outbound

This paper cites Optimizing Watermarks for Large Language Models.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Optimizing Watermarks for Large Language Models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:03.008982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9788929a-3801-4502-bbcf-9fcba5e1211d · outbound

This paper cites Adaptive Text Watermark for Large Language Models.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Adaptive Text Watermark for Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.549733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 370896eb-ba81-48ce-b4d1-da8da89b977f · outbound

This paper cites Unbiased Watermark for Large Language Models.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Unbiased Watermark for Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.553150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9306e0d-9ded-4704-b90f-0aeaa95bf0ce · outbound

This paper cites A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.996918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ca2bcec4-13c1-488d-89f4-7d579fd8902c · outbound

This paper cites SpecInfer: Accelerating Large Language Model Serving with Tree-Based Speculative Inference and Verification.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness SpecInfer: Accelerating Large Language Model Serving with Tree-Based Speculative Inference and Verification

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.986594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c6c68057-a9ec-4490-b04a-2b1c8bcdf281 · outbound

This paper cites An Unforgeable Publicly Verifiable Watermark for Large Language Models.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness An Unforgeable Publicly Verifiable Watermark for Large Language Models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.975930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0c49795d-598e-476a-aa04-390d9b28668f · outbound

This paper cites Towards Codable Watermarking for Injecting Multi-Bits Information to LLMs.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Towards Codable Watermarking for Injecting Multi-Bits Information to LLMs

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.964816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8edefd53-d188-4eae-b12c-300911eab52d · outbound

This paper cites Advancing Beyond Identification: Multi-bit Watermark for Large Language Models.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Advancing Beyond Identification: Multi-bit Watermark for Large Language Models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.953728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation edef35bb-d445-4147-8233-5590c84a9c0f · outbound

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

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness CodeIP: A Grammar-Guided Multi-Bit Watermark for Large Language Models of Code

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.571551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c28cafbd-a028-4e26-aa63-59f910b692c8 · outbound

This paper cites A Robust Semantics-based Watermark for Large Language Model against Paraphrasing.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness A Robust Semantics-based Watermark for Large Language Model against Paraphrasing

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.574849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a06b1165-d459-4156-8dde-1193c28b42b3 · outbound

This paper cites REMARK- LLM: A Robust and Efficient Watermarking Framework for Generative Large Language Models.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness REMARK- LLM: A Robust and Efficient Watermarking Framework for Generative Large Language Models

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.941778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 5a74bc96-ba1e-4986-97fa-bbb4883318b2 · outbound

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

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Robust Distortion-free Watermarks for Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.581169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f13b23a3-cc18-4643-8ca5-604d328ad691 · outbound

This paper cites Undetectable Watermarks for Language Models.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Undetectable Watermarks for Language Models

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.929967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 93a5fd60-64b5-480e-96c7-f24a3bbc708e · outbound

This paper cites GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.917658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 55832715-46c6-45d2-a06d-2dd13b98db36 · outbound

This paper cites Scalable watermarking for identifying large language model outputs.Nature, 634(8035):818–823, 2024.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Scalable watermarking for identifying large language model outputs.Nature, 634(8035):818–823, 2024

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.590939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c0648228-6037-4896-bef5-8ab1d7d0d46b · outbound

This paper cites Duwak: Dual Watermarks in Large Language Models.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Duwak: Dual Watermarks in Large Language Models

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.899900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 60d009b3-4ae2-47ce-82f8-3e906cc27146 · outbound

This paper cites Watermarking Conditional Text Generation for AI Detection: Unveiling Challenges and a Semantic-Aware Watermark Remedy.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Watermarking Conditional Text Generation for AI Detection: Unveiling Challenges and a Semantic-Aware Watermark Remedy

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.889639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2ac1393d-1d7f-4380-a40a-667fca8d347c · outbound

This paper cites WatME: Towards Lossless Watermarking Through Lexical Redundancy.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness WatME: Towards Lossless Watermarking Through Lexical Redundancy

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.877687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1984f33d-5c2f-4e62-9814-03ca87c6d78b · outbound

This paper cites MarkLLM: An Open-Source Toolkit for LLM Watermarking.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness MarkLLM: An Open-Source Toolkit for LLM Watermarking

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.603578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3cea9f7e-a037-4c78-99d1-0a3021862e7c · outbound

This paper cites Attention is all you need.Advances in Neural Information Processing Systems, 2017.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Attention is all you need.Advances in Neural Information Processing Systems, 2017

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.607135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d6dd473-7d00-4fde-870f-d5f2525b693a · outbound

This paper cites What Language Model Architecture and Pretraining Objective Works Best for Zero-Shot Generalization? InICML, pages 22964–22984, 2022.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness What Language Model Architecture and Pretraining Objective Works Best for Zero-Shot Generalization? InICML, pages 22964–22984, 2022

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.861851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 03adb95e-cbb5-4c2c-b53e-17aefaff0e65 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness LLaMA: Open and Efficient Foundation Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.613528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 888f7df6-bf98-44ec-939d-09ef845a64c6 · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90% chatgpt quality, 2023.https://vicuna.lmsys.org.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Vicuna: An open-source chatbot impressing gpt-4 with 90% chatgpt quality, 2023.https://vicuna.lmsys.org

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.850849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ac03c6af-0dc3-47c5-985d-2a2e4b63e37f · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Measuring Massive Multitask Language Understanding

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.620883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 272b37a0-984e-4d62-bbb8-a19186c83ce4 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Training Verifiers to Solve Math Word Problems

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.624775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2131d0b2-cac1-4551-99f5-f17a6ed048c2 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T05:41:02.628809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f773b2d1-d988-4924-ad10-b73ab0b717f6 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness Chain-of-thought prompting elicits reasoning in large language models

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:41:02.834285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation 0afaab52-db0b-45fb-a30a-91d7727d229e · 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 Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness

Reference 168

Resolution: verified exact; arxiv_id, observed 2026-05-18T22:46:53.083458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 87ad51f1-50d6-4920-ae57-c6a9c979b1c2 · inbound

LLM Self-Recognition: Steering and Retrieving Activation Signatures cites this paper.

LLM Self-Recognition: Steering and Retrieving Activation Signatures Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:56:57.448470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dc0a0d99-cb81-477f-8022-ca16b3683eaf · inbound

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts cites this paper.

Marking the Wrong Symptoms: Evaluating LLM Watermarks in Medical Texts Enhancing Watermarking Quality for LLMs via Contextual Generation States Awareness

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T13:52:08.772681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.