Character-Level Perturbations Disrupt LLM Watermarks | Paper Citation Record

Observation af1c3dac-5a6b-47f0-b9da-6114394187e5 · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

Character-Level Perturbations Disrupt LLM Watermarks OPT: Open Pre-trained Transformer Language Models

Reference 1

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Observation f95d0745-38c1-45f7-bf9d-1747d668a072 · outbound

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

Character-Level Perturbations Disrupt LLM Watermarks LLaMA: Open and Efficient Foundation Language Models

Reference 2

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Observation 9e718246-4dfd-400e-9ab1-817f5907d1cc · outbound

This paper cites Openai chatgpt blog,.

Character-Level Perturbations Disrupt LLM Watermarks Openai chatgpt blog,

Reference 3

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Observation aeba42fb-1191-40ac-8275-8b3062c3f54a · outbound

This paper cites Deepseek terms of use,.

Character-Level Perturbations Disrupt LLM Watermarks Deepseek terms of use,

Reference 4

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Observation 73bbabcb-5d4a-413d-9124-68b9f30a9271 · outbound

This paper cites Gemini api additional terms of service,.

Character-Level Perturbations Disrupt LLM Watermarks Gemini api additional terms of service,

Reference 5

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Observation 0dc0cfca-559d-4ebe-b84c-c1bbeb95ca34 · outbound

This paper cites Grammarly.

Character-Level Perturbations Disrupt LLM Watermarks Grammarly

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.106363Z

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Observation 86c47f59-411a-45c1-b8f9-03162a0c3751 · outbound

This paper cites Chatpaper.

Character-Level Perturbations Disrupt LLM Watermarks Chatpaper

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.136232Z

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Observation 25a8acb9-e072-476f-a2ce-7293e0584fa2 · outbound

This paper cites Transforming the future of music creation.

Character-Level Perturbations Disrupt LLM Watermarks Transforming the future of music creation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.189600Z

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Observation 23e1971f-30a2-44ef-896a-8681f59f4373 · outbound

This paper cites Quickstart: Generate and verify an image’s watermark using imagen text-to-image (console).

Character-Level Perturbations Disrupt LLM Watermarks Quickstart: Generate and verify an image’s watermark using imagen text-to-image (console)

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.240567Z

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Observation 610cf1b5-f003-4000-9641-276426b4deb3 · outbound

This paper cites Self-supervised adversarial example detection by disentangled representation,.

Character-Level Perturbations Disrupt LLM Watermarks Self-supervised adversarial example detection by disentangled representation,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.243147Z

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Observation 3b04871c-e940-44a5-8b3b-f7d8352b813c · outbound

This paper cites Evaluating membership inference through adversarial robustness,.

Character-Level Perturbations Disrupt LLM Watermarks Evaluating membership inference through adversarial robustness,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.266271Z

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Observation 64306f4c-6f26-478c-a3af-4a189294a195 · outbound

This paper cites Not all edges are equally robust: Evaluating the robustness of ranking-based federated learning,.

Character-Level Perturbations Disrupt LLM Watermarks Not all edges are equally robust: Evaluating the robustness of ranking-based federated learning,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.319803Z

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Observation ca756dd5-3883-4cd9-92c7-7c9bd68bbd06 · outbound

This paper cites When better features mean greater risks: The performance- privacy trade-off in contrastive learning,.

Character-Level Perturbations Disrupt LLM Watermarks When better features mean greater risks: The performance- privacy trade-off in contrastive learning,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.387501Z

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Observation 1f4cd71c-4cb2-4b1b-a515-e188907bf284 · outbound

This paper cites Dynamic graph unlearning: a general and efficient post-processing method via gradi- ent transformation,.

Character-Level Perturbations Disrupt LLM Watermarks Dynamic graph unlearning: a general and efficient post-processing method via gradi- ent transformation,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.427491Z

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Observation b946c5b4-04e9-4458-ba16-ee32c629e76b · outbound

This paper cites Unraveling privacy risks of individual fairness in graph neural networks,.

Character-Level Perturbations Disrupt LLM Watermarks Unraveling privacy risks of individual fairness in graph neural networks,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.485556Z

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Observation 4d14f793-8ff2-45e7-b6d5-339e9e2d1425 · outbound

This paper cites On the risk of misinformation pollution with large language models,.

Character-Level Perturbations Disrupt LLM Watermarks On the risk of misinformation pollution with large language models,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.531624Z

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Observation cd411e46-a3fb-49d2-8a12-4bdd5d8ab87c · outbound

This paper cites Spear Phishing With Large Language Models.

Character-Level Perturbations Disrupt LLM Watermarks Spear Phishing With Large Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.589714Z

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Observation dd80004e-74c3-433e-bef1-7e8fcf9fe996 · outbound

This paper cites Chatgpt for good? on opportunities and challenges of large language models for education,.

Character-Level Perturbations Disrupt LLM Watermarks Chatgpt for good? on opportunities and challenges of large language models for education,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.647691Z

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Observation 6ef2c037-1a1a-42fe-9191-1cfbe991e1b9 · outbound

This paper cites A watermark for large language models,.

Character-Level Perturbations Disrupt LLM Watermarks A watermark for large language models,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.687781Z

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Observation 1f471d1d-fafd-4e8d-98d9-9a1f59772796 · outbound

This paper cites Provable robust watermarking for AI-generated text,.

Character-Level Perturbations Disrupt LLM Watermarks Provable robust watermarking for AI-generated text,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.734763Z

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Observation 7fba4bf8-80ec-4bab-b539-049ecb010e5d · outbound

This paper cites Unbiased watermark for large language models,.

Character-Level Perturbations Disrupt LLM Watermarks Unbiased watermark for large language models,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:50.839856Z

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Observation 681c2d0a-2566-4b9d-b959-ba06eb95b302 · outbound

This paper cites A resilient and accessible distribution-preserving watermark for large language models,.

Character-Level Perturbations Disrupt LLM Watermarks A resilient and accessible distribution-preserving watermark for large language models,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.012068Z

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Observation 074e755d-8d82-4cfc-9609-5b9462d03de3 · outbound

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

Character-Level Perturbations Disrupt LLM Watermarks Scalable watermarking for identifying large language model outputs,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.120204Z

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Observation 219bb5de-11c5-4d2e-a0ab-b65e2e9f7158 · outbound

This paper cites Robust distortion-free watermarks for language models,.

Character-Level Perturbations Disrupt LLM Watermarks Robust distortion-free watermarks for language models,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.280380Z

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Observation 5a130255-fa94-4c60-aada-778758f4a513 · outbound

This paper cites Undetectable watermarks for language models,.

Character-Level Perturbations Disrupt LLM Watermarks Undetectable watermarks for language models,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.472649Z

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Observation 711f4715-12be-4419-ae98-4a1b7e30a767 · outbound

This paper cites Bimark: Unbiased multilayer watermarking for large language models,.

Character-Level Perturbations Disrupt LLM Watermarks Bimark: Unbiased multilayer watermarking for large language models,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.475398Z

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Observation d96a3aa7-4cf8-4296-b2e5-c40baf2907a1 · outbound

This paper cites A Certified Robust Watermark For Large Language Models.

Character-Level Perturbations Disrupt LLM Watermarks A Certified Robust Watermark For Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.478031Z

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Observation 375488aa-3132-453d-8623-a8c37b759485 · outbound

This paper cites Bypassing LLM watermarks with color- aware substitutions,.

Character-Level Perturbations Disrupt LLM Watermarks Bypassing LLM watermarks with color- aware substitutions,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.481037Z

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Observation 6a8047f6-5637-484d-860f-005adf515442 · outbound

This paper cites b 4: A black-box scrubbing attack on LLM watermarks,.

Character-Level Perturbations Disrupt LLM Watermarks b 4: A black-box scrubbing attack on LLM watermarks,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.483600Z

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Observation 2e6c8b32-61c5-48a6-86b2-fb5f686054e0 · outbound

This paper cites De-mark: Watermark removal in large language models,.

Character-Level Perturbations Disrupt LLM Watermarks De-mark: Watermark removal in large language models,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.486079Z

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Observation 01dcd123-91e0-498c-b77f-1eee60e2b138 · outbound

This paper cites Watermark Smoothing Attacks against Language Models.

Character-Level Perturbations Disrupt LLM Watermarks Watermark Smoothing Attacks against Language Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.488748Z

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Observation b47e50ba-84ee-4318-81ef-6f983f7a5180 · outbound

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

Character-Level Perturbations Disrupt LLM Watermarks Paraphrasing evades detectors of ai-generated text, but retrieval is an effective defense,

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.491415Z

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Observation 170903a3-188e-463e-b5f2-3ed59e5dcd1e · outbound

This paper cites On the reliability of watermarks for large language models,.

Character-Level Perturbations Disrupt LLM Watermarks On the reliability of watermarks for large language models,

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.493900Z

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Observation 2bac9422-7bc1-44a2-a67e-2918d54d90a1 · outbound

This paper cites Markmywords: Analyzing and evaluating language model watermarks,.

Character-Level Perturbations Disrupt LLM Watermarks Markmywords: Analyzing and evaluating language model watermarks,

Reference 34

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Observation d78e126a-9892-4403-baef-81335802e8ef · outbound

This paper cites Textbugger: Generating adversarial text against real-world applications,.

Character-Level Perturbations Disrupt LLM Watermarks Textbugger: Generating adversarial text against real-world applications,

Reference 35

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Observation ab842ec1-e927-44b5-b1b1-6832a794a607 · outbound

This paper cites Textattack: A framework for adversarial attacks, data augmentation, and adversarial training in nlp,.

Character-Level Perturbations Disrupt LLM Watermarks Textattack: A framework for adversarial attacks, data augmentation, and adversarial training in nlp,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.501431Z

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Observation 6656c59e-9302-4c0c-a6cb-e3934b8040d7 · outbound

This paper cites Black-box generation of adversarial text sequences to evade deep learning classifiers,.

Character-Level Perturbations Disrupt LLM Watermarks Black-box generation of adversarial text sequences to evade deep learning classifiers,

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.503983Z

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Observation d3bcf567-a4fc-46af-be4b-6aa044c64693 · outbound

This paper cites Exploring Gradient-Guided Masked Language Model to Detect Textual Adversarial Attacks.

Character-Level Perturbations Disrupt LLM Watermarks Exploring Gradient-Guided Masked Language Model to Detect Textual Adversarial Attacks

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.506675Z

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Observation 95f0f9bc-0bf2-42c1-beab-257e035e8796 · outbound

This paper cites Masked language model based textual adversarial example detection,.

Character-Level Perturbations Disrupt LLM Watermarks Masked language model based textual adversarial example detection,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.509818Z

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Observation 97c9dea4-216b-488f-9676-6b630a7290d5 · outbound

This paper cites Watermark stealing in large language models,.

Character-Level Perturbations Disrupt LLM Watermarks Watermark stealing in large language models,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.512236Z

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Observation d655e9cd-ac77-41a0-a642-16ad44da3855 · outbound

This paper cites Stealing watermarks of large language models via mixed integer programming,.

Character-Level Perturbations Disrupt LLM Watermarks Stealing watermarks of large language models via mixed integer programming,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.514650Z

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Observation 761aaf7b-3953-4a74-995b-dea8f5b81598 · outbound

This paper cites Can watermarks survive translation? on the cross-lingual consistency of text watermark for large language models,.

Character-Level Perturbations Disrupt LLM Watermarks Can watermarks survive translation? on the cross-lingual consistency of text watermark for large language models,

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.517041Z

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Observation a9f7d773-9aae-4b4c-a6a9-a8e97877789a · outbound

This paper cites On Evaluating The Performance of Watermarked Machine-Generated Texts Under Adversarial Attacks.

Character-Level Perturbations Disrupt LLM Watermarks On Evaluating The Performance of Watermarked Machine-Generated Texts Under Adversarial Attacks

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.519469Z

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Observation f3ff928d-3c0c-4544-bc3b-eb3e2a033914 · outbound

This paper cites Silverspeak: Evading ai-generated text detectors using homoglyphs,.

Character-Level Perturbations Disrupt LLM Watermarks Silverspeak: Evading ai-generated text detectors using homoglyphs,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.522573Z

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Observation 83e67408-48f4-47d0-9c06-5f3d00c9a010 · outbound

This paper cites Watermarks in the sand: impossibility of strong watermarking for language models,.

Character-Level Perturbations Disrupt LLM Watermarks Watermarks in the sand: impossibility of strong watermarking for language models,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.525081Z

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Observation 446f6627-c982-4311-a849-1648856c03e0 · outbound

This paper cites Watermark under fire: A robustness evaluation of llm watermarking,.

Character-Level Perturbations Disrupt LLM Watermarks Watermark under fire: A robustness evaluation of llm watermarking,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.527481Z

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Observation 82c4f5a0-2b51-4e6b-835b-e0196476444f · outbound

This paper cites Sslguard: A watermarking scheme for self-supervised learning pre-trained encoders,.

Character-Level Perturbations Disrupt LLM Watermarks Sslguard: A watermarking scheme for self-supervised learning pre-trained encoders,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.529999Z

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Observation 7ba6361f-37c2-4ab9-861b-aa5a11034f7d · outbound

This paper cites Entangled watermarks as a defense against model extraction,.

Character-Level Perturbations Disrupt LLM Watermarks Entangled watermarks as a defense against model extraction,

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.532316Z

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Observation a518a146-2387-42d3-ad09-49313477f8c5 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

Character-Level Perturbations Disrupt LLM Watermarks Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.534766Z

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Observation 2c7283d7-325b-49e1-ac60-945dc8da4060 · outbound

This paper cites Synthid.

Character-Level Perturbations Disrupt LLM Watermarks Synthid

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.537247Z

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Observation 7c481b3a-6f21-4141-8a4a-20099744aeca · outbound

This paper cites Terms of use,.

Character-Level Perturbations Disrupt LLM Watermarks Terms of use,

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.539643Z

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Observation 888b75bd-7e67-4ff7-a710-539909486d53 · outbound

This paper cites Optimizing adaptive attacks against content watermarks for language models,.

Character-Level Perturbations Disrupt LLM Watermarks Optimizing adaptive attacks against content watermarks for language models,

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.542218Z

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Observation 532e6623-8cfb-4399-8b10-9d69ce010d5c · outbound

This paper cites Markllm: An open-source toolkit for llm watermarking,.

Character-Level Perturbations Disrupt LLM Watermarks Markllm: An open-source toolkit for llm watermarking,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.544695Z

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Observation 5ebde10f-8818-4b65-9628-7e3fc2812608 · outbound

This paper cites Software Framework for Topic Modelling with Large Corpora,.

Character-Level Perturbations Disrupt LLM Watermarks Software Framework for Topic Modelling with Large Corpora,

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.547241Z

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Observation 8079ca2f-7778-4935-8656-362c6ccf748a · outbound

This paper cites AuthorMist: Evading AI Text Detectors with Reinforcement Learning.

Character-Level Perturbations Disrupt LLM Watermarks AuthorMist: Evading AI Text Detectors with Reinforcement Learning

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.549738Z

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Observation 17d1b733-e8c0-4662-88c5-e027750bdcd4 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation,.

Character-Level Perturbations Disrupt LLM Watermarks Bleu: a method for automatic evaluation of machine translation,

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.552722Z

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Observation ad71345a-99b2-4dda-a860-b192500809ba · outbound

This paper cites Rouge: A package for automatic evaluation of summaries,.

Character-Level Perturbations Disrupt LLM Watermarks Rouge: A package for automatic evaluation of summaries,

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.555135Z

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Observation c9135b88-33aa-44c1-9676-f03f0eb886ba · outbound

This paper cites The cefr levels.

Character-Level Perturbations Disrupt LLM Watermarks The cefr levels

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.557552Z

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Observation 2ded87d2-d40f-494a-a90e-7e672deb6a0b · outbound

This paper cites No free lunch in LLM watermarking: Trade-offs in watermarking design choices,.

Character-Level Perturbations Disrupt LLM Watermarks No free lunch in LLM watermarking: Trade-offs in watermarking design choices,

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.560050Z

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Observation 36368584-233b-4e00-9b85-40d1fc8c28aa · outbound

This paper cites New ai classifier for indicating ai-written tex,.

Character-Level Perturbations Disrupt LLM Watermarks New ai classifier for indicating ai-written tex,

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.562553Z

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Observation ac015a89-3fbc-4f7b-8369-27e998cde758 · outbound

This paper cites Ai detector by grammarly.

Character-Level Perturbations Disrupt LLM Watermarks Ai detector by grammarly

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.565140Z

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Observation d492b1c6-5759-4b8c-9aef-ca60198a7e40 · outbound

This paper cites Gptzero’s ai detection technology.

Character-Level Perturbations Disrupt LLM Watermarks Gptzero’s ai detection technology

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.567775Z

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Observation bd70620d-e1db-403e-8409-964d3466b614 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding,.

Character-Level Perturbations Disrupt LLM Watermarks Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.570265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1852bfb4-a84b-401e-843f-68f7227f0ebf · outbound

This paper cites Languagetool.

Character-Level Perturbations Disrupt LLM Watermarks Languagetool

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.572662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6635be85-c3ec-4b7c-b9f1-e6027b16a80e · outbound

This paper cites Python tesseract.

Character-Level Perturbations Disrupt LLM Watermarks Python tesseract

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.575026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94603794-456f-49da-ae57-f6817e1f2a8d · outbound

This paper cites Unicodedata.

Character-Level Perturbations Disrupt LLM Watermarks Unicodedata

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.577525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27693111-82a8-4098-bf69-763669810bde · outbound

This paper cites Results are reported forn= 5,10, and15, using both token- level and character-level perturbations across five watermark- ing schemes.

Character-Level Perturbations Disrupt LLM Watermarks Results are reported forn= 5,10, and15, using both token- level and character-level perturbations across five watermark- ing schemes

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.580631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11a52c92-b1d3-4a3b-8614-fd49f5be26b2 · outbound

This paper cites We compare both token-level (dashed lines) and character-level (solid lines) perturbations.

Character-Level Perturbations Disrupt LLM Watermarks We compare both token-level (dashed lines) and character-level (solid lines) perturbations

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.583360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b3f3546-5755-4d2d-8d3a-d65d2fbb1f25 · outbound

This paper cites As introduced TABLE XV: Performance of reference detectors with three levels of data augmentation across five watermark schemes.

Character-Level Perturbations Disrupt LLM Watermarks As introduced TABLE XV: Performance of reference detectors with three levels of data augmentation across five watermark schemes

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.586020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a20e059-ac93-4eb6-958c-611393b97e47 · outbound

This paper cites Major Revision.

Character-Level Perturbations Disrupt LLM Watermarks Major Revision

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.588729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b166493-c74c-4c53-9781-266e1cd21bfc · outbound

This paper cites We recom- mend downloading the code using the following command: git clone https://github.com/plll4zzx/CharacterRemoval4WM.

Character-Level Perturbations Disrupt LLM Watermarks We recom- mend downloading the code using the following command: git clone https://github.com/plll4zzx/CharacterRemoval4WM

Reference 71

Resolution: verified exact; doi, observed 2026-08-04T19:49:01.231791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 61a40ad6-0521-4c50-9d3e-e998b30e21ea · outbound

This paper cites an unresolved cited work.

Character-Level Perturbations Disrupt LLM Watermarks Unresolved cited work

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.594038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation be7ba321-042e-441d-8d9f-2a6d5dd1cb3d · outbound

This paper cites an unresolved cited work.

Character-Level Perturbations Disrupt LLM Watermarks Unresolved cited work

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.596929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 602d3fd1-93ae-49ac-9d77-b6519a501039 · outbound

This paper cites real- newslike/*.

Character-Level Perturbations Disrupt LLM Watermarks real- newslike/*

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.599453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5c90de35-de9d-4060-8c8b-694dcd33c20b · outbound

This paper cites /../dataset/c4/realnewslike.

Character-Level Perturbations Disrupt LLM Watermarks /../dataset/c4/realnewslike

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.602058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0dc88317-ae32-4354-b1ec-0980abe5b17e · outbound

This paper cites KGW" --num_epochs 15 \ --rand_char_rate 0.15 --rand_times 9 \ --llm_name.

Character-Level Perturbations Disrupt LLM Watermarks KGW" --num_epochs 15 \ --rand_char_rate 0.15 --rand_times 9 \ --llm_name

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-04T19:46:51.604848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Outbound references

Pith citing papers