Robust Detection of Watermarks for Large Language Models Under Human Edits | Paper Citation Record

Observation 0c58ee3e-aa39-40c1-9eae-b2cb6715a7be · outbound

This paper cites Watermarking of large language models, August 2023.

Robust Detection of Watermarks for Large Language Models Under Human Edits Watermarking of large language models, August 2023

Reference 1

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Observation 0cc4e3fe-b4fe-457c-9793-66a78191c8f1 · outbound

This paper cites GPT-4 Technical Report.

Robust Detection of Watermarks for Large Language Models Under Human Edits GPT-4 Technical Report

Reference 2

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Observation c8e05b64-48c4-4409-a0ed-1113449767b3 · outbound

This paper cites A learning algorithm for Boltzmann machines.Cognitive science, 9(1):147–169, 1985.

Robust Detection of Watermarks for Large Language Models Under Human Edits A learning algorithm for Boltzmann machines.Cognitive science, 9(1):147–169, 1985

Reference 3

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Observation dbf6d0db-db85-41eb-8da2-f642170da676 · outbound

This paper cites Distribution-free tests for sparse heterogeneous mixtures.

Robust Detection of Watermarks for Large Language Models Under Human Edits Distribution-free tests for sparse heterogeneous mixtures

Reference 4

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Observation 037c1d3f-3d13-41ad-9e16-959981a8c1b0 · outbound

This paper cites An intensive introduction to cryptography, lectures notes for Harvard CS 127.

Robust Detection of Watermarks for Large Language Models Under Human Edits An intensive introduction to cryptography, lectures notes for Harvard CS 127

Reference 5

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This paper cites On asymptotically optimal non-parametric criteria.Theory of Probability & Its Applications, 13(3):359–393, 1968.

Robust Detection of Watermarks for Large Language Models Under Human Edits On asymptotically optimal non-parametric criteria.Theory of Probability & Its Applications, 13(3):359–393, 1968

Reference 6

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Observation c1477f56-154e-4b37-bb88-6d6513b50114 · outbound

This paper cites Boundary-value problems for random walks and large deviations in function spaces.

Robust Detection of Watermarks for Large Language Models Under Human Edits Boundary-value problems for random walks and large deviations in function spaces

Reference 7

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Observation ba5ea833-5d0c-4062-9d29-aba54c3cf763 · outbound

This paper cites Language models are few-shot learners.

Robust Detection of Watermarks for Large Language Models Under Human Edits Language models are few-shot learners

Reference 8

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This paper cites Optimal detection of sparse mixtures against a given null distribution.

Robust Detection of Watermarks for Large Language Models Under Human Edits Optimal detection of sparse mixtures against a given null distribution

Reference 9

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Observation dc64b4c0-b1fe-4fea-a8dd-d5df73804f65 · outbound

This paper cites Optimal detection of heterogeneous and het- eroscedastic mixtures.

Robust Detection of Watermarks for Large Language Models Under Human Edits Optimal detection of heterogeneous and het- eroscedastic mixtures

Reference 10

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Observation fca63f73-ff70-49a9-a448-af05e687d12c · outbound

This paper cites Towards Better Statistical Understanding of Watermarking LLMs.

Robust Detection of Watermarks for Large Language Models Under Human Edits Towards Better Statistical Understanding of Watermarking LLMs

Reference 11

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Observation bc7b8695-dc10-4a4f-baf0-6d97180d0e8b · outbound

This paper cites Pseudorandom error-correcting codes.

Robust Detection of Watermarks for Large Language Models Under Human Edits Pseudorandom error-correcting codes

Reference 12

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Observation 529071a4-7204-4c45-9932-ae8275db4aa9 · outbound

This paper cites Undetectable watermarks for language models.

Robust Detection of Watermarks for Large Language Models Under Human Edits Undetectable watermarks for language models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.734954Z

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Observation 93402285-67af-488d-bce9-1ee6b539c30c · outbound

This paper cites Routledge, 2017.

Robust Detection of Watermarks for Large Language Models Under Human Edits Routledge, 2017

Reference 14

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Observation 725f85e2-11e9-43e3-85cc-a51b67c11cd2 · outbound

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

Robust Detection of Watermarks for Large Language Models Under Human Edits Scalable watermarking for identifying large language model outputs

Reference 15

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Observation 237d0a29-fc6f-462e-9ffb-97d03e93939a · outbound

This paper cites Cambridge university press, 2023.

Robust Detection of Watermarks for Large Language Models Under Human Edits Cambridge university press, 2023

Reference 16

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Observation e3e39d16-cc05-474c-bb40-b1eeb010a9ec · outbound

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Robust Detection of Watermarks for Large Language Models Under Human Edits Unresolved cited work

Reference 17

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Observation 0d53406b-a04f-4b7c-aeca-b0a9bd96b08c · outbound

This paper cites Higher criticism for detecting sparse heterogeneous mixtures.

Robust Detection of Watermarks for Large Language Models Under Human Edits Higher criticism for detecting sparse heterogeneous mixtures

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.756885Z

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Observation b8d9cc3e-ec4a-498e-afdf-4279c173418e · outbound

This paper cites Higher criticism for large-scale inference, especially for rare and weak effects.Statistical science, 30(1):1–25, 2015.

Robust Detection of Watermarks for Large Language Models Under Human Edits Higher criticism for large-scale inference, especially for rare and weak effects.Statistical science, 30(1):1–25, 2015

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.761622Z

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Observation 3fa17e8c-62e6-4cf4-b6fc-100da799af20 · outbound

This paper cites AI watermarking must be watertight to be effective.Nature, 634:753, 2024.

Robust Detection of Watermarks for Large Language Models Under Human Edits AI watermarking must be watertight to be effective.Nature, 634:753, 2024

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.766982Z

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Observation 14cd6eb6-0c8a-4c84-80eb-97b3401a7d8a · outbound

This paper cites an unresolved cited work.

Robust Detection of Watermarks for Large Language Models Under Human Edits Unresolved cited work

Reference 21

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Observation a27c8e2a-4097-4f19-b1e9-88127978e954 · outbound

This paper cites Three bricks to consolidate watermarks for large language models.

Robust Detection of Watermarks for Large Language Models Under Human Edits Three bricks to consolidate watermarks for large language models

Reference 22

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Observation 4dbf6c08-3081-477a-86f0-c48f10b481db · outbound

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

Robust Detection of Watermarks for Large Language Models Under Human Edits GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.781207Z

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Observation 2e524b93-b9b2-41dd-a95c-7d98d702f378 · outbound

This paper cites WaterMax: breaking the LLM watermark detectability-robustness-quality trade-off.

Robust Detection of Watermarks for Large Language Models Under Human Edits WaterMax: breaking the LLM watermark detectability-robustness-quality trade-off

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.787966Z

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Observation e623d957-fed1-49b3-b005-30d4ca2391ee · outbound

This paper cites Edit Distance Robust Watermarks via Indexing Pseudorandom Codes.

Robust Detection of Watermarks for Large Language Models Under Human Edits Edit Distance Robust Watermarks via Indexing Pseudorandom Codes

Reference 25

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Observation 88871c16-31db-4716-a5f4-a01550e06714 · outbound

This paper cites The intermediates take it all: Asymptotics of higher criticism statistics and a powerful alternative based on equal local levels.

Robust Detection of Watermarks for Large Language Models Under Human Edits The intermediates take it all: Asymptotics of higher criticism statistics and a powerful alternative based on equal local levels

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.798509Z

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Observation 81cba927-0c5d-49de-a9af-54c59b7007b5 · outbound

This paper cites US Government Printing Office, 1948.

Robust Detection of Watermarks for Large Language Models Under Human Edits US Government Printing Office, 1948

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.803949Z

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Observation 77fc24d9-9a69-4cb7-90e8-05ada41fc89f · outbound

This paper cites Properties of higher criticism under strong dependence.The Annals of Statistics, pages 381–402, 2008.

Robust Detection of Watermarks for Large Language Models Under Human Edits Properties of higher criticism under strong dependence.The Annals of Statistics, pages 381–402, 2008

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Observation 681670c1-6c56-48cd-8748-cd9411a95a7a · outbound

This paper cites Innovated higher criticism for detecting sparse signals in correlated noise.

Robust Detection of Watermarks for Large Language Models Under Human Edits Innovated higher criticism for detecting sparse signals in correlated noise

Reference 29

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Observation ed544a97-a28e-4906-aff3-0ce57b716c7f · outbound

This paper cites Convex analysis and minimization algorithms I: Fundamentals, volume 305.

Robust Detection of Watermarks for Large Language Models Under Human Edits Convex analysis and minimization algorithms I: Fundamentals, volume 305

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Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.819625Z

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Observation 28b391f5-683b-404b-adc3-23338b81930a · outbound

This paper cites SemStamp: A semantic watermark with paraphrastic robustness for text generation.

Robust Detection of Watermarks for Large Language Models Under Human Edits SemStamp: A semantic watermark with paraphrastic robustness for text generation

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Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.824545Z

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Observation 210a1a18-996d-4da9-bc46-328a3ea53da2 · outbound

This paper cites Unbiased watermark for large language models.

Robust Detection of Watermarks for Large Language Models Under Human Edits Unbiased watermark for large language models

Reference 32

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Observation d8c8db07-220b-493e-8b5c-32accc6254df · outbound

This paper cites Towards Optimal Statistical Watermarking.

Robust Detection of Watermarks for Large Language Models Under Human Edits Towards Optimal Statistical Watermarking

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Observation 8d029b77-f436-49f0-97c3-e43bf67a8c7c · outbound

This paper cites Robust estimation of a location parameter.

Robust Detection of Watermarks for Large Language Models Under Human Edits Robust estimation of a location parameter

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Observation aa4a55a1-51f2-400d-9c9c-bd2df7d7e5a4 · outbound

This paper cites John Wiley & Sons, 2011.

Robust Detection of Watermarks for Large Language Models Under Human Edits John Wiley & Sons, 2011

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Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.845399Z

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Observation 0f2f4044-7916-42fa-b625-3fcaadd6f288 · outbound

This paper cites Some problems of hypothesis testing leading to infinitely divisible distributions.

Robust Detection of Watermarks for Large Language Models Under Human Edits Some problems of hypothesis testing leading to infinitely divisible distributions

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.850874Z

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Observation 8d6c913a-06b1-4716-b7ff-38c9a0b1b03e · outbound

This paper cites Goodness-of-fit tests via phi-divergences.Annals of Statistics, 35(5):2018–2053, 2007.

Robust Detection of Watermarks for Large Language Models Under Human Edits Goodness-of-fit tests via phi-divergences.Annals of Statistics, 35(5):2018–2053, 2007

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Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.855553Z

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Observation a1e26ec0-c00d-4ded-9ed4-7c30c86ba1a0 · outbound

This paper cites Categorical reparameterization with Gumbel-Softmax.

Robust Detection of Watermarks for Large Language Models Under Human Edits Categorical reparameterization with Gumbel-Softmax

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Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.860176Z

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Observation 956e339e-abc5-4a4e-93e0-30c93dc50cf1 · outbound

This paper cites Rare and weak effects in large-scale inference: Methods and phase diagrams.

Robust Detection of Watermarks for Large Language Models Under Human Edits Rare and weak effects in large-scale inference: Methods and phase diagrams

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Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.864733Z

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Observation b73208d8-4b0d-43bc-9bb7-d27eb403dd6d · outbound

This paper cites Optimal adaptivity of signed-polygon statistics for network testing.The Annals of Statistics, 49(6):3408–3433, 2021.

Robust Detection of Watermarks for Large Language Models Under Human Edits Optimal adaptivity of signed-polygon statistics for network testing.The Annals of Statistics, 49(6):3408–3433, 2021

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Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.869471Z

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Observation 13c32de8-c97d-467e-a245-24d19d15c3e0 · outbound

This paper cites Covariance assisted screening and estimation.Annals of statistics, 42(6):2202, 2014.

Robust Detection of Watermarks for Large Language Models Under Human Edits Covariance assisted screening and estimation.Annals of statistics, 42(6):2202, 2014

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Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.874373Z

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Observation 2cfb38cb-a6c1-4209-9864-44c3dc031286 · outbound

This paper cites Martingale approach in the theory of goodness-of-fit tests.Theory of Probability & Its Applications, 26(2):240–257, 1982.

Robust Detection of Watermarks for Large Language Models Under Human Edits Martingale approach in the theory of goodness-of-fit tests.Theory of Probability & Its Applications, 26(2):240–257, 1982

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.879388Z

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Observation c2839de3-7e41-4e0b-9612-4c0b7220aea1 · outbound

This paper cites A watermark for large language models.

Robust Detection of Watermarks for Large Language Models Under Human Edits A watermark for large language models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.884577Z

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Observation 13bf99fb-c593-4c6c-8619-3ef06aa0b008 · outbound

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

Robust Detection of Watermarks for Large Language Models Under Human Edits On the reliability of watermarks for large language models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.890604Z

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Observation 2f1f0e6e-25f1-4cb3-aede-15d5e29f948b · outbound

This paper cites Robust distortion- free watermarks for language models.Transactions on Machine Learning Research, 2024.

Robust Detection of Watermarks for Large Language Models Under Human Edits Robust distortion- free watermarks for language models.Transactions on Machine Learning Research, 2024

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.696338Z

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Observation 1d0f3851-e5bb-4b5c-9705-3a697ff6b899 · outbound

This paper cites Higher criticism: p-values and criticism.The Annals of Statistics, 43(3):1323–1350, 2015.

Robust Detection of Watermarks for Large Language Models Under Human Edits Higher criticism: p-values and criticism.The Annals of Statistics, 43(3):1323–1350, 2015

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.681543Z

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Observation bbfe86ca-1369-4381-803d-6d92b3e4b948 · outbound

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Robust Detection of Watermarks for Large Language Models Under Human Edits Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:55:33.666700Z

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Observation 56bdf370-2500-4abd-92ae-865b571780cc · outbound

This paper cites A semantic invariant robust watermark for large language models.

Robust Detection of Watermarks for Large Language Models Under Human Edits A semantic invariant robust watermark for large language models

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.652129Z

Source-reported events for the cited work

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Observation 9b871df8-3bcf-4451-bb60-b3f9aa6ce12f · outbound

This paper cites Adaptive text watermark for large language models.

Robust Detection of Watermarks for Large Language Models Under Human Edits Adaptive text watermark for large language models

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.622518Z

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Observation cb3b469a-4b28-494b-863c-4d810bb124cb · outbound

This paper cites an unresolved cited work.

Robust Detection of Watermarks for Large Language Models Under Human Edits Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:55:33.637401Z

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Observation dce4bd95-8b3b-4735-bb05-8ff64eaf17b4 · outbound

This paper cites Large language models challenge the future of higher education.Nature Machine Intelligence, 5(4):333–334, 2023.

Robust Detection of Watermarks for Large Language Models Under Human Edits Large language models challenge the future of higher education.Nature Machine Intelligence, 5(4):333–334, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.590154Z

Source-reported events for the cited work

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Observation 1ca622e0-7ce9-44bb-888a-8375c76f8315 · outbound

This paper cites A* sampling.

Robust Detection of Watermarks for Large Language Models Under Human Edits A* sampling

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.605805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 911931af-685b-4911-9e87-42faf7c55515 · outbound

This paper cites Fast calculation of p-values for one-sided Kolmogorov-Smirnov type statistics.

Robust Detection of Watermarks for Large Language Models Under Human Edits Fast calculation of p-values for one-sided Kolmogorov-Smirnov type statistics

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.559189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2c7b8abb-ff7c-4e6e-bc2c-d8999783a581 · outbound

This paper cites WordNet: A lexical database for English.Communications of the ACM, 38 (11):39–41, 1995.

Robust Detection of Watermarks for Large Language Models Under Human Edits WordNet: A lexical database for English.Communications of the ACM, 38 (11):39–41, 1995

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.575118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d903ce7d-9318-4447-a09e-f86f6dc10368 · outbound

This paper cites Hodges-Lehmann asymptotic efficiency of the Kolmogorov and Smirnov goodness- of-fit tests.

Robust Detection of Watermarks for Large Language Models Under Human Edits Hodges-Lehmann asymptotic efficiency of the Kolmogorov and Smirnov goodness- of-fit tests

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.527350Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 30f5559a-149a-4349-9f4f-0b22cc2860b6 · outbound

This paper cites Cambridge University Press, 1995.

Robust Detection of Watermarks for Large Language Models Under Human Edits Cambridge University Press, 1995

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.542342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bc63a8ab-1582-44c0-bcb0-9faf56867684 · outbound

This paper cites Understanding the source of what we see and hear online, May 2024.

Robust Detection of Watermarks for Large Language Models Under Human Edits Understanding the source of what we see and hear online, May 2024

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.511131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation abcf3d72-33fd-414a-87eb-5e236b72622a · outbound

This paper cites ChatGPT: Optimizing language models for dialogue, Jan 2023.

Robust Detection of Watermarks for Large Language Models Under Human Edits ChatGPT: Optimizing language models for dialogue, Jan 2023

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.966203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation efd5ce1c-5895-4ac1-ae9e-34adf74d8da0 · outbound

This paper cites Mark My Words: Analyzing and Evaluating Language Model Watermarks.

Robust Detection of Watermarks for Large Language Models Under Human Edits Mark My Words: Analyzing and Evaluating Language Model Watermarks

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.984013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d15dc141-e1d3-43fd-992e-80ab1fa160db · outbound

This paper cites Perturb-and-map random fields: Using discrete opti- mization to learn and sample from energy models.

Robust Detection of Watermarks for Large Language Models Under Human Edits Perturb-and-map random fields: Using discrete opti- mization to learn and sample from energy models

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.495537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0ee2fc4c-f484-4e0d-acb6-f0930b618ba0 · outbound

This paper cites Language models are unsupervised multitask learners.OpenAI blog, 1(8):9, 2019.

Robust Detection of Watermarks for Large Language Models Under Human Edits Language models are unsupervised multitask learners.OpenAI blog, 1(8):9, 2019

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:31.994245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0a68f08-37eb-46fb-8485-5d0b2391fd64 · outbound

This paper cites Large deviations and bahadur efficiency of the Khmaladze-Aki statistic.

Robust Detection of Watermarks for Large Language Models Under Human Edits Large deviations and bahadur efficiency of the Khmaladze-Aki statistic

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.479317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation eb790900-6595-4f00-bff6-71b917f0fb8d · outbound

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

Robust Detection of Watermarks for Large Language Models Under Human Edits Exploring the limits of transfer learning with a unified text-to-text transformer

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:32.004984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 780a45e9-14b7-4f4f-bc0a-b0b40326cc0d · outbound

This paper cites Robust speech recognition via large-scale weak supervision.

Robust Detection of Watermarks for Large Language Models Under Human Edits Robust speech recognition via large-scale weak supervision

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.453561Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 14eb2008-2034-4b55-9b63-ec5352b6d62c · outbound

This paper cites A robust semantics-based watermark for large language model against paraphrasing.

Robust Detection of Watermarks for Large Language Models Under Human Edits A robust semantics-based watermark for large language model against paraphrasing

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.414450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6f550a15-b3c9-4976-a1f3-9b999f20c4fa · outbound

This paper cites Efficient estimates and optimum inference procedures in large samples.

Robust Detection of Watermarks for Large Language Models Under Human Edits Efficient estimates and optimum inference procedures in large samples

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.429253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 12238a51-4b1f-4a53-ab71-6df1c8ac79f8 · outbound

This paper cites The Curse of Recursion: Training on Generated Data Makes Models Forget.

Robust Detection of Watermarks for Large Language Models Under Human Edits The Curse of Recursion: Training on Generated Data Makes Models Forget

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:32.026605Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e62f8b12-ea0c-4663-9f50-67736067389c · outbound

This paper cites Applied Cryptography.

Robust Detection of Watermarks for Large Language Models Under Human Edits Applied Cryptography

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.398140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 81f8e701-f59e-43f9-b5b6-5e99b313ada0 · outbound

This paper cites AI bot ChatGPT writes smart essays—Should professors worry?Nature News, 2022.

Robust Detection of Watermarks for Large Language Models Under Human Edits AI bot ChatGPT writes smart essays—Should professors worry?Nature News, 2022

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.367164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 40692250-a9a5-48c7-a1c4-a0b5e0aa29b3 · outbound

This paper cites Disinformation’s spread: Bots, trolls and all of us.Nature, 571(7766):449–450, 2019.

Robust Detection of Watermarks for Large Language Models Under Human Edits Disinformation’s spread: Bots, trolls and all of us.Nature, 571(7766):449–450, 2019

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.382883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 47ddc336-dcaa-41af-8b2a-357018af270a · outbound

This paper cites Ethical and social risks of harm from Language Models.

Robust Detection of Watermarks for Large Language Models Under Human Edits Ethical and social risks of harm from Language Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:32.046245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9ee4196-f124-4927-9401-f462f9a207fb · outbound

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

Robust Detection of Watermarks for Large Language Models Under Human Edits LLaMA: Open and Efficient Foundation Language Models

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:32.041407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46e598f2-a26d-4646-b990-ac42db85aa97 · outbound

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

Robust Detection of Watermarks for Large Language Models Under Human Edits A Resilient and Accessible Distribution-Preserving Watermark for Large Language Models

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:32.055885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50edc2ac-5960-48f1-a09d-b4d5f4883443 · outbound

This paper cites A note on the asymptotic distribution of Berk—Jones type statistics under the null hypothesis.

Robust Detection of Watermarks for Large Language Models Under Human Edits A note on the asymptotic distribution of Berk—Jones type statistics under the null hypothesis

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.351425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0713530e-7e5b-41cb-83ea-3f2f851da90f · outbound

This paper cites Debiasing Watermarks for Large Language Models via Maximal Coupling.

Robust Detection of Watermarks for Large Language Models Under Human Edits Debiasing Watermarks for Large Language Models via Maximal Coupling

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:32.065124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aca2aba6-e9a5-44a9-96f9-7b89257ff7e1 · outbound

This paper cites Sheared LLaMA: Accelerating language model pre-training via structured pruning.

Robust Detection of Watermarks for Large Language Models Under Human Edits Sheared LLaMA: Accelerating language model pre-training via structured pruning

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.336349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a9f7f41c-289e-4bc4-a66e-714d7132875d · outbound

This paper cites Defending against neural fake news.

Robust Detection of Watermarks for Large Language Models Under Human Edits Defending against neural fake news

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.304956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b610c28a-852a-46ba-a762-137b1db2dac6 · outbound

This paper cites Robust multi-bit natural lan- guage watermarking through invariant features.

Robust Detection of Watermarks for Large Language Models Under Human Edits Robust multi-bit natural lan- guage watermarking through invariant features

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.320571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e7ff5082-14d5-46ac-88bd-2e9699b4af1a · outbound

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

Robust Detection of Watermarks for Large Language Models Under Human Edits Provable robust watermarking for AI-generated text

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.288187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 53598216-678c-429b-8ca6-1a2ae9dfb396 · outbound

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

Robust Detection of Watermarks for Large Language Models Under Human Edits OPT: Open Pre-trained Transformer Language Models

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:32.079268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a31c7156-eebb-4c3a-866b-ee6e65932952 · outbound

This paper cites Duwak: Dual watermarks in large language models.

Robust Detection of Watermarks for Large Language Models Under Human Edits Duwak: Dual watermarks in large language models

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.255835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 4c246e1f-985b-44bf-af32-08068f2dc601 · outbound

This paper cites an unresolved cited work.

Robust Detection of Watermarks for Large Language Models Under Human Edits Unresolved cited work

Reference 82

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:55:33.271434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2ad8d7cf-6bc5-4013-ab83-8dccf69afa8a · outbound

This paper cites Permute-and-Flip: An optimally stable and watermarkable decoder for LLMs.

Robust Detection of Watermarks for Large Language Models Under Human Edits Permute-and-Flip: An optimally stable and watermarkable decoder for LLMs

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-12T15:55:32.094602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f967c7db-47cb-47c6-bbc1-4e3e352fa228 · outbound

This paper cites Human behavior and the principle of least effort: An introduction to human ecology.

Robust Detection of Watermarks for Large Language Models Under Human Edits Human behavior and the principle of least effort: An introduction to human ecology

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.240816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation abb97b22-eca2-4f3c-aa41-0ad9e56902eb · outbound

This paper cites an unresolved cited work.

Robust Detection of Watermarks for Large Language Models Under Human Edits Unresolved cited work

Reference 86

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:55:33.225004Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9f604c8c-64b1-4eca-a064-f28a0e861bfd · outbound

This paper cites , Yt−1] be the conditional version ofµ1,Pt given the history information Y1,.

Robust Detection of Watermarks for Large Language Models Under Human Edits , Yt−1] be the conditional version ofµ1,Pt given the history information Y1,

Reference 87

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.207559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bb9b8713-d01c-4284-8190-595bb815be94 · outbound

This paper cites By the last inequality, (14), and (13), it follows that H 2(ρ0, ρ1) ≤ 1 − nY t=1 1 − sup Pt∈P H 2(µ0, (1 − εn)µ0 + εnµ1,Pt).

Robust Detection of Watermarks for Large Language Models Under Human Edits By the last inequality, (14), and (13), it follows that H 2(ρ0, ρ1) ≤ 1 − nY t=1 1 − sup Pt∈P H 2(µ0, (1 − εn)µ0 + εnµ1,Pt)

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.190029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c968cf93-a7e6-4eb0-b793-87df135875eb · outbound

This paper cites E1 " nY t=1 1Yt∈At|Gn−1 ## = E1.

Robust Detection of Watermarks for Large Language Models Under Human Edits E1 " nY t=1 1Yt∈At|Gn−1 ## = E1

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.174348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation da4bd56f-032a-4330-af15-8b55fb5372bc · outbound

This paper cites Hence, for any test, the sum of Type I and Type II errors tends to 1 asn → ∞.

Robust Detection of Watermarks for Large Language Models Under Human Edits Hence, for any test, the sum of Type I and Type II errors tends to 1 asn → ∞

Reference 90

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.159570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 86ebb938-a042-4c71-9375-91450f9191fb · outbound

This paper cites Furthermore, for the likelihood-ratio test that rejectsH0 if the log-likelihood ratio is positive, the sum of Type I and Type II errors tends to 0 asn → ∞.

Robust Detection of Watermarks for Large Language Models Under Human Edits Furthermore, for the likelihood-ratio test that rejectsH0 if the log-likelihood ratio is positive, the sum of Type I and Type II errors tends to 0 asn → ∞

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.144786Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f77856e0-b847-47fc-b233-9e5aa93f78e1 · outbound

This paper cites Then, H 2(µ0, 1 − εn + εnµ1,Pt) = Θ(1) · ε2 n · E0(f1,Pt(Y ) − 1)2.

Robust Detection of Watermarks for Large Language Models Under Human Edits Then, H 2(µ0, 1 − εn + εnµ1,Pt) = Θ(1) · ε2 n · E0(f1,Pt(Y ) − 1)2

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.129559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3204893d-a19e-42e1-99e8-9dab27616f1f · outbound

This paper cites an unresolved cited work.

Robust Detection of Watermarks for Large Language Models Under Human Edits Unresolved cited work

Reference 93

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:55:33.113827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3f014848-5365-4281-b4b8-fe1a97fe67bf · outbound

This paper cites By Lemma A.1, it suffices to show nX t=1 sup Pt∈P c ∆n H 2(µ0, (1 − εn)µ0 + εnµ1,Pt) → 0.

Robust Detection of Watermarks for Large Language Models Under Human Edits By Lemma A.1, it suffices to show nX t=1 sup Pt∈P c ∆n H 2(µ0, (1 − εn)µ0 + εnµ1,Pt) → 0

Reference 94

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.097816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0732f40e-beb2-4fe4-94d5-d0bc9930da2a · outbound

This paper cites Lemma A.5.

Robust Detection of Watermarks for Large Language Models Under Human Edits Lemma A.5

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.079002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c43b2854-4f79-4645-8a21-9ac3ed99ce33 · outbound

This paper cites an unresolved cited work.

Robust Detection of Watermarks for Large Language Models Under Human Edits Unresolved cited work

Reference 96

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:55:33.062718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 73110600-e671-4064-ac66-2a5e2d1ce263 · outbound

This paper cites an unresolved cited work.

Robust Detection of Watermarks for Large Language Models Under Human Edits Unresolved cited work

Reference 97

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:55:33.046790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a800174d-b6d7-4f54-b0d7-e8ba77816e19 · outbound

This paper cites (22) 38 For any givenδ >0, we would rejectH0 if HC+ n ≥ p 2(1 + δ) log logn.

Robust Detection of Watermarks for Large Language Models Under Human Edits (22) 38 For any givenδ >0, we would rejectH0 if HC+ n ≥ p 2(1 + δ) log logn

Reference 98

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T15:55:33.031924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation febb15fb-4864-4b6b-aa8d-52ffbfb56648 · outbound

This paper cites As a result, Tr-GoF can asymptotically distinguish between H0 and H mix 1.

Robust Detection of Watermarks for Large Language Models Under Human Edits As a result, Tr-GoF can asymptotically distinguish between H0 and H mix 1

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:33.012973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 85b667a1-9f9f-4981-b802-7c910100d4da · outbound

This paper cites Proof of Lemma A.11.If u < v, K+ s (u, v) = 0; thus, all the inequalities follow directly.

Robust Detection of Watermarks for Large Language Models Under Human Edits Proof of Lemma A.11.If u < v, K+ s (u, v) = 0; thus, all the inequalities follow directly

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:32.990623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 689bd7db-078c-4dee-b17a-25ae2e673998 · outbound

This paper cites (31) Given v ≤ u and s ≤ 2, it follows that −(1 − v) 1 − v u 2−s ≤ v(1 − v)Ds(u⋆, v) − 1 ≤ v " 1 − v 1 − u 2−s − 1 #.

Robust Detection of Watermarks for Large Language Models Under Human Edits (31) Given v ≤ u and s ≤ 2, it follows that −(1 − v) 1 − v u 2−s ≤ v(1 − v)Ds(u⋆, v) − 1 ≤ v " 1 − v 1 − u 2−s − 1 #

Reference 101

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:55:32.972729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers