Membership Inference Attacks on Tokenizers of Large Language Models | Paper Citation Record

Observation 89ca683b-9c28-46d2-b144-17a72af8f5ff · outbound

This paper cites Deep learning with differential privacy.

Membership Inference Attacks on Tokenizers of Large Language Models Deep learning with differential privacy

Reference 1

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Observation 3cc7c33f-5f83-47a8-96a9-6f0b7ca7df56 · outbound

This paper cites An information-theoretic perspective of tf–idf measures.Information Processing & Manage- ment, 39(1):45–65, 2003.

Membership Inference Attacks on Tokenizers of Large Language Models An information-theoretic perspective of tf–idf measures.Information Processing & Manage- ment, 39(1):45–65, 2003

Reference 2

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Observation 6ec36006-0b10-487b-a845-c462faa331b5 · outbound

This paper cites Judge allows new york times copyright lawsuit to go forward.

Membership Inference Attacks on Tokenizers of Large Language Models Judge allows new york times copyright lawsuit to go forward

Reference 3

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Observation 10c4a399-da1b-4a44-b4dc-e08208547665 · outbound

This paper cites Tokenizer for anthropic large language models.

Membership Inference Attacks on Tokenizers of Large Language Models Tokenizer for anthropic large language models

Reference 4

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Observation c03111da-bd68-4471-b239-a205630f5cda · outbound

This paper cites Claude opus 4 & claude sonnet 4.

Membership Inference Attacks on Tokenizers of Large Language Models Claude opus 4 & claude sonnet 4

Reference 5

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Observation 13c85151-3bc7-475a-b9ec-23eb93fc1a04 · outbound

This paper cites An efficient recommendation generation us- ing relevant jaccard similarity.Information Sciences, 483:53–64, 2019.

Membership Inference Attacks on Tokenizers of Large Language Models An efficient recommendation generation us- ing relevant jaccard similarity.Information Sciences, 483:53–64, 2019

Reference 6

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Observation 9e6aa735-4fed-4836-b236-4946d666d47e · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

Membership Inference Attacks on Tokenizers of Large Language Models DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 7

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Observation a65b57f8-2800-4351-bfa6-d8649e7593aa · outbound

This paper cites Pythia: A suite for analyzing large language models across train- ing and scaling.

Membership Inference Attacks on Tokenizers of Large Language Models Pythia: A suite for analyzing large language models across train- ing and scaling

Reference 8

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Observation 414d1b89-c345-4fd5-af62-d423de99ebe4 · outbound

This paper cites Gpt- neox-20b: An open-source autoregressive language model.Challenges & Perspectives in Creating Large Language Models, page 95, 2022.

Membership Inference Attacks on Tokenizers of Large Language Models Gpt- neox-20b: An open-source autoregressive language model.Challenges & Perspectives in Creating Large Language Models, page 95, 2022

Reference 9

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Observation 2f6d474c-fcd8-4d0f-9c32-015dcfb26820 · outbound

This paper cites Language models are few-shot learners.

Membership Inference Attacks on Tokenizers of Large Language Models Language models are few-shot learners

Reference 10

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Observation 098d1c8e-010d-4e15-b630-b9943137dbcf · outbound

This paper cites Member- ship inference attacks from first principles.

Membership Inference Attacks on Tokenizers of Large Language Models Member- ship inference attacks from first principles

Reference 11

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Observation 803170ef-c58f-4191-a968-bc6846138641 · outbound

This paper cites Extracting training data from large lan- guage models.

Membership Inference Attacks on Tokenizers of Large Language Models Extracting training data from large lan- guage models

Reference 12

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Observation 12b3022d-df34-4093-bfe0-f84599291d54 · outbound

This paper cites an unresolved cited work.

Membership Inference Attacks on Tokenizers of Large Language Models Unresolved cited work

Reference 13

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Observation ec55dba2-a01f-4865-bf65-1683e959af23 · outbound

This paper cites Evaluating the Dynamics of Membership Privacy in Deep Learning.

Membership Inference Attacks on Tokenizers of Large Language Models Evaluating the Dynamics of Membership Privacy in Deep Learning

Reference 14

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Observation 9234e720-7ce7-4196-ad70-afc777453ef6 · outbound

This paper cites How contaminated is your benchmark? measuring dataset leakage in large language models with kernel divergence.

Membership Inference Attacks on Tokenizers of Large Language Models How contaminated is your benchmark? measuring dataset leakage in large language models with kernel divergence

Reference 15

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Observation 6149220c-deb4-4710-b6dd-8384bb28e7d2 · outbound

This paper cites Label-only membership inference attacks.

Membership Inference Attacks on Tokenizers of Large Language Models Label-only membership inference attacks

Reference 16

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Observation 4eebd633-09a4-4821-a45d-6414e311e49b · outbound

This paper cites Power-law distributions in empirical data.

Membership Inference Attacks on Tokenizers of Large Language Models Power-law distributions in empirical data

Reference 17

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Observation e0a29057-cc14-4b30-995e-1b10e1a08329 · outbound

This paper cites an unresolved cited work.

Membership Inference Attacks on Tokenizers of Large Language Models Unresolved cited work

Reference 18

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Observation c1d21558-101f-4025-a1e0-a8ebbba5cea8 · outbound

This paper cites Getting the most out of your tokenizer for pre- training and domain adaptation.

Membership Inference Attacks on Tokenizers of Large Language Models Getting the most out of your tokenizer for pre- training and domain adaptation

Reference 19

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Observation 4bffe1b0-a320-48f4-a8f1-836002e189f3 · outbound

This paper cites Blind baselines beat membership inference attacks for foun- dation models.

Membership Inference Attacks on Tokenizers of Large Language Models Blind baselines beat membership inference attacks for foun- dation models

Reference 20

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Observation c4d2d478-1ac0-4395-a50d-f899d4dec326 · outbound

This paper cites Bert: Pre-training of deep bidi- rectional transformers for language understanding.

Membership Inference Attacks on Tokenizers of Large Language Models Bert: Pre-training of deep bidi- rectional transformers for language understanding

Reference 21

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Observation cb1496d5-0a47-4cfe-86f0-5cad142922ec · outbound

This paper cites Dp-forward: Fine-tuning and inference on language models with differential privacy in forward pass.

Membership Inference Attacks on Tokenizers of Large Language Models Dp-forward: Fine-tuning and inference on language models with differential privacy in forward pass

Reference 22

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Observation 30892f90-a83a-4d54-843e-b54ff8c7d596 · outbound

This paper cites Cascading and Proxy Membership Infer- ence Attacks.

Membership Inference Attacks on Tokenizers of Large Language Models Cascading and Proxy Membership Infer- ence Attacks

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T11:23:12.002596Z

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Observation 8fc3d85b-3406-48db-8572-b56659f47b96 · outbound

This paper cites Systematic Assessment of Tabular Data Synthesis.

Membership Inference Attacks on Tokenizers of Large Language Models Systematic Assessment of Tabular Data Synthesis

Reference 24

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Observation 685a4178-e04e-4c8f-9717-d50a35ac99ff · outbound

This paper cites Do membership inference attacks work on large language models? InFirst Conference on Lan- guage Modeling, 2024.

Membership Inference Attacks on Tokenizers of Large Language Models Do membership inference attacks work on large language models? InFirst Conference on Lan- guage Modeling, 2024

Reference 25

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Observation 720d92b9-6782-4471-8692-a3be8a943d0e · outbound

This paper cites De-cop: detecting copyrighted content in language models training data.

Membership Inference Attacks on Tokenizers of Large Language Models De-cop: detecting copyrighted content in language models training data

Reference 26

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Observation 227687d3-f9dd-40d6-bdb9-a6746c42256e · outbound

This paper cites Differential privacy.

Membership Inference Attacks on Tokenizers of Large Language Models Differential privacy

Reference 27

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Observation 67d56b7d-f175-4eee-9a24-7cfb1ef9743f · outbound

This paper cites Analysis of sparse bayesian learning.Advances in neural information processing systems, 14, 2001.

Membership Inference Attacks on Tokenizers of Large Language Models Analysis of sparse bayesian learning.Advances in neural information processing systems, 14, 2001

Reference 28

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Observation d2e8c732-49f8-4da3-9e9f-3c812b3b3b0f · outbound

This paper cites Privacy in pharmacogenetics: An {End-to-End} case study of personalized warfarin dosing.

Membership Inference Attacks on Tokenizers of Large Language Models Privacy in pharmacogenetics: An {End-to-End} case study of personalized warfarin dosing

Reference 29

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Observation 780ceb07-6693-4b17-9a11-b34a1e5b28bd · outbound

This paper cites Label inference attacks against vertical federated learning.

Membership Inference Attacks on Tokenizers of Large Language Models Label inference attacks against vertical federated learning

Reference 30

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Observation 092847cd-3848-48da-80c5-910353f0d4cc · outbound

This paper cites Zipf’s law and the growth of cities.

Membership Inference Attacks on Tokenizers of Large Language Models Zipf’s law and the growth of cities

Reference 31

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Observation f3b2c762-26a8-472b-a9f1-1f29ca244880 · outbound

This paper cites Investigating the effectiveness of bpe: The power of shorter sequences.

Membership Inference Attacks on Tokenizers of Large Language Models Investigating the effectiveness of bpe: The power of shorter sequences

Reference 32

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Observation faae467b-149c-4f95-a9fd-77ea20f46e57 · outbound

This paper cites Counting gemini text tokens locally with the vertex ai sdk, July 2024.

Membership Inference Attacks on Tokenizers of Large Language Models Counting gemini text tokens locally with the vertex ai sdk, July 2024

Reference 33

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Observation f8f08380-5760-45e7-beb1-de4c609416bc · outbound

This paper cites Likelihood-based diffusion language models.Ad- vances in Neural Information Processing Systems, 36:16693–16715, 2023.

Membership Inference Attacks on Tokenizers of Large Language Models Likelihood-based diffusion language models.Ad- vances in Neural Information Processing Systems, 36:16693–16715, 2023

Reference 34

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Observation 67ad8c75-cd09-42f4-ac54-8e01f62f6e3a · outbound

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

Membership Inference Attacks on Tokenizers of Large Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 35

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Observation 6e9ced76-0fb6-4eb2-ad8c-84b82d1e6ba1 · outbound

This paper cites Weird gpt-4 behavior for “davidjl”.

Membership Inference Attacks on Tokenizers of Large Language Models Weird gpt-4 behavior for “davidjl”

Reference 36

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Observation 7ac65f64-94ce-4f18-9d6f-64dcc68ccc30 · outbound

This paper cites Data mixture inference attack: Bpe tokenizers reveal training data compositions.Advances in Neural Information Processing Systems, 37:8956– 8983, 2024.

Membership Inference Attacks on Tokenizers of Large Language Models Data mixture inference attack: Bpe tokenizers reveal training data compositions.Advances in Neural Information Processing Systems, 37:8956– 8983, 2024

Reference 37

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Observation 22c71755-5ae2-442b-8be2-015103f505d2 · outbound

This paper cites Data mixture inference attack: Bpe tokenizers reveal training data compositions.

Membership Inference Attacks on Tokenizers of Large Language Models Data mixture inference attack: Bpe tokenizers reveal training data compositions

Reference 38

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Observation a866abed-7977-441a-92de-32ce83a00e20 · outbound

This paper cites Strong membership inference attacks on massive datasets and (moderately) large language models.arXiv preprint arXiv:2505.18773, 2025.

Membership Inference Attacks on Tokenizers of Large Language Models Strong membership inference attacks on massive datasets and (moderately) large language models.arXiv preprint arXiv:2505.18773, 2025

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T11:23:14.044399Z

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Observation e39349ed-285e-4f0b-a714-160e52d70c93 · outbound

This paper cites Deep residual learning for image recognition.

Membership Inference Attacks on Tokenizers of Large Language Models Deep residual learning for image recognition

Reference 40

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Observation 7a66f518-0e33-450b-8fcd-5e29b7c89e84 · outbound

This paper cites To- wards label-only membership inference attack against pre-trained large language models.

Membership Inference Attacks on Tokenizers of Large Language Models To- wards label-only membership inference attack against pre-trained large language models

Reference 41

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Observation da5416fe-9973-4fc6-b64e-e5260c2393a5 · outbound

This paper cites Membership inference attacks against vision-language models.

Membership Inference Attacks on Tokenizers of Large Language Models Membership inference attacks against vision-language models

Reference 42

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Observation db2e21bf-a47c-40d9-8aa7-39213b4fe42f · outbound

This paper cites Scaling Laws for Autoregressive Generative Modeling.

Membership Inference Attacks on Tokenizers of Large Language Models Scaling Laws for Autoregressive Generative Modeling

Reference 43

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Observation 42950e4d-d92d-4c75-b40f-e824e7696a2c · outbound

This paper cites Training Compute-Optimal Large Language Models.

Membership Inference Attacks on Tokenizers of Large Language Models Training Compute-Optimal Large Language Models

Reference 44

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Observation 0ae86809-87e4-450e-94bf-11e5cae853c7 · outbound

This paper cites Damia: Leveraging domain adaptation as a defense against membership inference attacks.IEEE Transactions on Dependable and Secure Computing, 19(5):3183–3199, 2021.

Membership Inference Attacks on Tokenizers of Large Language Models Damia: Leveraging domain adaptation as a defense against membership inference attacks.IEEE Transactions on Dependable and Secure Computing, 19(5):3183–3199, 2021

Reference 45

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Observation 2c985725-1bba-4182-8cab-403ad9c905a1 · outbound

This paper cites Over-tokenized trans- former: V ocabulary is generally worth scaling.

Membership Inference Attacks on Tokenizers of Large Language Models Over-tokenized trans- former: V ocabulary is generally worth scaling

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-04T11:23:15.054019Z

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Observation f0bc3db2-a78a-4178-b27e-a952fae1a53a · outbound

This paper cites Efficient reasoning for large reasoning language models via certainty-guided reflec- tion suppression.arXiv preprint arXiv:2508.05337, 2025.

Membership Inference Attacks on Tokenizers of Large Language Models Efficient reasoning for large reasoning language models via certainty-guided reflec- tion suppression.arXiv preprint arXiv:2508.05337, 2025

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-04T11:23:15.166718Z

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Observation 8eb61202-b734-4db2-9f5d-171715e968be · outbound

This paper cites Tokenizer.

Membership Inference Attacks on Tokenizers of Large Language Models Tokenizer

Reference 48

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Observation e2893360-396c-4497-a880-4c6c1d9767cc · outbound

This paper cites Codeparrot github code dataset.

Membership Inference Attacks on Tokenizers of Large Language Models Codeparrot github code dataset

Reference 49

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Observation d1b47ce6-aa7c-4ca6-a79c-7922e1016dcf · outbound

This paper cites Practical blind membership inference attack via differential compar- isons.

Membership Inference Attacks on Tokenizers of Large Language Models Practical blind membership inference attack via differential compar- isons

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-04T11:23:15.413438Z

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Observation a3ed5296-d8e7-4df0-8f14-c6f16d8cddc0 · outbound

This paper cites Memguard: Defend- ing against black-box membership inference attacks via adversarial examples.

Membership Inference Attacks on Tokenizers of Large Language Models Memguard: Defend- ing against black-box membership inference attacks via adversarial examples

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-04T11:23:15.501799Z

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Observation 8af5eba4-a178-440e-8c0e-38cef2378ecb · outbound

This paper cites Scaling Laws for Neural Language Models.

Membership Inference Attacks on Tokenizers of Large Language Models Scaling Laws for Neural Language Models

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-04T11:23:15.608484Z

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Observation 279d3227-3f6e-4198-8176-d1b049242167 · outbound

This paper cites Stolen memories: Leveraging model memorization for calibrated{White- Box} membership inference.

Membership Inference Attacks on Tokenizers of Large Language Models Stolen memories: Leveraging model memorization for calibrated{White- Box} membership inference

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-04T11:23:15.700474Z

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Observation 76a9f61f-abd6-44ab-9944-6bcc8ebd7a64 · outbound

This paper cites Se- qmia: sequential-metric based membership inference attack.

Membership Inference Attacks on Tokenizers of Large Language Models Se- qmia: sequential-metric based membership inference attack

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-04T11:23:15.769015Z

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Observation 5ef775ed-58c5-498f-9a6d-baa0e9342e2c · outbound

This paper cites Enhanced label-only membership inference attacks with fewer queries.

Membership Inference Attacks on Tokenizers of Large Language Models Enhanced label-only membership inference attacks with fewer queries

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-04T11:23:15.884237Z

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Observation 21eed840-cee6-4aec-8338-bdc8e24887a4 · outbound

This paper cites Mem- bership inference attacks and defenses in classification models.

Membership Inference Attacks on Tokenizers of Large Language Models Mem- bership inference attacks and defenses in classification models

Reference 56

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Observation bdb8a7d8-0346-4082-ab60-e33047b1b90b · outbound

This paper cites Large Language Models Can Be Strong Differentially Private Learners.

Membership Inference Attacks on Tokenizers of Large Language Models Large Language Models Can Be Strong Differentially Private Learners

Reference 57

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Observation 6c7a5148-7e2e-4d9b-bf33-a21a6259c3de · outbound

This paper cites Membership leakage in label-only exposures.

Membership Inference Attacks on Tokenizers of Large Language Models Membership leakage in label-only exposures

Reference 58

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Observation d565d62b-72d0-436d-b87f-6575bdc965fa · outbound

This paper cites SuperBPE: Space travel for language models.

Membership Inference Attacks on Tokenizers of Large Language Models SuperBPE: Space travel for language models

Reference 59

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Observation 26dfcea7-eefe-4573-b0ca-10a9ca6486cd · outbound

This paper cites Please tell me more: Privacy impact of explainability through the lens of membership inference attack.

Membership Inference Attacks on Tokenizers of Large Language Models Please tell me more: Privacy impact of explainability through the lens of membership inference attack

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-04T11:23:16.360687Z

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Observation 1cf32503-e51d-48dc-b149-1ca34bcbb4d4 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Membership Inference Attacks on Tokenizers of Large Language Models RoBERTa: A Robustly Optimized BERT Pretraining Approach

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Observation 8eeb39b4-8961-4b75-84b6-4d2cfb4f6bb9 · outbound

This paper cites Visu- alizing data using t-sne.Journal of machine learning research, 9(Nov):2579–2605, 2008.

Membership Inference Attacks on Tokenizers of Large Language Models Visu- alizing data using t-sne.Journal of machine learning research, 9(Nov):2579–2605, 2008

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Observation a12af4f5-b25c-41ab-b928-be75d08e663c · outbound

This paper cites Llm dataset inference: Did you train on my dataset?Advances in Neural Information Pro- cessing Systems, 37:124069–124092, 2024.

Membership Inference Attacks on Tokenizers of Large Language Models Llm dataset inference: Did you train on my dataset?Advances in Neural Information Pro- cessing Systems, 37:124069–124092, 2024

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Observation 4e79cc26-6e8e-4630-918c-6d305bfe0198 · outbound

This paper cites Dataset Inference: Ownership Resolution in Machine Learning.

Membership Inference Attacks on Tokenizers of Large Language Models Dataset Inference: Ownership Resolution in Machine Learning

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Observation c65b1c6d-c3e5-49ad-b80d-604c169f334a · outbound

This paper cites Tokens used by gpt-4 probably come from the reddit users.

Membership Inference Attacks on Tokenizers of Large Language Models Tokens used by gpt-4 probably come from the reddit users

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Observation a66197b2-16c6-4989-9f59-589f0b43630b · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models LLMs on the line: Data determines loss-to-loss scaling laws

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Observation b3521f76-742b-4828-9233-99b2a9e4ada4 · outbound

This paper cites Did the neurons read your book? document-level membership inference for large language models.

Membership Inference Attacks on Tokenizers of Large Language Models Did the neurons read your book? document-level membership inference for large language models

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Observation b912c77d-5959-4f74-bc61-7b783e172bce · outbound

This paper cites Sok: Membership inference attacks on llms are rushing nowhere (and how to fix it).

Membership Inference Attacks on Tokenizers of Large Language Models Sok: Membership inference attacks on llms are rushing nowhere (and how to fix it)

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Observation c56e5eb5-d70d-4d4f-bd27-e1fae8896bd6 · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models Pointer Sentinel Mixture Models

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Membership Inference Attacks on Tokenizers of Large Language Models Large Language Models: A Survey

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Membership Inference Attacks on Tokenizers of Large Language Models Scaling data-constrained language models.Advances in Neural Information Processing Systems, 36:50358– 50376, 2023

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Membership Inference Attacks on Tokenizers of Large Language Models Com- prehensive privacy analysis of deep learning: Passive and active white-box inference attacks against central- ized and federated learning

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Membership Inference Attacks on Tokenizers of Large Language Models Reddit sues anthropic over its data scraping to train large language models

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Observation 0b8b1236-ce26-4eb9-8e53-6638b6b9ebf8 · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models System card of chatgpt-o1

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Observation 1fa7d70f-00bd-4771-972d-3c31d89bf895 · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models tiktoken: Tokenizer for openai models

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Observation cff1adc0-6037-44a8-8ea4-f8c1590afbdd · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models Black-box Membership Inference Attacks against Fine-tuned Diffusion Models

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Observation 309cdaaa-72d0-4beb-bf5c-35641c9f9867 · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models White-box Membership Inference Attacks against Diffusion Models

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Membership Inference Attacks on Tokenizers of Large Language Models Zipf’s word frequency law in natural language: A critical review and future direc- tions.Psychonomic bulletin & review, 21(5):1112– 1130, 2014

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Membership Inference Attacks on Tokenizers of Large Language Models Scaling up membership inference: When and how attacks succeed on large language mod- els

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Membership Inference Attacks on Tokenizers of Large Language Models Text mining: use of tf-idf to examine the relevance of words to docu- ments.International journal of computer applications, 181(1):25–29, 2018

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Membership Inference Attacks on Tokenizers of Large Language Models Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020

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Observation e33d4ce0-8b00-4cf1-b85d-cf3cf1ecf926 · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models Using tf-idf to determine word rele- vance in document queries

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Observation d7523255-b8bc-45f6-acb1-d4454dba0d7d · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models Gpqa: A graduate- level google-proof q&a benchmark

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Observation da2ec6eb-684f-4777-b0de-5350c18d96d6 · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models Self- comparison for dataset-level membership inference in large (vision-) language model

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Membership Inference Attacks on Tokenizers of Large Language Models Learning representations by back- propagating errors.nature, 323(6088):533–536, 1986

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Membership Inference Attacks on Tokenizers of Large Language Models White-box vs black-box: Bayes optimal strategies for membership inference

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This paper cites Simple and effec- tive masked diffusion language models.Advances in Neural Information Processing Systems, 37:130136– 130184, 2024.

Membership Inference Attacks on Tokenizers of Large Language Models Simple and effec- tive masked diffusion language models.Advances in Neural Information Processing Systems, 37:130136– 130184, 2024

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This paper cites ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models.

Membership Inference Attacks on Tokenizers of Large Language Models ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models

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Membership Inference Attacks on Tokenizers of Large Language Models Genomic privacy and limits of individual detection in a pool.Nature genetics, 41(9):965–967, 2009

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Membership Inference Attacks on Tokenizers of Large Language Models Language models are greedy reasoners: A systematic formal analysis of chain-of-thought

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Observation e0710dc0-34b3-43f1-84b8-160776b7f55a · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models Spearman’s rank correlation coeffi- cient.Bmj, 349, 2014

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Membership Inference Attacks on Tokenizers of Large Language Models Detecting pretraining data from large language models

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Observation 99600e56-1ee2-4f41-9361-43aa1acf2b31 · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models Byte pair encoding: A text compression scheme that accelerates pattern matching

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Membership Inference Attacks on Tokenizers of Large Language Models Membership inference attacks against machine learning models

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Membership Inference Attacks on Tokenizers of Large Language Models Spacebyte: Towards deleting tokeniza- tion from large language modeling.Advances in Neural Information Processing Systems, 37:124925– 124950, 2024

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Observation e5676652-d172-4871-93f1-c0deacbfa35f · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models A statistical interpretation of term specificity and its application in retrieval.Journal of documentation, 28(1):11–21, 1972

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Membership Inference Attacks on Tokenizers of Large Language Models Scaling laws with vocabulary: Larger mod- els deserve larger vocabularies.Advances in Neural Information Processing Systems, 37:114147–114179, 2024

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Observation 4d7019a2-f1f9-4993-8c01-4678c4699916 · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models On the vulnerability of text sanitization

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Membership Inference Attacks on Tokenizers of Large Language Models Inferdpt: Privacy-preserving inference for black-box large language models.IEEE Transactions on Dependable and Secure Computing, 2025

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Observation 027c7336-e9db-4dfa-998f-53f8d225a299 · outbound

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Membership Inference Attacks on Tokenizers of Large Language Models LLaMA: Open and Efficient Foundation Language Models

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