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Paper Citation Record · LEDGER

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning

As of 16 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 0 inbound Pith citation observations for arXiv:2411.11144.

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

pith.paper-citation-record.v1
2411.11144 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T18:54:57.819552Z

measured 43 of 43 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

43 of 43 outbound references displayed

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External citation measurements

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Outbound references

Observation 89877994-a8ac-48fb-8275-7192cf126b18 · outbound

This paper cites Deep learning with differential privacy,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Deep learning with differential privacy,

Reference 1

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Observation ae066db7-cff7-46f5-9fc0-0afceb686d12 · outbound

This paper cites Membership inference attacks from first principles,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Membership inference attacks from first principles,

Reference 2

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Observation 93d1d80a-4a1c-411e-b835-4b46629264ac · outbound

This paper cites The secret sharer: Evaluating and testing unintended memorization in neural net- works,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning The secret sharer: Evaluating and testing unintended memorization in neural net- works,

Reference 3

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Observation a06cb806-6156-4522-a979-cbdb0961e20f · outbound

This paper cites RelaxLoss: Defending Membership Inference Attacks without Losing Utility.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning RelaxLoss: Defending Membership Inference Attacks without Losing Utility

Reference 4

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Observation 6a41c433-297a-46bc-be70-29062f931204 · outbound

This paper cites Practical membership inference attack against collaborative inference in industrial iot,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Practical membership inference attack against collaborative inference in industrial iot,

Reference 5

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Observation df31b5b6-ed34-4fa5-9876-10aca03a8562 · outbound

This paper cites A simple framework for contrastive learning of visual representations,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning A simple framework for contrastive learning of visual representations,

Reference 6

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Observation e89c699f-44a4-48ec-825c-37b76d3aa8b5 · outbound

This paper cites Predicting future earnings changes using machine learning and detailed financial data,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Predicting future earnings changes using machine learning and detailed financial data,

Reference 7

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Observation 47328948-3030-4117-b0e1-d865c920e35a · outbound

This paper cites Exploring simple siamese representation learning,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Exploring simple siamese representation learning,

Reference 8

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Observation a4e2b470-ec8a-4f24-b678-9bb607cc92d4 · outbound

This paper cites Exploring simple siamese representation learning,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Exploring simple siamese representation learning,

Reference 9

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Observation 49f6c73a-1d56-4be2-898f-13a6341c16b0 · outbound

This paper cites Leveraging adversarial examples to quantify membership information leakage,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Leveraging adversarial examples to quantify membership information leakage,

Reference 10

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Observation 2c2815ef-c130-4db1-ba6e-e74562490892 · outbound

This paper cites Simcse: Simple contrastive learning of sentence embeddings,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Simcse: Simple contrastive learning of sentence embeddings,

Reference 11

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Observation eabbac77-304f-41e2-b1f0-c08fd9e2dd6b · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Bootstrap your own latent-a new approach to self-supervised learning,

Reference 12

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Observation ddcc38e4-b4b7-4d5d-b4bf-4acc945ccd68 · outbound

This paper cites Momentum contrast for unsupervised visual representation learning,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Momentum contrast for unsupervised visual representation learning,

Reference 13

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Observation 1561a008-285d-4bfb-b945-d191e209bd88 · outbound

This paper cites Segmentations-leak: Membership inference attacks and defenses in semantic image segmen- tation,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Segmentations-leak: Membership inference attacks and defenses in semantic image segmen- tation,

Reference 14

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Observation 15948c6b-1c55-42c8-aafd-b9b5a88a9637 · outbound

This paper cites Mem- bership inference via backdooring,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Mem- bership inference via backdooring,

Reference 15

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Observation e9e8bd1d-647b-4a07-81f4-5ea76500c662 · outbound

This paper cites Practical blind membership inference attack via differential comparisons,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Practical blind membership inference attack via differential comparisons,

Reference 16

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Observation bfc91a05-0617-486e-8813-61b102b52230 · outbound

This paper cites Demystifying the membership inference attack,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Demystifying the membership inference attack,

Reference 17

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Observation 2be8d422-7bf8-4e2a-8674-29ed0b5c95f6 · outbound

This paper cites Memguard: Defending against black-box membership inference attacks via adver- sarial examples,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Memguard: Defending against black-box membership inference attacks via adver- sarial examples,

Reference 18

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Observation 07e3ef05-b8dc-4de9-a3a4-4155e99b7645 · outbound

This paper cites When does data augmentation help with membership inference attacks?.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning When does data augmentation help with membership inference attacks?

Reference 19

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Observation 136e927d-4e51-431e-868d-124e0fb0a82c · outbound

This paper cites On the Effectiveness of Regularization Against Membership Inference Attacks.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning On the Effectiveness of Regularization Against Membership Inference Attacks

Reference 20

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Observation 0956fc74-6bd3-4c9e-8fe6-37f51a54fcc6 · outbound

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

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Stolen memories: Leveraging model memorization for calibrated {White-Box} membership inference,

Reference 21

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Observation 20493039-ead3-4e65-844d-63aebb348456 · outbound

This paper cites User-Level Membership Inference Attack against Metric Embedding Learning.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning User-Level Membership Inference Attack against Metric Embedding Learning

Reference 22

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Observation 8224e8f6-d113-4e30-8f59-7115235c75f4 · outbound

This paper cites Membership inference attacks and defenses in classification models,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Membership inference attacks and defenses in classification models,

Reference 23

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Observation c11bd846-c5b7-4d86-8666-5f750bdead7f · outbound

This paper cites Membership leakage in label-only exposures,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Membership leakage in label-only exposures,

Reference 24

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Observation ec6c2e4e-f1b2-423e-9dc4-3b22fd7caf66 · outbound

This paper cites Socinf: Membership inference attacks on social media health data with machine learning,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Socinf: Membership inference attacks on social media health data with machine learning,

Reference 25

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Observation 3157bf97-0ef1-441c-8664-ebfad57eb354 · outbound

This paper cites Membership inference attacks by exploiting loss trajectory,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Membership inference attacks by exploiting loss trajectory,

Reference 26

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Observation 0212ee6f-7a6e-4e02-a8a0-0f341a156bd0 · outbound

This paper cites Membership inference attacks by exploiting loss trajectory,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Membership inference attacks by exploiting loss trajectory,

Reference 27

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Observation d3abadae-3eac-4111-b9df-18e7ccdffe57 · outbound

This paper cites Understanding Membership Inferences on Well-Generalized Learning Models.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Understanding Membership Inferences on Well-Generalized Learning Models

Reference 28

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Observation 0776587d-7dd4-4b4e-81ad-70c121db7927 · outbound

This paper cites The audio auditor: User-level membership inference in internet of things voice services,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning The audio auditor: User-level membership inference in internet of things voice services,

Reference 29

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Observation 9016b324-f22d-4193-b7a4-b93fb98d7f20 · outbound

This paper cites Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning,

Reference 30

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Observation 3e7adc52-b810-465e-8b0a-fa849c488c3f · outbound

This paper cites Knock Knock, Who's There? Membership Inference on Aggregate Location Data.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Knock Knock, Who's There? Membership Inference on Aggregate Location Data

Reference 31

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Observation 6c828998-a2ad-4331-ab8f-068940d7b34e · outbound

This paper cites Differential privacy defenses and sampling attacks for membership inference,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Differential privacy defenses and sampling attacks for membership inference,

Reference 32

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Observation c55a4481-9804-4298-a098-8cf5b5c7e7c3 · outbound

This paper cites White-box vs black-box: Bayes optimal strategies for membership inference,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning White-box vs black-box: Bayes optimal strategies for membership inference,

Reference 33

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Observation cbe1b33f-5d89-415a-95ff-72c4d3e4442b · outbound

This paper cites Ml-leaks: Model and data independent membership inference attacks and defenses on machine learning models,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Ml-leaks: Model and data independent membership inference attacks and defenses on machine learning models,

Reference 34

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Observation 700440c6-bd46-45cb-8cf1-6aaac1668e05 · outbound

This paper cites Evaluating the vulnerability of end-to-end automatic speech recogni- tion models to membership inference attacks.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Evaluating the vulnerability of end-to-end automatic speech recogni- tion models to membership inference attacks

Reference 35

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 3c827b07-bb14-4e7e-a061-2e8434c2c7d3 · outbound

This paper cites Membership inference attacks against machine learning models,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Membership inference attacks against machine learning models,

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-12T18:54:58.154913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-12T18:54:57.787638Z digest=sha256:12301514fd74315d5e93f21069e1f03fc4f172b2f03f15b654d7b1506b777d15

Observation d1d35f68-41b0-4d42-bf1c-3ab2ba8cf637 · outbound

This paper cites Systematic evaluation of privacy risks of ma- chine learning models,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Systematic evaluation of privacy risks of ma- chine learning models,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:54:58.140068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-12T18:54:57.792411Z digest=sha256:1347d9c284fee4659cd3f318bec0f7f6681d3c2d9b74f5fb0e89bf97c10c33aa

Observation 08fb08b1-f422-469c-9303-67293f0b37dd · outbound

This paper cites Privacy risks of securing machine learning models against adversarial examples,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Privacy risks of securing machine learning models against adversarial examples,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:54:58.124635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-12T18:54:57.796883Z digest=sha256:8ca769d6fab248406f1256c647b900bc699a3e3ae7c2e7a8a262100d4a80360f

Observation aa7582c7-b283-4a34-ab0f-c1a040ec3474 · outbound

This paper cites Unsupervised feature learning via non-parametric instance discrimination,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Unsupervised feature learning via non-parametric instance discrimination,

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T18:54:57.801398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:54:57.801398Z digest=sha256:89952fb9a968dd139b9d0b670dc5d28426ae259161bb4274d37406248ca557fc

Observation 164caadb-57c9-4168-a155-775576c978fd · outbound

This paper cites Privacy risk in machine learning: Analyzing the connection to overfitting,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Privacy risk in machine learning: Analyzing the connection to overfitting,

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-12T18:54:57.805955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T18:54:57.805955Z digest=sha256:6e4742000cab4791791b1394c1ac5f39fd71f51da3b35c62baa991f3ced9c903

Observation b6e9ba71-091a-4f54-9219-a3afec45f582 · outbound

This paper cites Label-only membership inference attacks and defenses in semantic segmentation models,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Label-only membership inference attacks and defenses in semantic segmentation models,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:54:58.089604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-12T18:54:57.810349Z digest=sha256:6568fd7420a60ebcad5abd72f8c39fdc96d16d0fab30d5e0ee5fb742cb975f4c

Observation f04a5553-1832-4992-b17a-51e5b210f6b4 · outbound

This paper cites Membership inference attacks against recommender systems,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Membership inference attacks against recommender systems,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:54:58.073775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-12T18:54:57.814980Z digest=sha256:8a8d45647c175025f423b1a4325c223693db7ae197ca279c86baad8920715f6b

Observation be0123c1-519c-418b-96eb-f03f19f44c66 · outbound

This paper cites Membership inference attacks against synthetic health data,.

CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning Membership inference attacks against synthetic health data,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T18:54:58.056129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-12T18:54:57.819552Z digest=sha256:962814fc840232c1588dcb54a7519acddfb62dc593fd3de8d5d042f36f263444

Pith citing papers

No inbound Pith citation observations are available.