Paper Citation Record · LEDGER

Blind Baselines Beat Membership Inference Attacks for Foundation Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2406.16201.

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

pith.paper-citation-record.v1
2406.16201 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:58:01.315898Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T16:49:57.332189Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e7466f45-a03f-4c2e-acf0-7ee3857095f1 · inbound

Synthetic Data Can Mislead Evaluations: Membership Inference as Machine Text Detection cites this paper.

Synthetic Data Can Mislead Evaluations: Membership Inference as Machine Text Detection Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-10T17:58:01.315898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46ad08a5-44ba-4310-a002-24e41f574e34 · inbound

Riddle Me This! Stealthy Membership Inference for Retrieval-Augmented Generation cites this paper.

Riddle Me This! Stealthy Membership Inference for Retrieval-Augmented Generation Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T19:32:34.210438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50c0aa63-13be-43e9-b518-401304874202 · inbound

How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence cites this paper.

How Contaminated Is Your Benchmark? Quantifying Dataset Leakage in Large Language Models with Kernel Divergence Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-09T18:11:34.958297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65b390e2-b07e-47ce-8d8e-4bc27b8f4354 · inbound

Position: Adversarial ML for LLMs Is Not Making Any Progress cites this paper.

Position: Adversarial ML for LLMs Is Not Making Any Progress Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-09T12:47:21.646809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55013165-6fae-4f78-8c63-3d6d866a728c · inbound

How much do language models memorize? cites this paper.

How much do language models memorize? Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:35:37.466719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8eaa5759-0314-41c5-a184-6b38f69dae84 · inbound

What Really is a Member? Discrediting Membership Inference via Poisoning cites this paper.

What Really is a Member? Discrediting Membership Inference via Poisoning Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T06:13:04.729680Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acbb2d96-5b45-4e4a-a34e-9f1fb404ad37 · inbound

Hey, That's My Data! Token-Only Dataset Inference in Large Language Models cites this paper.

Hey, That's My Data! Token-Only Dataset Inference in Large Language Models Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-19T11:07:15.785816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c073c910-4be3-4f8a-bfb6-ccb2432706b5 · inbound

SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning against Membership Inference Attacks cites this paper.

SOFT: Selective Data Obfuscation for Protecting LLM Fine-tuning against Membership Inference Attacks Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T04:33:16.850599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 645920de-1fd1-4335-863c-bc93d144ea7f · inbound

Rectifying Privacy and Efficacy Measurements in Machine Unlearning: A New Inference Attack Perspective cites this paper.

Rectifying Privacy and Efficacy Measurements in Machine Unlearning: A New Inference Attack Perspective Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T00:42:28.132202Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 70e6cf08-dc4a-4b82-a179-d8d1aea8ca75 · inbound

Membership Inference Attacks as Privacy Tools: Reliability, Disparity and Ensemble cites this paper.

Membership Inference Attacks as Privacy Tools: Reliability, Disparity and Ensemble Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T00:30:35.058644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caa7fbb1-adbc-43b4-99a1-1ed6457181d5 · inbound

Layer-Wise Perturbations via Sparse Autoencoders for Adversarial Text Generation cites this paper.

Layer-Wise Perturbations via Sparse Autoencoders for Adversarial Text Generation Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 130

Resolution: unresolved; no resolver link, observed 2026-08-05T20:31:44.862860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0559cb92-41b8-49a9-a2df-a94f97c92065 · inbound

Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models cites this paper.

Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 285

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:27:29.601787Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 80e0ad19-9119-40b8-b0a3-c6b491123a18 · inbound

Natural Identifiers for Privacy and Data Audits in Large Language Models cites this paper.

Natural Identifiers for Privacy and Data Audits in Large Language Models Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-04T16:49:57.333760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 248863ba-a2bf-44eb-b301-866a91c8152c · inbound

Leak It: A Probabilistic Approach to Training-Data Extraction from Black-Box Language Models cites this paper.

Leak It: A Probabilistic Approach to Training-Data Extraction from Black-Box Language Models Blind Baselines Beat Membership Inference Attacks for Foundation Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T01:13:45.742226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.