Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-15T19:26:13.175797Z
Paper Citation Record · LEDGER
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training
As of 22 July 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2602.22611.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-07-21T06:31:05.380196+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
13 of 13 outbound references displayed
- verified exact8
- verified fuzzy4
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation bacd9593-7050-4e07-94d0-fb37bbc3112f · outbound
This paper cites B., Mironov, I., Talwar, K., and Zhang, L.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training B., Mironov, I., Talwar, K., and Zhang, L
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T19:26:31.675561Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation f7b08cef-6523-4859-a5e2-e201a6ee0a5f · outbound
This paper cites Cal- ibrating noise to sensitivity in private data analysis.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training Cal- ibrating noise to sensitivity in private data analysis
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T19:26:31.672466Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation eb5d90cc-60b0-4e66-b134-5c3b19a9fdae · outbound
This paper cites Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-15T19:26:31.270195Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 2ee3ca89-dbb0-49fd-abc6-ff88cfbe094d · outbound
This paper cites an unresolved cited work.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training Unresolved cited work
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T19:26:31.669215Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation a533d1f0-6e23-4f45-b752-a4bc64306bf0 · outbound
This paper cites Progressive Growing of GANs for Improved Quality, Stability, and Variation.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training Progressive Growing of GANs for Improved Quality, Stability, and Variation
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T19:26:31.287253Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 26fad3c5-0e0e-466e-a998-d4d32cb24e73 · outbound
This paper cites Function-Consistent Feature Distillation.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training Function-Consistent Feature Distillation
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T19:26:31.265597Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation f86558a4-52ac-4c99-82c7-0ee06124eb04 · outbound
This paper cites Can Neural Network Memorization Be Localized?.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training Can Neural Network Memorization Be Localized?
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T19:26:31.301938Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation a4ad90f0-2eb8-4926-87ca-02c560163521 · outbound
This paper cites MTEB: Massive Text Embedding Benchmark.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training MTEB: Massive Text Embedding Benchmark
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T19:26:31.291505Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation f0ccc035-5bf6-409f-89c6-c8822f9748e8 · outbound
This paper cites AdaCliP: Adaptive Clipping for Private SGD.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training AdaCliP: Adaptive Clipping for Private SGD
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T19:26:31.296429Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation ee548ee4-a2d1-4cbb-a070-5d6c38936444 · outbound
This paper cites ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training ML-Leaks: Model and Data Independent Membership Inference Attacks and Defenses on Machine Learning Models
Reference 10
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T19:26:31.279487Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 9ea2a2ab-7cef-443d-a05c-c2d55e940d10 · outbound
This paper cites BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-05-15T19:26:31.283487Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 03e86f1c-0fe9-4020-9736-cc677d4a2301 · outbound
This paper cites Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T19:26:31.275224Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Observation 89ab32f6-9e67-4bd0-8153-3cf22a732c2e · outbound
This paper cites Notations For clarity and consistency, Table 4 provides a summary of key symbols and their corresponding descriptions.
Mitigating Membership Inference in Intermediate Representations with Differentially Private Training Notations For clarity and consistency, Table 4 provides a summary of key symbols and their corresponding descriptions
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-15T19:26:31.665777Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-07-21T06:31:05.380196+00:00.
Pith citing papers
No inbound Pith citation observations are available.