Paper Citation Record · LEDGER

Deep Leakage from Gradients

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1906.08935.

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

pith.paper-citation-record.v1
1906.08935 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:39:53.272927Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T10:24:06.836970Z

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 e6f34589-aab0-4634-ae1d-4b915f76f4e3 · inbound

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning cites this paper.

SMTFL: Secure Model Training to Untrusted Participants in Federated Learning Deep Leakage from Gradients

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-09T13:39:53.272927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89257ba0-bdc9-4ab2-9738-27bcfce1e6bf · inbound

Large Language Model Adversarial Landscape Through the Lens of Attack Objectives cites this paper.

Large Language Model Adversarial Landscape Through the Lens of Attack Objectives Deep Leakage from Gradients

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T10:29:50.009850Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7542908e-e29e-4929-8837-f10e6200977c · inbound

Privacy Preserving Conversion Modeling in Data Clean Room cites this paper.

Privacy Preserving Conversion Modeling in Data Clean Room Deep Leakage from Gradients

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T15:32:44.621939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65a5a987-39a0-419e-9a0f-75e3b4ac9d5c · inbound

FedRP: A Communication-Efficient Approach for Differentially Private Federated Learning Using Random Projection cites this paper.

FedRP: A Communication-Efficient Approach for Differentially Private Federated Learning Using Random Projection Deep Leakage from Gradients

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-04T18:23:57.138979Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cb83209-a438-43b1-9954-11aafe8dde2a · inbound

Informationally Compressive Anonymization: Non-Degrading Sensitive Input Protection for Privacy-Preserving Supervised Machine Learning cites this paper.

Informationally Compressive Anonymization: Non-Degrading Sensitive Input Protection for Privacy-Preserving Supervised Machine Learning Deep Leakage from Gradients

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-21T10:24:06.838298Z

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 b62c528a-9121-47e5-b09f-91bbd9031708 · inbound

Privacy Leakage in Federated Learning in Radiology Reports: A Comparative Evaluation of Tokenizer-Driven Privacy Risks cites this paper.

Privacy Leakage in Federated Learning in Radiology Reports: A Comparative Evaluation of Tokenizer-Driven Privacy Risks Deep Leakage from Gradients

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-02T02:54:04.303701Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.