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Paper Citation Record · LEDGER

Training Differentially Private Models with Secure Multiparty Computation

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2202.02625.

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

pith.paper-citation-record.v1
2202.02625 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:58:39.578816Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T09:05:37.609086Z

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 ce10caea-ff50-40ad-9c7f-c85aa44deed0 · inbound

ByzSFL: Achieving Byzantine-Robust Secure Federated Learning with Zero-Knowledge Proofs cites this paper.

ByzSFL: Achieving Byzantine-Robust Secure Federated Learning with Zero-Knowledge Proofs Training Differentially Private Models with Secure Multiparty Computation

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-10T20:58:39.578816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:58:39.578816Z digest=sha256:9f8f7a48e68313fb5d7740a43e0f9320104f88f9b2cc492c399c00a314c373c2

Observation 9cbee824-27fe-49e8-a31b-f9e0ecbd81b7 · inbound

Secure and Privacy-Preserving Vertical Federated Learning cites this paper.

Secure and Privacy-Preserving Vertical Federated Learning Training Differentially Private Models with Secure Multiparty Computation

Reference 75

Resolution
verified exact
arxiv_id, observed 2026-05-10T13:45:27.770689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T13:44:02.024816Z digest=sha256:61db2642151e82e6e8d8f3fa8e14bc4bb0902a6ede8b25f37e36fb959247ec6e

Observation d18b419d-63ec-4c95-bc85-586980511119 · inbound

Probing Memorization of Tabular In-Context Learning cites this paper.

Probing Memorization of Tabular In-Context Learning Training Differentially Private Models with Secure Multiparty Computation

Reference 56

Resolution
verified exact
arxiv_id, observed 2026-07-01T09:05:37.615840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-07-01T06:37:44.328625Z digest=sha256:5f0d66f43d845c008feb9309ec2175ed6fab2fbe58623db9d4560fc12b4aa5b9