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Paper Citation Record · LEDGER

Differentially Private Label Protection in Split Learning

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2203.02073.

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

pith.paper-citation-record.v1
2203.02073 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:57:20.837784Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T22:26:14.000786Z

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 c2ec2967-31cf-4eab-bbee-f36700fcc1d4 · inbound

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) cites this paper.

SafeSplit: A Novel Defense Against Client-Side Backdoor Attacks in Split Learning (Full Version) Differentially Private Label Protection in Split Learning

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-10T21:02:02.001136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:02:02.001136Z digest=sha256:821f76b72ecb1ae05b6a20f54e3c65429fa86e9d7b07f0262135f721a5353d99

Observation 90f9b373-0c86-4033-af96-633083bdc780 · inbound

A Taxonomy of Attacks and Defenses in Split Learning cites this paper.

A Taxonomy of Attacks and Defenses in Split Learning Differentially Private Label Protection in Split Learning

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-15T22:57:20.837784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:57:20.837784Z digest=sha256:33deca03e3850b8c1f40d64de8286a79b96d1055c877a77c3bd2ceab80649b15

Observation 7c3df98c-af9f-4576-9e6a-f89304f22a91 · inbound

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

Privacy Preserving Conversion Modeling in Data Clean Room Differentially Private Label Protection in Split Learning

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T15:32:44.289368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:32:44.289368Z digest=sha256:d9b9491d035070378add47385ec6ec4daba7dcf68d99130529e961b65e603bde

Observation b0622afb-4521-446e-afd9-f57118aec960 · inbound

Scalable and Private Federated Learning Using Distributed Differential Privacy and Secure Aggregation cites this paper.

Scalable and Private Federated Learning Using Distributed Differential Privacy and Secure Aggregation Differentially Private Label Protection in Split Learning

Reference 83

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:51:11.068307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T17:54:31.930947Z digest=sha256:fc9db9262f6c7c98fde840b54040d904f3f18ab21132dae155b75b316c07fa3f

Observation 36c30be5-316d-4882-a3d4-aef6b1743de1 · inbound

A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations cites this paper.

A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations Differentially Private Label Protection in Split Learning

Reference 159

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:26:14.008055Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-08T02:46:34.459345Z digest=sha256:0f49e85ef3e4739b0f6ff32aa27622a1e8717df9d3a8eaa1b480f53615426c63