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Paper Citation Record · LEDGER

When MiniBatch SGD Meets SplitFed Learning:Convergence Analysis and Performance Evaluation

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2308.11953.

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

pith.paper-citation-record.v1
2308.11953 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:02:47.044732Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T22:26:14.020984Z

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 a2403aeb-246a-4738-aa2e-eb19d915a97b · inbound

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? cites this paper.

How Can Incentives and Cut Layer Selection Influence Data Contribution in Split Federated Learning? When MiniBatch SGD Meets SplitFed Learning:Convergence Analysis and Performance Evaluation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T19:02:47.044732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:02:47.044732Z digest=sha256:102b84bbd84174fe2610004ef274ae634ee1b294508337d5f2fe5c5318adb6f3

Observation 75ea73ac-9a71-4e32-b25e-32dd3a52d47e · 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 When MiniBatch SGD Meets SplitFed Learning:Convergence Analysis and Performance Evaluation

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:26:14.030534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-08T02:46:34.459345Z digest=sha256:3169a8fedc4393b8a595ad4b88f9b2622228ab5dced820f02de661d8f22dd5b3