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Paper Citation Record · LEDGER

A Secure and Efficient Federated Learning Framework for NLP

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2201.11934.

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

pith.paper-citation-record.v1
2201.11934 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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:13:03.302442Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T06:01:23.672744Z

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 a17c0b48-59d7-49af-aee4-c564db33ae11 · inbound

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation cites this paper.

DSFL: A Dual-Server Byzantine-Resilient Federated Learning Framework via Group-Based Secure Aggregation A Secure and Efficient Federated Learning Framework for NLP

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T16:13:03.302442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:13:03.302442Z digest=sha256:1642de06796f2b7d949b826ecdbb514c35ac70056cf933582ecfc0e19d180362

Observation e6f39494-f3d4-470e-9c8d-84ea81285cab · inbound

Provable Sparse Inversion and Token Relabel Enhanced One-shot Federated Learning with ViTs cites this paper.

Provable Sparse Inversion and Token Relabel Enhanced One-shot Federated Learning with ViTs A Secure and Efficient Federated Learning Framework for NLP

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:01:23.675577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-12T04:42:46.426796Z digest=sha256:e114747ffcff0390054a007239f7d279baca84f6c1f6005c51e65e46ea3e9fe3