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Paper Citation Record · LEDGER

Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2204.12703.

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

pith.paper-citation-record.v1
2204.12703 v1

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 2026-08-05T06:32:48.257954+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T12:50:41.988694Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T01:06:24.110193Z

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 2727c497-b521-446f-b96b-c9f4a4c99801 · inbound

Representation-Aligned Multi-Scale Personalization for Federated Learning cites this paper.

Representation-Aligned Multi-Scale Personalization for Federated Learning Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning

Reference 4

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T09:56:01.499239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-05-10T15:45:17.555896Z digest=sha256:4b7681754eeb60affcdc28f9ba01e7f1c894682fb8ed2e988ecb500c25847d95

Observation bb9d0930-6404-44cc-b733-c3b883867141 · inbound

FedProxy: Federated Fine-Tuning of LLMs via Proxy SLMs and Heterogeneity-Aware Fusion cites this paper.

FedProxy: Federated Fine-Tuning of LLMs via Proxy SLMs and Heterogeneity-Aware Fusion Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning

Reference 81

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:56:06.666402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=arxiv_source observed=2026-05-10T02:35:40.593397Z digest=sha256:223f96e3e943a29fa734b6bfbdae3c71cbf1cd87b8fbac76af6fb51e0f4d877e

Observation 0dd280a6-d5bb-4e5b-b324-02c9a844ecda · inbound

Boosting Multimodal Federated Learning via Chained Modality Optimization cites this paper.

Boosting Multimodal Federated Learning via Chained Modality Optimization Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T01:06:24.111732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-28T12:50:41.988694Z digest=sha256:71ea06a8ce4f798f158ddefd778de5cba7c53bb2333cc622240cec22b84b3b5e