Pith. sign in

Paper Citation Record · LEDGER

Heterogeneous Federated Learning

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2008.06767.

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

pith.paper-citation-record.v1
2008.06767 v2

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 2026-08-11T06:34:44.6726+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:33:58.358797Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T09:15:44.222518Z

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 14d7a7fd-e4c0-4b1b-9a81-33a8c89ea563 · inbound

Heterogeneous Federated Learning Systems for Time-Series Power Consumption Prediction with Multi-Head Embedding Mechanism cites this paper.

Heterogeneous Federated Learning Systems for Time-Series Power Consumption Prediction with Multi-Head Embedding Mechanism Heterogeneous Federated Learning

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-10T17:33:58.358797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:33:58.358797Z digest=sha256:a4cb5d8efa1bfed1ac266c55a67239983777b37dc16c4e9719c0ce289ccc6693

Observation 5fa57d8e-c89b-4921-87cc-724236b7a9ca · inbound

Coalition Formation for Heterogeneous Federated Learning Enabled Channel Estimation in RIS-assisted Cell-free MIMO cites this paper.

Coalition Formation for Heterogeneous Federated Learning Enabled Channel Estimation in RIS-assisted Cell-free MIMO Heterogeneous Federated Learning

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-08T19:02:23.315520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:02:23.315520Z digest=sha256:38d3032be22da1ff3eaccc4ae3fd78bdead853d9a2bbc9a077b1bf7148673489

Observation bed99ba9-7475-4b59-9b8e-4384181019d6 · inbound

FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection cites this paper.

FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection Heterogeneous Federated Learning

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-11T21:46:16.946250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-08T04:30:06.269559Z digest=sha256:3e0bb66dc47dcacd4fa17cce33b9628e85e03740a86610dfaac6984aa1f8642b

Observation 074e2da2-c600-4b43-969e-170016e53a87 · inbound

FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection cites this paper.

FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection Heterogeneous Federated Learning

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-07-01T09:15:44.226077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-07-01T09:10:20.045403Z digest=sha256:cfec9df8bea7027de72debcad83004c9a8e8ce70d4cb543a43437dbe4713655e

Observation b16f5938-e820-4ef5-abd1-3d97dd50e623 · inbound

Subspace Optimization for Efficient Federated Learning under Heterogeneous Data cites this paper.

Subspace Optimization for Efficient Federated Learning under Heterogeneous Data Heterogeneous Federated Learning

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:31:17.616953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-07T16:45:53.627922Z digest=sha256:96293064fa31a0cccc77a6d0939fc20440184564410da30281ab867abeb7d5e8