Pith. sign in

Paper Citation Record · LEDGER

FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2202.01267.

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

pith.paper-citation-record.v1
2202.01267 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 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:13:00.330125Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T21:50:19.377413Z

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 024b8d6d-2691-46bb-8ce0-6090707c3182 · inbound

EarthSight: A Distributed Framework for Low-Latency Satellite Intelligence cites this paper.

EarthSight: A Distributed Framework for Low-Latency Satellite Intelligence FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-17T21:50:19.379861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-17T21:50:17.098331Z digest=sha256:d036bcbda5dbe4cd256c4dbc0251e364431bd12fa5d48bd176ebc993eba0f144

Observation 2af4e106-4740-4397-8244-5e2118e499ea · inbound

Equinox: Decentralized Scheduling for Hardware-Aware Orbital Intelligence cites this paper.

Equinox: Decentralized Scheduling for Hardware-Aware Orbital Intelligence FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-10T01:04:50.162778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T01:00:52.055938Z digest=sha256:b2570f09081475547126ed4ac995ca37e6ccf5e9cdb806cef9e6128428c15014

Observation c0a52a5f-8a55-431d-af18-4e8147a01a89 · inbound

Constraint-Aware Execution Planning for Hybrid Space-Ground Compute Workloads cites this paper.

Constraint-Aware Execution Planning for Hybrid Space-Ground Compute Workloads FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-15T16:30:09.894985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T16:27:19.738832Z digest=sha256:fc916f6aad636c5388561b4a41719f43988b432b778168464e18c4a65f60941a

Observation 4d6f3c8f-38ac-4637-80fd-5b3062add99f · inbound

Topology-Aware Two-Stage Federated Learning via Proxy Models for Sub-THz Heterogeneous LEO Communications cites this paper.

Topology-Aware Two-Stage Federated Learning via Proxy Models for Sub-THz Heterogeneous LEO Communications FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:06:06.927982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T16:39:18.491139Z digest=sha256:33c6c53e1edd810b616d95136c56e43cb34d29a2a41b6beed07c263714fbb4cb

Observation 3031fbec-1cc6-4ea3-8115-82d17d77cadc · inbound

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations cites this paper.

FedRings: A Scalable and Topology-Aware Federated Learning Framework for LEO Satellite Constellations FedSpace: An Efficient Federated Learning Framework at Satellites and Ground Stations

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T19:13:00.330125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:13:00.330125Z digest=sha256:1544934bb61b303572e3289081f477ed55af401a62170f419352b6d3c5864f90