Paper Citation Record · LEDGER

Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2404.06114.

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

pith.paper-citation-record.v1
2404.06114 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T21:59:29.312593Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 39a78f93-62ff-421f-8049-18203beaf1dd · inbound

Energy Consumption in Parallel Neural Network Training cites this paper.

Energy Consumption in Parallel Neural Network Training Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-05T21:59:29.312593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41ac7e3a-b43a-4dfa-becb-7b516fea32bf · inbound

NCCLZ: Compression-Enabled GPU Collectives with Decoupled Quantization and Entropy Coding cites this paper.

NCCLZ: Compression-Enabled GPU Collectives with Decoupled Quantization and Entropy Coding Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-13T03:37:11.692948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 658633d2-acbf-42eb-8636-ae0e91f6002f · inbound

Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity cites this paper.

Rescaled Asynchronous SGD: Optimal Distributed Optimization under Data and System Heterogeneity Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey

Reference 73

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:32:51.306739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ef788e5b-2660-4900-b5b5-1bc0669180fc · inbound

ScaleAcross: Designing Multi-Data-Center Infrastructure for Geo-Distributed AI Training cites this paper.

ScaleAcross: Designing Multi-Data-Center Infrastructure for Geo-Distributed AI Training Communication-Efficient Large-Scale Distributed Deep Learning: A Comprehensive Survey

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T16:28:38.933384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.