Paper Citation Record · LEDGER

On Biased Compression for Distributed Learning

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2002.12410.

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

pith.paper-citation-record.v1
2002.12410 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-23T18:58:32.168274Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T19:03:21.891826Z

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 9fcbb58b-25ab-471d-8615-8477c017405a · inbound

Tighter Performance Theory of FedExProx cites this paper.

Tighter Performance Theory of FedExProx On Biased Compression for Distributed Learning

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:03:21.896166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a1a4f7a4-5787-482e-a273-7134eb3a5807 · inbound

Improved Convergence for Decentralized Stochastic Optimization with Biased Gradients cites this paper.

Improved Convergence for Decentralized Stochastic Optimization with Biased Gradients On Biased Compression for Distributed Learning

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:00:58.038131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6f4324de-bc99-42f1-9305-de594a6c9926 · inbound

Scalable Distributed Stochastic Optimization via Bidirectional Compression: Beyond Pessimistic Limits cites this paper.

Scalable Distributed Stochastic Optimization via Bidirectional Compression: Beyond Pessimistic Limits On Biased Compression for Distributed Learning

Reference 25

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T03:05:54.881821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 39d40f27-4799-4843-95f3-84fc64e75ed5 · inbound

Rennala MVR: Improved Time Complexity for Parallel Stochastic Optimization via Momentum-Based Variance Reduction cites this paper.

Rennala MVR: Improved Time Complexity for Parallel Stochastic Optimization via Momentum-Based Variance Reduction On Biased Compression for Distributed Learning

Reference 101

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T07:51:32.227933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 98a1d22d-b526-4db2-ac3f-324bfc4d2801 · 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 On Biased Compression for Distributed Learning

Reference 218

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T19:32:52.154101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0dd46d94-8e11-4d7a-a00f-99a938f80eec · inbound

Ringmaster LMO: Asynchronous Linear Minimization Oracle Momentum Method cites this paper.

Ringmaster LMO: Asynchronous Linear Minimization Oracle Momentum Method On Biased Compression for Distributed Learning

Reference 103

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T13:13:18.631188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.