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Paper Citation Record · LEDGER

EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2205.04180.

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

pith.paper-citation-record.v1
2205.04180 v4

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 2026-08-04T06:34:03.388597+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T05:49:28.713982Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T05:49:40.674609Z

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 1c534154-0863-4872-a0ed-afef8139f238 · inbound

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

Scalable Distributed Stochastic Optimization via Bidirectional Compression: Beyond Pessimistic Limits EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization

Reference 96

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:05:54.870792Z

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.

source=arxiv_source observed=2026-05-11T02:52:53.588595Z digest=sha256:ce0e23f5ece6895c540b9346ff952b98efd36bd1f9d31d6655145ac1e9b1d67e

Observation 8e0ff453-a492-429f-89d9-8add88445282 · 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 EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization

Reference 175

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:51:34.111621Z

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.

source=arxiv_source observed=2026-05-12T01:51:20.003552Z digest=sha256:c67a6df36ff6d9227bc7101808394b2659186397279e378765aef7c16fc12b18

Observation a0fe9d9c-e00d-4450-aa10-16553b394650 · 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 EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization

Reference 280

Resolution
verified exact
arxiv_id, observed 2026-05-14T19:32:52.127647Z

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.

source=arxiv_source observed=2026-05-14T19:31:12.149482Z digest=sha256:ad5fd958647fe29f194356e5700a37796db7f517ac781d51b5f412cd1816361e

Observation 17cf50c8-d48a-4122-bc81-74c36d742980 · inbound

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

Ringmaster LMO: Asynchronous Linear Minimization Oracle Momentum Method EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization

Reference 177

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:13:18.452507Z

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.

source=arxiv_source observed=2026-05-20T13:08:52.912250Z digest=sha256:b784a82e8d143f0415681aad03ee9fb72a075a371f07ef3f0c2939593ba323ef

Observation c260891b-0929-4e16-8fcd-845a07fa1cf1 · inbound

LOSCAR-SGD: Local SGD with Communication-Computation Overlap and Delay-Corrected Sparse Model Averaging cites this paper.

LOSCAR-SGD: Local SGD with Communication-Computation Overlap and Delay-Corrected Sparse Model Averaging EF-BV: A Unified Theory of Error Feedback and Variance Reduction Mechanisms for Biased and Unbiased Compression in Distributed Optimization

Reference 178

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:49:40.676157Z

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.

source=arxiv_source observed=2026-05-21T05:49:28.713982Z digest=sha256:0682101715fb050c57bae5babc7237c6db136b0abb2c4e37b4fd2f89a955cff5