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Paper Citation Record · LEDGER

Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2002.10940.

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

pith.paper-citation-record.v1
2002.10940 v5

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 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:35:29.665720Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T14:13:21.237419Z

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 18de87ef-29fd-40ad-a805-85677420daf0 · inbound

Sign Operator for Coping with Heavy-Tailed Noise in Non-Convex Optimization: High Probability Bounds Under $(L_0, L_1)$-Smoothness cites this paper.

Sign Operator for Coping with Heavy-Tailed Noise in Non-Convex Optimization: High Probability Bounds Under $(L_0, L_1)$-Smoothness Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-08T11:35:29.665720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T11:35:29.665720Z digest=sha256:68ce6980edf8f1ff876ffdeea0cfda1deb6cdd7d5e3ad6566ef11a2693523c0c

Observation e443549c-b651-4ca3-9450-c1c3f949e365 · inbound

Byzantine Outside, Curious Inside: Reconstructing Data Through Malicious Updates cites this paper.

Byzantine Outside, Curious Inside: Reconstructing Data Through Malicious Updates Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-07T04:17:46.792095Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:17:46.792095Z digest=sha256:424595434ba2c67e53f0818a085c9af013ab505898404301174aa500b0227400

Observation 6c20472c-8c0f-4fdf-93ef-71f74f3ce58f · inbound

Improved Analysis for Sign-based Methods with Momentum Updates cites this paper.

Improved Analysis for Sign-based Methods with Momentum Updates Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T17:13:44.717529Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:13:44.717529Z digest=sha256:fc02a5f90abb6a6088cd320ce6642d1b207d8abd2fa31fe5377012677b9627d9

Observation 9a82bb99-8359-499e-a71a-0864560b9994 · inbound

ParaBlock: Communication-Computation Parallel Block Coordinate Federated Learning for Large Language Models cites this paper.

ParaBlock: Communication-Computation Parallel Block Coordinate Federated Learning for Large Language Models Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-03T20:29:49.125473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:29:49.125473Z digest=sha256:8ee135e64a4e6dcfc5fde06158746a5405e670a0c7b9cd62d38e4bae65a566fc

Observation 746ed81a-b507-4d46-8694-eb50005040d2 · inbound

Q-LocalAdam: Memory-Efficient Client-Side Adaptive Optimization for Edge Federated Learning cites this paper.

Q-LocalAdam: Memory-Efficient Client-Side Adaptive Optimization for Edge Federated Learning Stochastic-Sign SGD for Federated Learning with Theoretical Guarantees

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-20T14:13:21.238755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T14:11:53.371521Z digest=sha256:4decfdfae954cbc5e44e6c7eadd8a21c870e5f6b575b99923d03a80445006622