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Paper Citation Record · LEDGER

Jointly Improving the Sample and Communication Complexities in Decentralized Stochastic Minimax Optimization

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2307.09421.

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

pith.paper-citation-record.v1
2307.09421 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:14:38.867602Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T02:43:47.436900Z

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 6136e4a3-77d5-4497-b060-98952be07937 · inbound

A Stochastic GDA Method With Backtracking For Solving Nonconvex Concave Minimax Problems cites this paper.

A Stochastic GDA Method With Backtracking For Solving Nonconvex Concave Minimax Problems Jointly Improving the Sample and Communication Complexities in Decentralized Stochastic Minimax Optimization

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-24T02:43:47.439947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-24T02:40:21.808440Z digest=sha256:4708452437ee7dc2fa862809a7ae0c1793c6659a3e3378fded7a121a1c0b3053

Observation 3f390b95-e7c9-4dfd-9aa8-97f2298e48a5 · inbound

Decentralized Min-Max Optimization with Gradient Tracking cites this paper.

Decentralized Min-Max Optimization with Gradient Tracking Jointly Improving the Sample and Communication Complexities in Decentralized Stochastic Minimax Optimization

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T21:14:38.867602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:14:38.867602Z digest=sha256:43698e6188ce1b8cb53ee269a4da1d5b335c4d859a2f20262864d5d7039f6b37