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Paper Citation Record · LEDGER

Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2305.03938.

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

pith.paper-citation-record.v1
2305.03938 v2

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 2026-08-10T14:10:55.387153Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T08:57:47.431961Z

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 18d67b15-0b65-4b23-84f4-71b7548b57a3 · inbound

Mathematical analysis of the gradients in deep learning cites this paper.

Mathematical analysis of the gradients in deep learning Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-10T14:10:55.387153Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:10:55.387153Z digest=sha256:bb6f324b8a173b6bbcef4724039944feaf0a963d2ad58ec462fff13191ae424a

Observation c9bcd6b8-5b68-4203-a46f-0721cbb8f4a2 · inbound

On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem cites this paper.

On exploration of an interior mirror descent flow for stochastic nonconvex constrained problem Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-06T15:48:30.436126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:48:30.436126Z digest=sha256:c2a39f3e3de09a4122518ea2e25376ec2351ad40ffb413c4072b331d2a6f271c

Observation e15fddb0-a32e-41cd-8bd9-8fd0a4e26943 · inbound

On convergence rates of subgradient descent on semialgebraic functions cites this paper.

On convergence rates of subgradient descent on semialgebraic functions Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:41:36.779229Z

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.

source=pdf_text observed=2026-05-10T06:38:02.975663Z digest=sha256:b6b0433275440abcc462009b3fea15565097eaee25ad91a0e6b47c4ed5744127

Observation c827a6df-31d6-41aa-b86c-b2dd48b89437 · inbound

Decentralized Stochastic Subgradient-type Methods with Communication Compression for Nonsmooth Nonconvex Optimization cites this paper.

Decentralized Stochastic Subgradient-type Methods with Communication Compression for Nonsmooth Nonconvex Optimization Adam-family Methods for Nonsmooth Optimization with Convergence Guarantees

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-07-03T08:57:47.433477Z

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.

source=pdf_text observed=2026-07-03T08:48:04.553667Z digest=sha256:5a92e0ca76e33de6dce07f09bd53907760692864db9333df8992d459b2bd0df8