Pith. sign in

Paper Citation Record · LEDGER

Lower Bounds for Non-Convex Stochastic Optimization

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1912.02365.

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

pith.paper-citation-record.v1
1912.02365 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:25:45.857333Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T21:22:36.985126Z

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 d1ac6a8a-d3ef-4a6f-a8a6-2f7fe30aeab6 · inbound

Training Deep Learning Models with Norm-Constrained LMOs cites this paper.

Training Deep Learning Models with Norm-Constrained LMOs Lower Bounds for Non-Convex Stochastic Optimization

Reference 154

Resolution
verified exact
arxiv_id, observed 2026-05-21T21:22:36.987752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-21T21:22:36.870292Z digest=sha256:13f1a6f425a273e7d94fd4e9c824ad6089d54efa543a3794e048b0a7a81ad883

Observation de371656-0f81-4e4b-81c8-12ace02e2625 · inbound

Observability conditions for neural state-space models with eigenvalues and their roots of unity cites this paper.

Observability conditions for neural state-space models with eigenvalues and their roots of unity Lower Bounds for Non-Convex Stochastic Optimization

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-16T11:25:45.857333Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:25:45.857333Z digest=sha256:ed49c20f298b9c38196ff25055994c4d3f1111bd584141162d4ae86e6d2dddce

Observation e9e687f1-298e-4ce2-8ed5-7dc8189b02e5 · inbound

What Makes Local Updates Effective: The Role of Data Heterogeneity and Smoothness cites this paper.

What Makes Local Updates Effective: The Role of Data Heterogeneity and Smoothness Lower Bounds for Non-Convex Stochastic Optimization

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T21:27:18.386639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:27:18.386639Z digest=sha256:78995e05a3a4590b0bf0d6c2b21a22cdaab20f6742848a5cd2000c052218cc36