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Paper Citation Record · LEDGER

On Graduated Optimization for Stochastic Non-Convex Problems

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1503.03712.

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

pith.paper-citation-record.v1
1503.03712 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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:56:01.021634Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-20T20:18:59.783919Z

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 f9b478da-b336-40fd-bd59-b00c1e63fe42 · inbound

Regularizing quantum loss landscapes by noise injection cites this paper.

Regularizing quantum loss landscapes by noise injection On Graduated Optimization for Stochastic Non-Convex Problems

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-15T21:56:01.021634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:56:01.021634Z digest=sha256:7800346372d2bb39321e76606e4c14d4441cd9006d3d628f5498be2610b0207b

Observation e917a3e0-01ba-4eee-ace9-532c898ca3c9 · inbound

Global Convergence of Sampling-Based Nonconvex Optimization through Diffusion-Style Smoothing cites this paper.

Global Convergence of Sampling-Based Nonconvex Optimization through Diffusion-Style Smoothing On Graduated Optimization for Stochastic Non-Convex Problems

Reference 92

Resolution
verified exact
local_arxiv, observed 2026-05-20T20:18:59.785620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-05-20T20:15:44.030714Z digest=sha256:a83aae43a9bb97765e6c018f2821ddad75cbed78c7b92f6693b279f2b9a91927