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Paper Citation Record · LEDGER

An Efficient On-Policy Deep Learning Framework for Stochastic Optimal Control

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.05163.

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

pith.paper-citation-record.v1
2410.05163 v3

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

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T13:09:37.388826Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T00:14:27.738429Z

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 61f9a66e-e4ff-4bb6-abec-f434e721da53 · inbound

Stein Diffusion Guidance: Training-Free Posterior Correction for Sampling Beyond High-Density Regions cites this paper.

Stein Diffusion Guidance: Training-Free Posterior Correction for Sampling Beyond High-Density Regions An Efficient On-Policy Deep Learning Framework for Stochastic Optimal Control

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-05-22T00:14:27.741325Z

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=arxiv_source observed=2026-05-22T00:13:51.383775Z digest=sha256:0ed861dc36ee1261e80f960f46a26855df416265779cd77201727d86b91facc0

Observation ac2586a1-7b57-4c08-8560-796af0143350 · inbound

An Effective Particle Gradient Projection Method for Solving Stochastic and Mean Field Control Problem cites this paper.

An Effective Particle Gradient Projection Method for Solving Stochastic and Mean Field Control Problem An Efficient On-Policy Deep Learning Framework for Stochastic Optimal Control

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-11T00:50:50.419180Z

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=2026-05-10T18:18:20.121201Z digest=sha256:9a7ccfce6d3ae7649f2fe9401c48adb809c30e0630803d9a866b016d26604afa

Observation ec253e27-dca1-4af2-b925-0de4d41d739f · inbound

Neural feedback approximation for stochastic control with degenerate diffusions: error estimates and numerical analysis cites this paper.

Neural feedback approximation for stochastic control with degenerate diffusions: error estimates and numerical analysis An Efficient On-Policy Deep Learning Framework for Stochastic Optimal Control

Reference 26

Resolution
unresolved
no resolver link, observed 2026-07-14T13:09:37.388826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T13:09:37.388826Z digest=sha256:e5b947544c264c9aa39247f85ce054b32708d14555e715d279b22c2b984ef639