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Paper Citation Record · LEDGER

Deep Reinforcement Learning via L-BFGS Optimization

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1811.02693.

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

pith.paper-citation-record.v1
1811.02693 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 2026-08-14T05:18:08.730528Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T20:20:07.144136Z

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 90eea510-9941-4328-8c95-980f04d59b7e · inbound

Learning sparse representations in reinforcement learning cites this paper.

Learning sparse representations in reinforcement learning Deep Reinforcement Learning via L-BFGS Optimization

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-14T05:18:08.730528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:18:08.730528Z digest=sha256:5bd668a49d755aeff77a38e5d15120466d6ef7a243084d89f9a944cd2a31e885

Observation d1b4acc8-d59a-4ef6-82f8-8ddc08bf8c47 · inbound

Physics-Informed Neural Networks for the Time-Domain Maxwell Equations with Split-Field Perfectly Matched Layers cites this paper.

Physics-Informed Neural Networks for the Time-Domain Maxwell Equations with Split-Field Perfectly Matched Layers Deep Reinforcement Learning via L-BFGS Optimization

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-07-04T20:20:07.145874Z

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=2026-06-25T20:21:59.870759Z digest=sha256:867e1acc6c1bc9a7259b72a748a324409ecf1b087b5dd5837daf28b448d324f7