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Paper Citation Record · LEDGER

Learning Representations in Model-Free Hierarchical Reinforcement Learning

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1810.10096.

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

pith.paper-citation-record.v1
1810.10096 v3

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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:18:08.740570Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T05:11:03.111087Z

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 76a0dafd-d6ec-4cc5-b07d-8bf574f4df25 · inbound

Learning sparse representations in reinforcement learning cites this paper.

Learning sparse representations in reinforcement learning Learning Representations in Model-Free Hierarchical Reinforcement Learning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-14T05:18:08.740570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:18:08.740570Z digest=sha256:1835f9adda9a9a9edfe412767b6f618b2b269a52334a93d6a9d772a84ccbc38a

Observation 4bc88f45-e231-4428-bc54-6a8c02da8162 · inbound

Quasi-Newton Optimization Methods For Deep Learning Applications cites this paper.

Quasi-Newton Optimization Methods For Deep Learning Applications Learning Representations in Model-Free Hierarchical Reinforcement Learning

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-14T05:11:03.117555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-14T05:11:02.961196Z digest=sha256:c91dd0f60d052a3ff1303a49848f0135530a0a54891ed707d2754fe478c0d93c