Pith. sign in

Paper Citation Record · LEDGER

Information-Theoretic Considerations in Batch Reinforcement Learning

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1905.00360.

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

pith.paper-citation-record.v1
1905.00360 v1

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 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:27:42.014837Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T20:26:50.063789Z

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 7904e087-0c57-46d9-9044-4c3d3161e69e · inbound

Neural Policy Gradient Methods: Global Optimality and Rates of Convergence cites this paper.

Neural Policy Gradient Methods: Global Optimality and Rates of Convergence Information-Theoretic Considerations in Batch Reinforcement Learning

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-14T10:27:42.014837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T10:27:42.014837Z digest=sha256:964fdf0b8046339f9995e8543438d720135e7b513c229c8033149b75051c7db8

Observation 61ddd041-b55b-4d1e-932d-44105215db94 · inbound

Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning cites this paper.

Two-way Deconfounder for Off-policy Evaluation in Causal Reinforcement Learning Information-Theoretic Considerations in Batch Reinforcement Learning

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-08-11T20:26:50.069475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-11T20:26:49.073582Z digest=sha256:00d564d8cb65755a4fce08785cf7544210d0ee7a9e968af5f53de787ddca4bc6