Paper Citation Record · LEDGER

Revisiting the Minimalist Approach to Offline Reinforcement Learning

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2305.09836.

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

pith.paper-citation-record.v1
2305.09836 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T11:01:33.933425Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T07:51:16.626435Z

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 e93d6353-2fa9-4423-ab1c-f0619dffc6d6 · inbound

Value Flows cites this paper.

Value Flows Revisiting the Minimalist Approach to Offline Reinforcement Learning

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-04T11:01:33.933425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d619b10-8368-4f73-a930-90479d29d469 · inbound

Long-Horizon Q-Learning: Accurate Value Learning via n-Step Inequalities cites this paper.

Long-Horizon Q-Learning: Accurate Value Learning via n-Step Inequalities Revisiting the Minimalist Approach to Offline Reinforcement Learning

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:41:07.949401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ca759100-b47d-4607-8893-591603c2495c · inbound

Long-Horizon Q-Learning: Accurate Value Learning via n-Step Inequalities cites this paper.

Long-Horizon Q-Learning: Accurate Value Learning via n-Step Inequalities Revisiting the Minimalist Approach to Offline Reinforcement Learning

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:41:24.766345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 990e4c5e-04d6-4a26-940c-ba6d3b720a6e · inbound

RankQ: Offline-to-Online Reinforcement Learning via Self-Supervised Action Ranking cites this paper.

RankQ: Offline-to-Online Reinforcement Learning via Self-Supervised Action Ranking Revisiting the Minimalist Approach to Offline Reinforcement Learning

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:37:08.180692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a0bd2cc3-7b94-46b1-9f37-a7f338af5164 · inbound

RankQ: Offline-to-Online Reinforcement Learning via Self-Supervised Action Ranking cites this paper.

RankQ: Offline-to-Online Reinforcement Learning via Self-Supervised Action Ranking Revisiting the Minimalist Approach to Offline Reinforcement Learning

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-21T08:54:05.812498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 961bcf7d-6779-45d9-80f6-d5ab4545ef13 · inbound

Abstraction for Offline Goal-Conditioned Reinforcement Learning cites this paper.

Abstraction for Offline Goal-Conditioned Reinforcement Learning Revisiting the Minimalist Approach to Offline Reinforcement Learning

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-22T07:51:16.629858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.