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Paper Citation Record · LEDGER

How to Leverage Unlabeled Data in Offline Reinforcement Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2202.01741.

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

pith.paper-citation-record.v1
2202.01741 v4

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 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:02:13.337362Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T04:42:52.833456Z

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 c68e7379-2819-4c1f-84e0-90d1c502ce2b · inbound

VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training cites this paper.

VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training How to Leverage Unlabeled Data in Offline Reinforcement Learning

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-15T04:42:52.836495Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T04:42:52.627166Z digest=sha256:5f5bc0f26a0d6bc7a2725d1cc1ae37d7af9dfe06935c8b966e3d3768113d3ed7

Observation 4a6b2247-a7b6-4c53-8a33-62eec05ac09a · inbound

Learning from Active Human Involvement through Proxy Value Propagation cites this paper.

Learning from Active Human Involvement through Proxy Value Propagation How to Leverage Unlabeled Data in Offline Reinforcement Learning

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-09T05:02:13.337362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T05:02:13.337362Z digest=sha256:aee51a44651b21a865727d05918dbd8241a2a0b5d4fd3c159271bd9dddb02d99

Observation a434c5ef-29ce-4767-afae-38d6881c0c75 · inbound

Reinforcement Learning: From Algorithms To Foundation Models cites this paper.

Reinforcement Learning: From Algorithms To Foundation Models How to Leverage Unlabeled Data in Offline Reinforcement Learning

Reference 217

Resolution
unresolved
no resolver link, observed 2026-08-01T17:45:17.708685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T17:45:17.708685Z digest=sha256:94618404f5678e81cb714ab21e759086f3d58d2c4a36dc11a7e501dd8bcba7b0