Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Boosting Offline Reinforcement Learning via Data Rebalancing
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2210.09241.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T05:09:29.254979Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T14:25:45.854529Z
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 fbf7fc05-7fff-4ef7-a5cd-6f2bbb3f7db7 · inbound
BiTrajDiff: Bidirectional Trajectory Generation with Diffusion Models for Offline Reinforcement Learning cites this paper.
BiTrajDiff: Bidirectional Trajectory Generation with Diffusion Models for Offline Reinforcement Learning Boosting Offline Reinforcement Learning via Data Rebalancing
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T10:52:15.280066Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 912e2045-4ae9-4daa-b764-dd6721502493 · inbound
Offline vs. Online Learning in Model-based RL: Lessons for Data Collection Strategies cites this paper.
Offline vs. Online Learning in Model-based RL: Lessons for Data Collection Strategies Boosting Offline Reinforcement Learning via Data Rebalancing
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T05:09:29.254979Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1984199f-0fb1-41ab-8f4e-e89d1adbc13b · inbound
Peng's Q($\lambda$) for Conservative Value Estimation in Offline Reinforcement Learning cites this paper.
Peng's Q($\lambda$) for Conservative Value Estimation in Offline Reinforcement Learning Boosting Offline Reinforcement Learning via Data Rebalancing
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T14:25:45.856279Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.