Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2405.07637.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T00:08:08.503214Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T23:29:02.935467Z
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 699927c1-cb2f-4ee0-9007-a75377c529d0 · inbound
Near-optimal Regret Using Policy Optimization in Online MDPs with Aggregate Bandit Feedback cites this paper.
Near-optimal Regret Using Policy Optimization in Online MDPs with Aggregate Bandit Feedback Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T00:08:08.503214Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8998aaef-1560-4dc3-926c-2f66599e2a49 · inbound
Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits cites this paper.
Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:10:39.669228Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2235d6ee-d481-4f4f-9947-cf2a99a962ec · inbound
When Does Trajectory-Level Supervision Permit Efficient Offline Reinforcement Learning? cites this paper.
When Does Trajectory-Level Supervision Permit Efficient Offline Reinforcement Learning? Near-Optimal Regret in Linear MDPs with Aggregate Bandit Feedback
Reference 73
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T23:29:02.936716Z
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.