Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits
As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2505.20268.
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 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-26T22:06:24.412259Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T23:39:03.174419Z
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 0b754f7a-d39b-4cc8-9df6-fcd65096b85b · inbound
On the optimization dynamics of RLVR: Gradient gap and step size thresholds cites this paper.
On the optimization dynamics of RLVR: Gradient gap and step size thresholds Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T08:36:07.276562Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation c0716695-dd2f-478e-96b2-7f034332ea94 · inbound
Towards Differentially Private Reinforcement Learning with General Function Approximation cites this paper.
Towards Differentially Private Reinforcement Learning with General Function Approximation Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T04:31:00.541325Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0ca2e471-63fd-473e-96bb-80f75fc32575 · inbound
When Does Trajectory-Level Supervision Permit Efficient Offline Reinforcement Learning? cites this paper.
When Does Trajectory-Level Supervision Permit Efficient Offline Reinforcement Learning? Outcome-Based Online Reinforcement Learning: Algorithms and Fundamental Limits
Reference 7
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-03T23:39:03.177721Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.