Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Designing Rewards for Fast Learning
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2205.15400.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T04:49:16.542411Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T21:17:45.605359Z
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 acdb7612-10c1-4f0b-b002-a87c6acd77e5 · inbound
Optimizing Plastic Waste Collection in Water Bodies Using Heterogeneous Autonomous Surface Vehicles with Deep Reinforcement Learning cites this paper.
Optimizing Plastic Waste Collection in Water Bodies Using Heterogeneous Autonomous Surface Vehicles with Deep Reinforcement Learning Designing Rewards for Fast Learning
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T23:41:05.150853Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4eadafe7-d748-4008-a0d6-8318cd56f562 · inbound
A General Approach of Automated Environment Design for Learning the Optimal Power Flow cites this paper.
A General Approach of Automated Environment Design for Learning the Optimal Power Flow Designing Rewards for Fast Learning
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T04:49:16.542411Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f88d3ae8-ed99-4203-8d96-2eefa5134337 · inbound
Residual Reward Models for Preference-based Reinforcement Learning cites this paper.
Residual Reward Models for Preference-based Reinforcement Learning Designing Rewards for Fast Learning
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T21:17:45.664056Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.