Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
On the Use and Misuse of Absorbing States in Multi-agent Reinforcement Learning
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2111.05992.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:26:24.463573Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T07:17:08.338076Z
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 e46cddb1-2bb6-46be-8458-a9dec95a4095 · inbound
Constrained Optimization of Charged Particle Tracking with Multi-Agent Reinforcement Learning cites this paper.
Constrained Optimization of Charged Particle Tracking with Multi-Agent Reinforcement Learning On the Use and Misuse of Absorbing States in Multi-agent Reinforcement Learning
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:26:24.463573Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5432464d-a88f-4ec2-9ea7-43d2d61ea582 · inbound
Focusing Influence Mechanism for Multi-Agent Reinforcement Learning cites this paper.
Focusing Influence Mechanism for Multi-Agent Reinforcement Learning On the Use and Misuse of Absorbing States in Multi-agent Reinforcement Learning
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T07:17:08.340357Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.