Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Scalability Bottlenecks in Multi-Agent Reinforcement Learning Systems
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2302.05007.
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 2026-08-22T06:32:14.747728+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T14:15:43.390034Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T20:40:07.906014Z
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 fc56e9a1-3f97-48e5-b4ff-388e933486a2 · inbound
Intelligent Offloading in Vehicular Edge Computing: A Comprehensive Review of Deep Reinforcement Learning Approaches and Architectures cites this paper.
Intelligent Offloading in Vehicular Edge Computing: A Comprehensive Review of Deep Reinforcement Learning Approaches and Architectures Scalability Bottlenecks in Multi-Agent Reinforcement Learning Systems
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T14:15:43.390034Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c5100255-1511-4acb-8cd4-577d86db9696 · inbound
Rate-Aware Quantum-Inspired Trajectory Learning for Interference-Limited Multi-UAV Networks cites this paper.
Rate-Aware Quantum-Inspired Trajectory Learning for Interference-Limited Multi-UAV Networks Scalability Bottlenecks in Multi-Agent Reinforcement Learning Systems
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T20:40:07.907566Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.