Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Iroko: A Framework to Prototype Reinforcement Learning for Data Center Traffic Control
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1812.09975.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T15:21:50.553187Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T03:30:51.032781Z
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 3f65f03d-e9c0-4e6b-8269-d58db559c0ac · inbound
A View on Deep Reinforcement Learning in System Optimization cites this paper.
A View on Deep Reinforcement Learning in System Optimization Iroko: A Framework to Prototype Reinforcement Learning for Data Center Traffic Control
Reference 2011
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T15:21:50.553187Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b40ab6b9-29df-44df-aed2-a5ab6769c8c7 · inbound
ConfigTron: Tackling network diversity with heterogeneous configurations cites this paper.
ConfigTron: Tackling network diversity with heterogeneous configurations Iroko: A Framework to Prototype Reinforcement Learning for Data Center Traffic Control
Reference 72
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T13:44:09.527341Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1fb8f6a8-9ab2-47b4-bc75-70b1def0e1b1 · inbound
Glia: A Human-Inspired AI for Automated Systems Design and Optimization cites this paper.
Glia: A Human-Inspired AI for Automated Systems Design and Optimization Iroko: A Framework to Prototype Reinforcement Learning for Data Center Traffic Control
Reference 62
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T03:30:51.035499Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.