Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MIOpen: An Open Source Library For Deep Learning Primitives
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1910.00078.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T00:42:10.585999Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T11:16:09.577764Z
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 f26a0eb5-879d-4f6a-a255-3d3caadd13d0 · inbound
Adding MFMA Support to gem5 cites this paper.
Adding MFMA Support to gem5 MIOpen: An Open Source Library For Deep Learning Primitives
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T00:42:10.585999Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c6dea6d6-cfd9-47e5-a421-1fedca7475e1 · inbound
A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO cites this paper.
A Survey of End-to-End Modeling for Distributed DNN Training: Workloads, Simulators, and TCO MIOpen: An Open Source Library For Deep Learning Primitives
Reference 66
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:57:52.368856Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8eca48f5-0bda-4d7d-8a6a-391063228a90 · inbound
Evaluating Cross-Architecture Performance Modeling of Distributed ML Workloads Using StableHLO cites this paper.
Evaluating Cross-Architecture Performance Modeling of Distributed ML Workloads Using StableHLO MIOpen: An Open Source Library For Deep Learning Primitives
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T11:16:09.581722Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.