Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Energy Efficiency of Training Neural Network Architectures: An Empirical Study
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2302.00967.
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 2026-08-06T15:46:12.158178Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
11
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 4f4c3fea-300e-4138-8144-abad46856b9f · inbound
EBA-AI: Ethics-Guided Bias-Aware AI for Efficient Underwater Image Enhancement and Coral Reef Monitoring cites this paper.
EBA-AI: Ethics-Guided Bias-Aware AI for Efficient Underwater Image Enhancement and Coral Reef Monitoring Energy Efficiency of Training Neural Network Architectures: An Empirical Study
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:46:12.158178Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f1a4b88-27f9-435d-8852-26034dd31492 · inbound
Energy Consumption in Parallel Neural Network Training cites this paper.
Energy Consumption in Parallel Neural Network Training Energy Efficiency of Training Neural Network Architectures: An Empirical Study
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T21:59:28.579827Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9e11e736-f4a3-4869-b0b4-d91ad2f85041 · inbound
LIFE -- an energy efficient advanced continual learning agentic AI framework for frontier systems cites this paper.
LIFE -- an energy efficient advanced continual learning agentic AI framework for frontier systems Energy Efficiency of Training Neural Network Architectures: An Empirical Study
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T15:50:33.775404Z
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.