Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecycle
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2303.01980.
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 2026-08-05T21:59:28.450074Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T10:09:45.443803Z
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 ad7c6112-3499-418f-986b-5da523c5078c · inbound
Energy Consumption in Parallel Neural Network Training cites this paper.
Energy Consumption in Parallel Neural Network Training Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecycle
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T21:59:28.450074Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d292e714-5d8d-4a05-bc4e-1114cfa0a617 · inbound
AI Application Benchmarking: Power-Aware Performance Analysis for Vision and Language Models cites this paper.
AI Application Benchmarking: Power-Aware Performance Analysis for Vision and Language Models Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecycle
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T23:54:54.872017Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b0d9fd75-5a0a-4e46-b1e2-d4d3d582cb45 · inbound
The Energy Consumption of Transformer Fine-Tuning: A Roofline-Inspired Scaling Model cites this paper.
The Energy Consumption of Transformer Fine-Tuning: A Roofline-Inspired Scaling Model Towards energy-efficient Deep Learning: An overview of energy-efficient approaches along the Deep Learning Lifecycle
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T10:09:45.445219Z
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.