Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Computing Within Limits: An Empirical Study of Energy Consumption in ML Training and Inference
As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2406.14328.
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 2026-08-04T06:26:17.122813Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T04:29:34.874762Z
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 9a7b7ffe-8b8d-400f-b109-7c11878128b6 · inbound
Visualising Information Flow in Word Embeddings with Diffusion Tensor Imaging cites this paper.
Visualising Information Flow in Word Embeddings with Diffusion Tensor Imaging Computing Within Limits: An Empirical Study of Energy Consumption in ML Training and Inference
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T06:26:17.122813Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0b17a2ac-aa8c-4ab6-a669-9f5b394f03c8 · inbound
From Cradle to Cloud: A Life Cycle Review of AI's Environmental Footprint cites this paper.
From Cradle to Cloud: A Life Cycle Review of AI's Environmental Footprint Computing Within Limits: An Empirical Study of Energy Consumption in ML Training and Inference
Reference 69
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T18:31:12.947347Z
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.
Observation e4d8276b-fb9a-4133-b8fc-3c4f8683d36e · inbound
The Hidden Environmental Cost of Poor Coding Practices in TensorFlow and Keras Applications: A Study on Resource Leaks and Carbon Emissions cites this paper.
The Hidden Environmental Cost of Poor Coding Practices in TensorFlow and Keras Applications: A Study on Resource Leaks and Carbon Emissions Computing Within Limits: An Empirical Study of Energy Consumption in ML Training and Inference
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T04:29:34.876113Z
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.