Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Compute and Energy Consumption Trends in Deep Learning Inference
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2109.05472.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:51:48.992724Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T21:15:49.390225Z
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 a3a60006-d9f1-4b4d-a26b-c8024ce1c7cf · inbound
Survival of the Cheapest: Cost-Aware Hardware Adaptation for Adversarial Robustness cites this paper.
Survival of the Cheapest: Cost-Aware Hardware Adaptation for Adversarial Robustness Compute and Energy Consumption Trends in Deep Learning Inference
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T21:15:49.393891Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation d451bf7b-1548-498a-b8d2-0ff3e2e5dd27 · inbound
OscNet v1.5: Energy Efficient Hopfield Network on CMOS Oscillators for Image Classification cites this paper.
OscNet v1.5: Energy Efficient Hopfield Network on CMOS Oscillators for Image Classification Compute and Energy Consumption Trends in Deep Learning Inference
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T00:51:48.992724Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 975ceabd-6ae1-42c3-a578-9ded4b81d03b · inbound
Fast Cross-Operator Optimization of Attention Dataflow cites this paper.
Fast Cross-Operator Optimization of Attention Dataflow Compute and Energy Consumption Trends in Deep Learning Inference
Reference 21
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T17:53:05.240294Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.