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Paper Citation Record · LEDGER

PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2310.19991.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2310.19991 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T05:17:33.307298Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-12T10:06:29.059625Z

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 9f8a6691-13ec-4db1-8c00-09710167b446 · inbound

Strait: Perceiving Priority and Interference in ML Inference Serving cites this paper.

Strait: Perceiving Priority and Interference in ML Inference Serving PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices

Reference 105

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:06:29.063915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-07T07:50:05.245164Z digest=sha256:cec556f52a0edba246324d24743670fec600d680b6e07701736d8431369a7ebf

Observation 9e40eb3e-456b-45bf-918f-f9c051edc096 · inbound

Formally Verifying Analog Neural Networks Under Process Variations Using Polynomial Zonotopes cites this paper.

Formally Verifying Analog Neural Networks Under Process Variations Using Polynomial Zonotopes PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:06:35.844516Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-05-12T03:43:54.341698Z digest=sha256:054d78c868344ca1d5050717ac69bd0061955a5615f2420307392c5b3387f162

Observation d0681e55-1bed-49af-a100-f38f2b36013e · inbound

Formally Verifying Analog Neural Networks Under Process Variations Using Polynomial Zonotopes cites this paper.

Formally Verifying Analog Neural Networks Under Process Variations Using Polynomial Zonotopes PolyThrottle: Energy-efficient Neural Network Inference on Edge Devices

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-04T05:17:33.307298Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:17:33.307298Z digest=sha256:48b4de35feaeb0854f9d29c5ef3f8d9da2747ecd91e9f3e801cd935dbddd6ce4