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Paper Citation Record · LEDGER

Full deep neural network training on a pruned weight budget

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1806.06949.

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

pith.paper-citation-record.v1
1806.06949 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:16:42.135559Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T09:16:06.540094Z

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 f091178e-2f58-42ea-bcab-d9738141dc0e · inbound

Accelerated CNN Training Through Gradient Approximation cites this paper.

Accelerated CNN Training Through Gradient Approximation Full deep neural network training on a pruned weight budget

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-14T13:16:42.135559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:16:42.135559Z digest=sha256:d6e668b8d2628adce3c75cb73fcb450a6b8bb2f1396ab3755fca65571e5a33b4

Observation 6e0da1ec-11c4-4870-842b-4d929c859f5c · inbound

Competitive plasticity to reduce the energetic costs of learning cites this paper.

Competitive plasticity to reduce the energetic costs of learning Full deep neural network training on a pruned weight budget

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-24T09:16:06.543061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-24T09:14:33.037303Z digest=sha256:726a9af8d3df04c801cb1cbedcaa4f1b6771705366539ed919f72eeae1a40450