Pith. sign in

Paper Citation Record · LEDGER

A Capacity Scaling Law for Artificial Neural Networks

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1708.06019.

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

pith.paper-citation-record.v1
1708.06019 v3

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 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:21:06.522469Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T18:28:51.367963Z

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 cf2fa5cc-0f7f-4673-9647-7e26aa5910a5 · inbound

The Capacity of Quantum Neural Networks cites this paper.

The Capacity of Quantum Neural Networks A Capacity Scaling Law for Artificial Neural Networks

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-14T15:21:06.522469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:21:06.522469Z digest=sha256:ff972968651a5585be02d607e9b6d05106feeb29e9b165841be36869e3250762

Observation 234255ad-9363-48be-b16a-977d815ee1b8 · inbound

Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering cites this paper.

Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering A Capacity Scaling Law for Artificial Neural Networks

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-12T18:28:51.467626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-12T18:28:47.322643Z digest=sha256:bbb37480bf5ed5fd19515a509cf7324620df085632d9d91597e495aacb0458f5