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Paper Citation Record · LEDGER

Scaling Laws for Deep Learning

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2108.07686.

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

pith.paper-citation-record.v1
2108.07686 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:13:07.424428Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:36:56.163999Z

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 a5656490-a8c6-4722-93d1-504f395f8b20 · inbound

CRONOS: Enhancing Deep Learning with Scalable GPU Accelerated Convex Neural Networks cites this paper.

CRONOS: Enhancing Deep Learning with Scalable GPU Accelerated Convex Neural Networks Scaling Laws for Deep Learning

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-25T08:50:32.638854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-05-25T08:50:09.472259Z digest=sha256:1535f5f3be4edd2c4d0de27480281604991f574e68d366d8906a7ac533e0e23b

Observation 6680b5c9-4332-47e4-902b-d10b72e4bf9e · inbound

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI cites this paper.

Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI Scaling Laws for Deep Learning

Reference 83

Resolution
unresolved
no resolver link, observed 2026-08-11T20:13:07.424428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:13:07.424428Z digest=sha256:5ad35be07a87f5e45ecbadb819af586d46226e570354baa738adfc6025b3c20e

Observation 19f8e135-0fc4-4d37-8dbb-42ac1a7bc875 · inbound

Phase Transitions in Large Language Models and the $O(N)$ Model cites this paper.

Phase Transitions in Large Language Models and the $O(N)$ Model Scaling Laws for Deep Learning

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-10T13:42:54.771304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T13:42:54.771304Z digest=sha256:88d406ce44f4483ce7659ac592892475b1d32ebdde3b8227e08420ed21c9a7a1

Observation 63f008db-3ba3-4339-9a0d-85137d6cff62 · inbound

Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks cites this paper.

Bayesian Neural Scaling Law Extrapolation with Prior-Data Fitted Networks Scaling Laws for Deep Learning

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T13:01:10.240133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:01:10.240133Z digest=sha256:9344396f75f2e7f459ec160ca38e4d5cb1f9e39537f56341646f6447f23e4362

Observation 80773bb8-76bf-48ca-a07f-a179b60e6c5d · inbound

Two AI Metrics Diverged: Will it Make All the Difference? cites this paper.

Two AI Metrics Diverged: Will it Make All the Difference? Scaling Laws for Deep Learning

Reference 31

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T12:36:56.165351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-07-02T12:29:24.439779Z digest=sha256:e1e936b5595f9c644c1bcf346312ebb8440f2b0d7bdb9398dc296f2dda38d102