Paper Citation Record · LEDGER

Reconciling Kaplan and Chinchilla Scaling Laws

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2406.12907.

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

pith.paper-citation-record.v1
2406.12907 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:21:06.764274Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T22:17:25.639716Z

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 c0f8769d-cd31-4e69-b33a-7bc9f6b1a6f8 · inbound

Safety case template for frontier AI: A cyber inability argument cites this paper.

Safety case template for frontier AI: A cyber inability argument Reconciling Kaplan and Chinchilla Scaling Laws

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-12T22:01:11.502440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5fc80514-aad9-4313-a44b-c19eae6c2c88 · inbound

Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient cites this paper.

Joint MoE Scaling Laws: Mixture of Experts Can Be Memory Efficient Reconciling Kaplan and Chinchilla Scaling Laws

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T20:06:23.559291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5be144fc-b5ef-41b9-bb18-d0db1e2f5d94 · inbound

Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks cites this paper.

Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks Reconciling Kaplan and Chinchilla Scaling Laws

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T20:48:53.523148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5459d24b-1b93-4b2f-a4ba-05661d88294c · inbound

Meek Models Shall Inherit the Earth cites this paper.

Meek Models Shall Inherit the Earth Reconciling Kaplan and Chinchilla Scaling Laws

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T18:33:49.753030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27abd2b6-a631-4563-bf5d-8cddd35aee25 · inbound

Signal and Noise: A Framework for Reducing Uncertainty in Language Model Evaluation cites this paper.

Signal and Noise: A Framework for Reducing Uncertainty in Language Model Evaluation Reconciling Kaplan and Chinchilla Scaling Laws

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T17:21:06.764274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 470be790-5a77-439e-8a6b-0d7c76fb44bb · inbound

From Zipf's Law to Neural Scaling through Heaps' Law and Hilberg's Hypothesis cites this paper.

From Zipf's Law to Neural Scaling through Heaps' Law and Hilberg's Hypothesis Reconciling Kaplan and Chinchilla Scaling Laws

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-03T16:34:39.029708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a0a2a55-f086-4f3e-99ee-2599278a85ee · inbound

Tempus: A Temporally Scalable Resource-Invariant GEMM Streaming Framework for Versal AI Edge cites this paper.

Tempus: A Temporally Scalable Resource-Invariant GEMM Streaming Framework for Versal AI Edge Reconciling Kaplan and Chinchilla Scaling Laws

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:51:42.156510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ddf50cc3-a215-4cf5-8906-7c4d94f13ac6 · inbound

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions cites this paper.

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions Reconciling Kaplan and Chinchilla Scaling Laws

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-06-29T08:33:14.808956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b1390d29-5f1a-45af-9dbe-31c58c5394ba · inbound

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions cites this paper.

How Much Is a Dataset Worth? Scaling Laws, the Vendi Score, and Matrix Spectral Functions Reconciling Kaplan and Chinchilla Scaling Laws

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-02T12:58:43.461300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ffb8759-dd5d-4c00-9c48-4afcc1e94230 · inbound

Scaling Laws for Neural-Network Quantum States cites this paper.

Scaling Laws for Neural-Network Quantum States Reconciling Kaplan and Chinchilla Scaling Laws

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-07-02T01:46:27.083332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0149c990-33ca-44bd-8bd2-61e61e025e49 · inbound

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale cites this paper.

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale Reconciling Kaplan and Chinchilla Scaling Laws

Reference 64

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T22:17:25.641220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f5bd04a6-ca24-4b6f-8adf-e4d91cacc052 · inbound

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling cites this paper.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling Reconciling Kaplan and Chinchilla Scaling Laws

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T12:32:57.276785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.