Paper Citation Record · LEDGER

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling

As of 14 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2608.07222.

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

pith.paper-citation-record.v1
2608.07222 v1

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T12:32:57.305972Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

16 of 16 outbound references displayed

verified exact0
verified fuzzy4
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 04b26bc0-6c1b-4fd6-be9e-02c91177dc8c · outbound

This paper cites Chinchilla Scaling: A replication attempt.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling Chinchilla Scaling: A replication attempt

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T12:32:57.240702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d4769d5-cd39-4294-a7c4-8ebb19c379c9 · outbound

This paper cites Differentiatingln|∂L/∂N| and ln|∂L/∂D| gives γN = (1 −k ) β wD and γD = (1 −k ) α wN, soγN /γD = (β/α) (wD/wN ).

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling Differentiatingln|∂L/∂N| and ln|∂L/∂D| gives γN = (1 −k ) β wD and γD = (1 −k ) α wN, soγN /γD = (β/α) (wD/wN )

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:32:57.479722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 755b5046-0fc4-408f-aec7-31f6ec3e78b5 · outbound

This paper cites Distillation Scaling Laws.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling Distillation Scaling Laws

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T12:32:57.249732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2674cee7-764c-40e5-8158-027d93dfa714 · outbound

This paper cites +dom”) fitting versus the default joint L-BFGS fit, for Chinchilla and Skaling on every dataset and grid. Each “+dom.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling +dom”) fitting versus the default joint L-BFGS fit, for Chinchilla and Skaling on every dataset and grid. Each “+dom

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:32:57.458103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9915bbbb-8284-4dd8-96fb-f322b4b0e7ec · outbound

This paper cites For instance, a broadly mistuned grid might artificially dampen the measured interaction or skew the optimal ratio.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling For instance, a broadly mistuned grid might artificially dampen the measured interaction or skew the optimal ratio

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:32:57.469136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ccbfc936-1a76-441c-9e54-57a0a6a87c1a · outbound

This paper cites Resolving Discrepancies in Compute-Optimal Scaling of Language Models.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling Resolving Discrepancies in Compute-Optimal Scaling of Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T12:32:57.280540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a084e13-c8b9-4ce1-a5b7-74bb9534412d · outbound

This paper cites A Constructive Prediction of the Generalization Error Across Scales.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling A Constructive Prediction of the Generalization Error Across Scales

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T12:32:57.284844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdd9b0ac-c09c-4e68-ae6f-f6fec19ce165 · outbound

This paper cites At each grid point, we estimate ∂z/∂x j using two mesh-free procedures: a local moving least-squares estimator (MLS) and a global Gaussian- process estimator (GP).

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling At each grid point, we estimate ∂z/∂x j using two mesh-free procedures: a local moving least-squares estimator (MLS) and a global Gaussian- process estimator (GP)

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T12:32:57.490635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e67906cf-a0dd-4ba7-99cd-56a488ffb3f0 · outbound

This paper cites Predictable Scale: Part II, Farseer: A Refined Scaling Law in Large Language Models.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling Predictable Scale: Part II, Farseer: A Refined Scaling Law in Large Language Models

Reference 1981

Resolution: unresolved; no resolver link, observed 2026-08-10T12:32:57.272146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5457aa2f-e8cb-4770-80a0-6dd228c6d93f · outbound

This paper cites Deep Learning Scaling is Predictable, Empirically.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling Deep Learning Scaling is Predictable, Empirically

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-10T12:32:57.258281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f62fa8cd-a60f-45d7-990f-b03452aaeb6f · outbound

This paper cites Training Compute-Optimal Large Language Models.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling Training Compute-Optimal Large Language Models

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-10T12:32:57.262732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ced49488-87ea-4177-9bba-162d3f2ec2d5 · outbound

This paper cites Scaling Laws for Neural Language Models.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling Scaling Laws for Neural Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-10T12:32:57.267379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites Reconciling Kaplan and Chinchilla Scaling Laws.

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.

Observation 38d75e2c-8956-422d-b27e-8b399c61df8d · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T12:32:57.245565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db8e3b10-7466-4a23-ae11-b1323abb05b1 · outbound

This paper cites The CMA Evolution Strategy: A Tutorial.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling The CMA Evolution Strategy: A Tutorial

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-10T12:32:57.254025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b1b60ca-1c2b-41db-b8f9-0b223161b12d · outbound

This paper cites Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance.

Skaling: Chinchilla's Exponents Meet Kaplan's Coupling Data Mixing Laws: Optimizing Data Mixtures by Predicting Language Modeling Performance

Reference 2026

Resolution: unresolved; no resolver link, observed 2026-08-10T12:32:57.289214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.