Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Resolving Discrepancies in Compute-Optimal Scaling of Language Models
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2406.19146.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:56:44.065789Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T08:24:26.777027Z
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 67dd0421-289c-416f-89ea-365cd9570f7d · inbound
LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws cites this paper.
LLMs on the Line: Data Determines Loss-to-Loss Scaling Laws Resolving Discrepancies in Compute-Optimal Scaling of Language Models
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T02:52:27.048190Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3655e6a8-347f-4e19-8a15-b59acbea6277 · inbound
Sub-Scaling Laws: On the Role of Data Density and Training Strategies in LLMs cites this paper.
Sub-Scaling Laws: On the Role of Data Density and Training Strategies in LLMs Resolving Discrepancies in Compute-Optimal Scaling of Language Models
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:56:44.065789Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 33c67b5a-9d66-4a3c-abb8-35214a292016 · inbound
The Art of Scaling Reinforcement Learning Compute for LLMs cites this paper.
The Art of Scaling Reinforcement Learning Compute for LLMs Resolving Discrepancies in Compute-Optimal Scaling of Language Models
Reference 16
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-16T16:29:14.020476Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 476b2924-8eda-4b34-8fd6-bcd00ef32e7f · inbound
Deriving Neural Scaling Laws from the statistics of natural language cites this paper.
Deriving Neural Scaling Laws from the statistics of natural language Resolving Discrepancies in Compute-Optimal Scaling of Language Models
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T03:40:04.086576Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d1f9fc82-2e64-42e7-a7ae-822593694116 · inbound
Scaling Laws for Mixture Pretraining Under Data Constraints cites this paper.
Scaling Laws for Mixture Pretraining Under Data Constraints Resolving Discrepancies in Compute-Optimal Scaling of Language Models
Reference 49
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-14T21:48:00.928165Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0d3ff1a0-82a2-4c11-8b99-2105eb2b147b · inbound
Mix, Don't Tune: Bilingual Pre-Training Outperforms Hyperparameter Search in Data-Constrained Settings cites this paper.
Mix, Don't Tune: Bilingual Pre-Training Outperforms Hyperparameter Search in Data-Constrained Settings Resolving Discrepancies in Compute-Optimal Scaling of Language Models
Reference 19
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-14T20:19:27.501686Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 787c5515-67ed-498e-a9cb-6ed590107e5b · 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 Resolving Discrepancies in Compute-Optimal Scaling of Language Models
Reference 19
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-29T08:33:14.783193Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9b75355a-6218-459a-b27a-92394c8be7e1 · 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 Resolving Discrepancies in Compute-Optimal Scaling of Language Models
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T12:58:43.631762Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 70f0f246-979c-4d3a-9506-8d9675bd2dab · inbound
On the Nonlinearity of Learning Rate Scaling for LLM Training cites this paper.
On the Nonlinearity of Learning Rate Scaling for LLM Training Resolving Discrepancies in Compute-Optimal Scaling of Language Models
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T08:24:26.779384Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.