Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Scaling Parameter-Constrained Language Models with Quality Data
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.03083.
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 2026-08-06T11:59:52.166832Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T11:18:13.578024Z
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 f5b23fb9-4805-4d89-8d05-f9945896ddbb · inbound
Using Scaling Laws for Data Source Utility Estimation in Domain-Specific Pre-Training cites this paper.
Using Scaling Laws for Data Source Utility Estimation in Domain-Specific Pre-Training Scaling Parameter-Constrained Language Models with Quality Data
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T11:59:52.166832Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 30f21f0c-9a62-465a-89b2-96cff0b0d1e6 · inbound
On the Invariance and Generality of Neural Scaling Laws cites this paper.
On the Invariance and Generality of Neural Scaling Laws Scaling Parameter-Constrained Language Models with Quality Data
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T03:15:56.081878Z
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 b173033b-1076-4c1b-82c5-8d0b2e07bb4e · inbound
QSTRBench: a New Benchmark to Evaluate the Ability of Language Models to Reason with Qualitative Spatial and Temporal Calculi cites this paper.
QSTRBench: a New Benchmark to Evaluate the Ability of Language Models to Reason with Qualitative Spatial and Temporal Calculi Scaling Parameter-Constrained Language Models with Quality Data
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T11:18:13.579863Z
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.