Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
An Information Theory of Compute-Optimal Size Scaling, Emergence, and Plateaus in Language Models
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.01243.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T19:33:05.307058Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T06:40:24.954391Z
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 4ad03e50-f14c-4676-bde9-b494977d04a3 · inbound
CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation Learning cites this paper.
CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation Learning An Information Theory of Compute-Optimal Size Scaling, Emergence, and Plateaus in Language Models
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T19:33:05.307058Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f7d8cc1c-0c02-4cea-b347-2c1ea26ab6c9 · inbound
Feature Learning in Linear-Width Two-Layer Networks: Two vs. One Step of Gradient Descent cites this paper.
Feature Learning in Linear-Width Two-Layer Networks: Two vs. One Step of Gradient Descent An Information Theory of Compute-Optimal Size Scaling, Emergence, and Plateaus in Language Models
Reference 219
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T01:32:55.915763Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c09ff053-0a39-4998-b0e1-b02f87cba1ab · inbound
Feature Learning in Linear-Width Two-Layer Networks: Two vs. One Step of Gradient Descent cites this paper.
Feature Learning in Linear-Width Two-Layer Networks: Two vs. One Step of Gradient Descent An Information Theory of Compute-Optimal Size Scaling, Emergence, and Plateaus in Language Models
Reference 219
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T06:40:24.957452Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.