Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Loss-to-Loss Prediction: Scaling Laws for All Datasets
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2411.12925.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:47:51.739078Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T02:52:27.116228Z
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 301b63cf-4ca6-43db-9fd3-45446de0fef7 · 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 Loss-to-Loss Prediction: Scaling Laws for All Datasets
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T02:52:27.118254Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 7d601040-612c-4bf7-82fb-444c1c6d7747 · inbound
Characterization and Mitigation of Training Instabilities in Microscaling Formats cites this paper.
Characterization and Mitigation of Training Instabilities in Microscaling Formats Loss-to-Loss Prediction: Scaling Laws for All Datasets
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T22:47:51.739078Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7f6d9595-27b7-498f-bc6f-105d6625a25d · inbound
Fast and Simplex: 2-Simplicial Attention in Triton cites this paper.
Fast and Simplex: 2-Simplicial Attention in Triton Loss-to-Loss Prediction: Scaling Laws for All Datasets
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:31:47.679967Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1c69b71e-f28a-42a8-bc81-ee5b518d9a9f · inbound
Language Models Improve When Pretraining Data Matches Target Tasks cites this paper.
Language Models Improve When Pretraining Data Matches Target Tasks Loss-to-Loss Prediction: Scaling Laws for All Datasets
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:53:08.690318Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 390254aa-afba-40f3-a213-37590a99fb04 · inbound
Domain Fine-Tuning FinBERT on Finnish Histopathological Reports: Train-Time Signals and Downstream Correlations cites this paper.
Domain Fine-Tuning FinBERT on Finnish Histopathological Reports: Train-Time Signals and Downstream Correlations Loss-to-Loss Prediction: Scaling Laws for All Datasets
Reference 9
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T11:35:18.719653Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 8d93b66f-50d8-4b03-84ba-f98b0bf73032 · inbound
On the Invariance and Generality of Neural Scaling Laws cites this paper.
On the Invariance and Generality of Neural Scaling Laws Loss-to-Loss Prediction: Scaling Laws for All Datasets
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T03:15:56.088442Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.