Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Scaling Laws for Sparsely-Connected Foundation Models
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2309.08520.
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 2026-08-10T17:20:51.156794Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-08T20:44:48.795871Z
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 60c7d7be-2e56-4d08-a2b4-38c32e4a9efb · inbound
Physics of Skill Learning cites this paper.
Physics of Skill Learning Scaling Laws for Sparsely-Connected Foundation Models
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T17:20:51.156794Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a16b1939-9604-4793-952f-8c496c0761c2 · inbound
QuEST: Stable Training of LLMs with 1-Bit Weights and Activations cites this paper.
QuEST: Stable Training of LLMs with 1-Bit Weights and Activations Scaling Laws for Sparsely-Connected Foundation Models
Reference 13
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-08T20:44:48.799372Z
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 b58cbc9d-c761-451e-aa26-f54b78697daf · inbound
MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference cites this paper.
MXSens: Sensitivity-Aware Mixed-Precision Quantization for Efficient LLM Inference Scaling Laws for Sparsely-Connected Foundation Models
Reference 83
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T17:12:35.695223Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.