Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2405.13867.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
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 2026-08-02T09:50:23.904462Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T20:40:07.764274Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation a7284959-9895-417f-bf9a-fb4d18ad47ee · inbound
On the Invariance and Generality of Neural Scaling Laws Scaling-laws for Large Time-series Models
Reference 18
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 104f8075-73ab-495d-a476-d2e71887fbd3 · inbound
The Inference-Compute Frontier and a Latency-Efficient Architecture for Limit Order Book Prediction Scaling-laws for Large Time-series Models
Reference 9
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 de221bc5-c4d0-48e4-8644-e7fbc2b01d24 · inbound
When Do Foundation Models Pay Off? A Break-Even Analysis of Pretrained Time Series Forecasters Scaling-laws for Large Time-series Models
Reference 6
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3266b451-762d-4163-9a63-bcab426e6722 · inbound
Learning Spatio-Temporal Foundation Models from Pure Synthetic Data Scaling-laws for Large Time-series Models
Reference 63
Source-reported events for the cited work
Unavailable: canonical work link unavailable.