Paper Citation Record · LEDGER

Towards Neural Scaling Laws for Time Series Foundation Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.12360.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2410.12360 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T09:50:23.556077Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-20T13:48:19.688014Z

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 9ac79d3d-2df6-42e6-a352-614649c0fa64 · inbound

Discrete Prototypical Memories for Federated Time Series Foundation Models cites this paper.

Discrete Prototypical Memories for Federated Time Series Foundation Models Towards Neural Scaling Laws for Time Series Foundation Models

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T23:35:51.904011Z

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 49a5d50b-5e10-4b94-9d58-ea1bb8106579 · inbound

MaskTab: Scalable Masked Tabular Pretraining with Scaling Laws and Distillation for Industrial Classification cites this paper.

MaskTab: Scalable Masked Tabular Pretraining with Scaling Laws and Distillation for Industrial Classification Towards Neural Scaling Laws for Time Series Foundation Models

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:47:08.504480Z

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 c6eda297-504d-4683-8092-4a3610b36780 · inbound

How Do Electrocardiogram Models Scale? cites this paper.

How Do Electrocardiogram Models Scale? Towards Neural Scaling Laws for Time Series Foundation Models

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-20T13:48:19.690108Z

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 c186d53f-5251-462e-add7-9f8ce92e424e · inbound

Learning Spatio-Temporal Foundation Models from Pure Synthetic Data cites this paper.

Learning Spatio-Temporal Foundation Models from Pure Synthetic Data Towards Neural Scaling Laws for Time Series Foundation Models

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-02T09:50:23.556077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.