Paper Citation Record · LEDGER

SpectraFM: Tuning into Stellar Foundation Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2411.04750.

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

pith.paper-citation-record.v1
2411.04750 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:22:32.731159Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:20:06.502032Z

Reference resolution

0 of 0 outbound references displayed

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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 513bda4c-ac0e-4f88-8ccc-fd0c5b6b5313 · inbound

From stellar light to astrophysical insight: automating variable star research with machine learning cites this paper.

From stellar light to astrophysical insight: automating variable star research with machine learning SpectraFM: Tuning into Stellar Foundation Models

Reference 101

Resolution: unresolved; no resolver link, observed 2026-08-06T20:22:32.731159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dcab38ba-5415-4aba-acff-a8fd2b088331 · inbound

ABC-SN: Attention Based Classifier for Supernova Spectra cites this paper.

ABC-SN: Attention Based Classifier for Supernova Spectra SpectraFM: Tuning into Stellar Foundation Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T12:08:17.001226Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2b660b02-1e8e-4f28-9fc2-64e9a41d06b8 · inbound

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI cites this paper.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI SpectraFM: Tuning into Stellar Foundation Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T23:02:27.725712Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5fa2643-72a3-48c8-b2a3-addcdca479e6 · inbound

FASTAR -- I. Continuous and differentiable evolutionary stellar population models cites this paper.

FASTAR -- I. Continuous and differentiable evolutionary stellar population models SpectraFM: Tuning into Stellar Foundation Models

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T15:34:47.966337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 881b2ecf-8982-4d49-a22d-96cb4b89e30f · inbound

The Galaxy's Guide to the Tokenizer: A Benchmark for Scientific Foundation Models cites this paper.

The Galaxy's Guide to the Tokenizer: A Benchmark for Scientific Foundation Models SpectraFM: Tuning into Stellar Foundation Models

Reference 9

Resolution: malformed identifier; arxiv_id, observed 2026-07-04T20:20:06.504886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 19b40662-a8e0-4e14-bf34-42df4ada8d22 · inbound

How Low Can We Go? Minimum Spectroscopic Requirements For Supernova Subtype Classification cites this paper.

How Low Can We Go? Minimum Spectroscopic Requirements For Supernova Subtype Classification SpectraFM: Tuning into Stellar Foundation Models

Reference 206

Resolution: unresolved; no resolver link, observed 2026-07-12T01:49:47.560255Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4d618ef-e593-45c1-a7fe-9eeeab73c99e · inbound

Emulation of non-linear 1D spectral models: relativistic X-ray reflection cites this paper.

Emulation of non-linear 1D spectral models: relativistic X-ray reflection SpectraFM: Tuning into Stellar Foundation Models

Reference 127

Resolution: unresolved; no resolver link, observed 2026-07-11T13:33:19.513336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88f566f0-6bfe-45ef-b0bd-0430de1f96d8 · inbound

Microlensing Detection and Inference via Learned Bayes Factors cites this paper.

Microlensing Detection and Inference via Learned Bayes Factors SpectraFM: Tuning into Stellar Foundation Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T10:23:22.574971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e08595c9-1e24-460e-9ce6-82009d59b6fe · inbound

Foundation Models for Astrophysics cites this paper.

Foundation Models for Astrophysics SpectraFM: Tuning into Stellar Foundation Models

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-04T04:31:48.844874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.