Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 1 inbound Pith citation observation for arXiv:2602.15021.

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

pith.paper-citation-record.v1
2602.15021 v2

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Outbound references

Observation 1eaec12a-7dc2-4622-a131-d8465a4206eb · outbound

This paper cites 2022, ApJS, 259, 35, doi: 10.3847/1538-4365/ac4414.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2022, ApJS, 259, 35, doi: 10.3847/1538-4365/ac4414

Reference 1

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Observation 42589543-78f3-445a-87a7-203f513419e5 · outbound

This paper cites 2023, FERRE: Match physical models to measurements, Astrophysics Source Code Library, record ascl:2301.016.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2023, FERRE: Match physical models to measurements, Astrophysics Source Code Library, record ascl:2301.016

Reference 2

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Observation d37473cf-91a4-43b8-ab92-d800810d077b · outbound

This paper cites 2019, MNRAS, 486, 2075, doi: 10.1093/mnras/stz549.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2019, MNRAS, 486, 2075, doi: 10.1093/mnras/stz549

Reference 3

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Observation 1331e9fb-e968-4f2b-b5eb-94d57fbf8ccd · outbound

This paper cites 2020, in Advances in Neural Information Processing Systems, ed.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2020, in Advances in Neural Information Processing Systems, ed

Reference 4

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Observation e194bf55-d6e6-48a3-b257-99e63ec7e24c · outbound

This paper cites Deep Multimodal Representation Learning for Stellar Spectra.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI Deep Multimodal Representation Learning for Stellar Spectra

Reference 5

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Observation fab17f6f-f4c4-4505-9cd6-4ef86c6dcf3c · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 6

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Observation d2c24778-dbd3-4b59-ad47-4c4e6c6bf52d · outbound

This paper cites J., Olsen, K., Economou, F., et al.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI J., Olsen, K., Economou, F., et al

Reference 7

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Observation 93b93ba1-e036-4af3-8613-25c2ff92f955 · outbound

This paper cites M., Rasch, M.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI M., Rasch, M

Reference 8

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Observation 2a1cf8b3-0e52-4f16-938e-925faa3ac8ac · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI LoRA: Low-Rank Adaptation of Large Language Models

Reference 9

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Observation adcbf838-dd07-4a39-9c0b-c74ac3f19549 · outbound

This paper cites C., Xiao, K., et al.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI C., Xiao, K., et al

Reference 10

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Observation 7f549977-8e93-4a55-b47d-468ae9d78d34 · outbound

This paper cites 2021, Computing in Science & Engineering, 23, 15, doi: 10.1109/MCSE.2021.3057097.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2021, Computing in Science & Engineering, 23, 15, doi: 10.1109/MCSE.2021.3057097

Reference 11

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Observation a09781d7-b2bd-4bb9-a2bf-d358dc3d133a · outbound

This paper cites SPARCL: SPectra Analysis and Retrievable Catalog Lab.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI SPARCL: SPectra Analysis and Retrievable Catalog Lab

Reference 12

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

This paper cites SpectraFM: Tuning into Stellar Foundation Models.

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

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Observation 5090b91c-df1b-43e4-9279-94daae52328c · outbound

This paper cites E., Allende Prieto, C., Cooper, A.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI E., Allende Prieto, C., Cooper, A

Reference 14

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Observation 63b41134-346d-49ec-a1cb-3fa4bda45e9d · outbound

This paper cites E., Li, T.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI E., Li, T

Reference 15

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Observation 3567d714-55d5-44b2-96e9-55818f5955a8 · outbound

This paper cites 2024, NIST Atomic Spectra Database, https://physics.nist.gov/asd, Gaithersburg, MD: National Institute of Standards and Technology, doi: 10.18434/T4W30F.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2024, NIST Atomic Spectra Database, https://physics.nist.gov/asd, Gaithersburg, MD: National Institute of Standards and Technology, doi: 10.18434/T4W30F

Reference 16

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Observation 3520774a-05bc-4d58-9fc5-12fd8fe6294f · outbound

This paper cites W., & Bovy, J.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI W., & Bovy, J

Reference 17

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Observation 14590416-d7ba-4a32-9229-c0c4b6e147dc · outbound

This paper cites Visualizing the Loss Landscape of Neural Nets.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI Visualizing the Loss Landscape of Neural Nets

Reference 18

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Observation 4ea94030-613c-4368-a338-2060d343515a · outbound

This paper cites 2022, ApJ, 931, 147, doi: 10.3847/1538-4357/ac6514.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2022, ApJ, 931, 147, doi: 10.3847/1538-4357/ac6514

Reference 19

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Observation dca635c6-144a-40fb-aa2b-357943c5e68e · outbound

This paper cites Decoupled Weight Decay Regularization.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI Decoupled Weight Decay Regularization

Reference 20

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Observation 5615b7e0-7c23-417d-a345-c10f7b5b767d · outbound

This paper cites R., Schiavon, R.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI R., Schiavon, R

Reference 21

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Observation 4c5facaa-ef2c-458f-8cc4-90eb7a862837 · outbound

This paper cites 2015, ApJ, 808, 16, doi: 10.1088/0004-637X/808/1/16.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2015, ApJ, 808, 16, doi: 10.1088/0004-637X/808/1/16

Reference 22

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This paper cites 2020, Astronomy and Computing, 33, 100411, doi: https://doi.org/10.1016/j.ascom.2020.100411.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2020, Astronomy and Computing, 33, 100411, doi: https://doi.org/10.1016/j.ascom.2020.100411

Reference 23

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Observation 53ddeb5e-4195-47c1-abd4-1d2408c13854 · outbound

This paper cites 2024, MNRAS, 531, 4990, doi: 10.1093/mnras/stae1450.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2024, MNRAS, 531, 4990, doi: 10.1093/mnras/stae1450

Reference 24

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Observation 8a94dc41-5121-4be6-a254-1ca0d12cb87e · outbound

This paper cites 2019, in Advances in Neural Information Processing Systems 32 (Curran.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2019, in Advances in Neural Information Processing Systems 32 (Curran

Reference 25

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This paper cites SpecPT (Spectroscopy Pre-trained Transformer) Model for Extragalactic Spectroscopy: I. Architecture and Automated Redshift Measurement.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI SpecPT (Spectroscopy Pre-trained Transformer) Model for Extragalactic Spectroscopy: I. Architecture and Automated Redshift Measurement

Reference 26

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Observation bbc28ebf-27f5-4aa9-b82d-fc20eadbe27c · outbound

This paper cites 2009, WSEAS Transactions on Circuits and Systems, 8, 579.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2009, WSEAS Transactions on Circuits and Systems, 8, 579

Reference 27

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Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI Unresolved cited work

Reference 28

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This paper cites 2019, Language models are unsupervised multitask learners.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2019, Language models are unsupervised multitask learners

Reference 29

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Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI AstroM$^3$: A self-supervised multimodal model for astronomy

Reference 30

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Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI F., et al

Reference 31

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This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 32

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Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI AstroPT: Scaling Large Observation Models for Astronomy

Reference 33

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This paper cites 2016, A&A, 591, A118, doi: 10.1051/0004-6361/201628497.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2016, A&A, 591, A118, doi: 10.1051/0004-6361/201628497

Reference 34

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Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2006, AJ, 132, 1645, doi: 10.1086/506564

Reference 35

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Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2008, PASJ, 60, 1159, doi: 10.1093/pasj/60.5.1159

Reference 36

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Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2019, ApJ, 879, 69, doi: 10.3847/1538-4357/ab2331

Reference 37

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Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI Unresolved cited work

Reference 38

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Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2017, in Advances in Neural Information Processing Systems, ed

Reference 39

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Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2019, ApJS, 245, 34, doi: 10.3847/1538-4365/ab5364

Reference 40

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Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2024, ApJS, 273, 19, doi: 10.3847/1538-4365/ad51dd

Reference 41

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Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2012, Research in Astronomy and Astrophysics, 12, 723, doi: 10.1088/1674-4527/12/7/002

Reference 42

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This paper cites 2025, SpecCLIP v1.0.0: Aligning and Translating Spectroscopic Measurements for Stars, v1.0.0, Zenodo, doi: 10.5281/zenodo.17824840.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2025, SpecCLIP v1.0.0: Aligning and Translating Spectroscopic Measurements for Stars, v1.0.0, Zenodo, doi: 10.5281/zenodo.17824840

Reference 43

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This paper cites Finetuning Stellar Spectra Foundation Models with LoRA.

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

Reference 44

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This paper cites 2025b, arXiv e-prints, arXiv:2507.01939, doi: 10.48550/arXiv.2507.01939.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI 2025b, arXiv e-prints, arXiv:2507.01939, doi: 10.48550/arXiv.2507.01939

Reference 45

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This paper cites R., Heneka, C., et al.

Generalization from Low- to Moderate-Resolution Spectra with Neural Networks for Stellar Parameter Estimation: A Case Study with DESI R., Heneka, C., et al

Reference 46

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Pith citing papers

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Foundation Models for Astrophysics cites this paper.

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

Reference 149

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