Paper Citation Record · LEDGER

Federated Foundation Models on Heterogeneous Time Series

As of 12 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 1 inbound Pith citation observation for arXiv:2412.08906.

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

pith.paper-citation-record.v1
2412.08906 v1

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:31:07.202866Z

measured 51 of 51 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-09T19:14:28.664878Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T15:47:07.680103Z

Reference resolution

50 of 50 outbound references displayed

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verified fuzzy0
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External citation measurements

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Outbound references

Observation cda8cc5b-01cf-45d0-a16f-02b42999ab8a · outbound

This paper cites TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting.

Federated Foundation Models on Heterogeneous Time Series TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T17:31:06.921656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e914685b-a294-4984-8279-a7a5fb421e2e · outbound

This paper cites N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting.

Federated Foundation Models on Heterogeneous Time Series N-HiTS: Neural Hierarchical Interpolation for Time Series Forecasting

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T17:31:06.928101Z

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Observation d5daccd3-66cc-4e11-b805-fde7a5f2f607 · outbound

This paper cites LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters.

Federated Foundation Models on Heterogeneous Time Series LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters

Reference 3

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Observation 32236760-01bc-4187-984f-846993ad8808 · outbound

This paper cites Foundation Models for Weather and Climate Data Understanding: A Comprehensive Survey.

Federated Foundation Models on Heterogeneous Time Series Foundation Models for Weather and Climate Data Understanding: A Comprehensive Survey

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T17:31:06.938426Z

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Observation 8f4b8e90-7caa-402d-b375-f9deaf5dee6e · outbound

This paper cites Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models.

Federated Foundation Models on Heterogeneous Time Series Personalized Adapter for Large Meteorology Model on Devices: Towards Weather Foundation Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T17:31:06.947598Z

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Observation 853fc919-fbaf-4c52-97f2-e8667f1123dd · outbound

This paper cites Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data.

Federated Foundation Models on Heterogeneous Time Series Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data

Reference 6

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Observation 2e811080-5f0e-4138-9a4e-a5e693950dfb · outbound

This paper cites Federated Prompt Learning for Weather Foundation Models on Devices.

Federated Foundation Models on Heterogeneous Time Series Federated Prompt Learning for Weather Foundation Models on Devices

Reference 7

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Observation 3023421d-8f53-4eea-b191-5931ad9d4eb0 · outbound

This paper cites an unresolved cited work.

Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 8

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Observation 1e2eeb96-f853-4687-9015-4b9301f98629 · outbound

This paper cites an unresolved cited work.

Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 9

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This paper cites an unresolved cited work.

Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 10

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 11

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Observation 30ab3d83-2206-4af6-930f-22ef9afaa37a · outbound

This paper cites an unresolved cited work.

Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 12

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Observation c8ffb1a4-b3b1-40b4-a52b-e27023c210bc · outbound

This paper cites A decoder-only foundation model for time-series forecasting.

Federated Foundation Models on Heterogeneous Time Series A decoder-only foundation model for time-series forecasting

Reference 13

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Observation 3f16d302-ce9c-4c65-ac06-977d55fbfab6 · outbound

This paper cites S.; Mohapatra, C.; Naidu, S.

Federated Foundation Models on Heterogeneous Time Series S.; Mohapatra, C.; Naidu, S

Reference 14

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 15

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Observation 508638e7-6adb-4cc4-b4c0-bc4ac1d7dc7e · outbound

This paper cites TimeGPT-1.

Federated Foundation Models on Heterogeneous Time Series TimeGPT-1

Reference 16

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Observation 92344a6f-4167-45e9-8e4d-03e74a39e436 · outbound

This paper cites MOMENT: A Family of Open Time-series Foundation Models.

Federated Foundation Models on Heterogeneous Time Series MOMENT: A Family of Open Time-series Foundation Models

Reference 17

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Observation 574f5dc6-b9e1-4f02-8404-1d41ec7af7aa · outbound

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 18

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Observation 54f053ae-639c-45e5-b5fc-65b2e72f7ee4 · outbound

This paper cites Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.

Federated Foundation Models on Heterogeneous Time Series Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 19

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Observation a83d833d-3929-468d-ac17-66738cf9c34b · outbound

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 20

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Observation 2876205c-77e9-4d79-9f57-b272212bb126 · outbound

This paper cites Reformer: The Efficient Transformer.

Federated Foundation Models on Heterogeneous Time Series Reformer: The Efficient Transformer

Reference 21

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Observation 5e98c44e-3512-47fa-a85d-8c6dd90d2981 · outbound

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 22

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Observation a76bfb55-c0c4-4378-a7e1-9c69c0dd0e78 · outbound

This paper cites K.; Zaheer, M.; Sanjabi, M.; Talwalkar, A.; and Smith, V.

Federated Foundation Models on Heterogeneous Time Series K.; Zaheer, M.; Sanjabi, M.; Talwalkar, A.; and Smith, V

Reference 23

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Observation 52932683-8595-434c-8089-29b1ab53bba5 · outbound

This paper cites Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting.

Federated Foundation Models on Heterogeneous Time Series Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting

Reference 24

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Observation b1b9657e-1405-4631-aeda-330ea45d9196 · outbound

This paper cites X.; and Dustdar, S.

Federated Foundation Models on Heterogeneous Time Series X.; and Dustdar, S

Reference 25

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Observation df826155-aaf4-4538-acb5-1aaaa690dd04 · outbound

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 26

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Observation 3bfa8c82-e241-432a-9422-ac5cf9186dad · outbound

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 27

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Observation 91eb1bfb-a89c-4a7d-b818-4dca1784feb7 · outbound

This paper cites Timer: Generative Pre-trained Transformers Are Large Time Series Models.

Federated Foundation Models on Heterogeneous Time Series Timer: Generative Pre-trained Transformers Are Large Time Series Models

Reference 28

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Observation 33b8e938-fdf7-4c43-9134-ea8206c65614 · outbound

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 29

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Observation b50a8d79-7b1f-4224-b718-22960ba49bef · outbound

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 30

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Observation c61a1286-4908-4660-b451-3c253b0a2082 · outbound

This paper cites A Time Series is Worth 64 Words: Long-term Forecasting with Transformers.

Federated Foundation Models on Heterogeneous Time Series A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 31

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Observation 4cf66254-ea0e-4459-88fd-e93ea482afe1 · outbound

This paper cites N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.

Federated Foundation Models on Heterogeneous Time Series N-BEATS: Neural basis expansion analysis for interpretable time series forecasting

Reference 32

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 33

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Observation 799ca65b-2d95-46ab-8930-05a81e190574 · outbound

This paper cites Federated Distillation for Medical Image Classification: Towards Trustworthy Computer-Aided Diagnosis.

Federated Foundation Models on Heterogeneous Time Series Federated Distillation for Medical Image Classification: Towards Trustworthy Computer-Aided Diagnosis

Reference 34

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Observation cef12d5d-a268-4c78-9352-6d744eb5ec3e · outbound

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 35

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Observation 35a190c7-7fe2-4174-95e6-b851df076241 · outbound

This paper cites an unresolved cited work.

Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 36

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Observation 2ddc6b80-92ee-4749-b0da-53f5ea5f0baa · outbound

This paper cites Unified Training of Universal Time Series Forecasting Transformers.

Federated Foundation Models on Heterogeneous Time Series Unified Training of Universal Time Series Forecasting Transformers

Reference 37

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Observation 41df7eec-2fcb-446c-8542-d57e11280e31 · outbound

This paper cites ETSformer: Exponential Smoothing Transformers for Time-series Forecasting.

Federated Foundation Models on Heterogeneous Time Series ETSformer: Exponential Smoothing Transformers for Time-series Forecasting

Reference 38

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Observation ea5c23f2-c342-46df-9570-ff3571a4296c · outbound

This paper cites TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis.

Federated Foundation Models on Heterogeneous Time Series TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

Reference 39

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 40

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Observation 5c452cbd-62c4-4e85-99b5-a56e86220947 · outbound

This paper cites Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy.

Federated Foundation Models on Heterogeneous Time Series Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy

Reference 41

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 42

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 43

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Observation 080f1bcb-2140-481a-a5cb-83af745d3a77 · outbound

This paper cites Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures.

Federated Foundation Models on Heterogeneous Time Series Less Is More: Fast Multivariate Time Series Forecasting with Light Sampling-oriented MLP Structures

Reference 44

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 45

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Observation bdfa5902-cdae-4ca2-9667-74638adf0591 · outbound

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 46

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Observation 5a2e0d4d-ceb7-4559-b06f-9d488199606d · outbound

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Federated Foundation Models on Heterogeneous Time Series Unresolved cited work

Reference 47

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Observation af9998fe-edcb-4e0e-9fbb-1b3b55dc56a1 · outbound

This paper cites When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions.

Federated Foundation Models on Heterogeneous Time Series When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions

Reference 48

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Observation 77959d10-2e91-45ad-81c1-658405a08af4 · outbound

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Federated Foundation Models on Heterogeneous Time Series , " * write output.state after.block = add.period write newline

Reference 49

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Observation 1a69110c-00f3-4cab-b692-3694cfb7d2a3 · outbound

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Federated Foundation Models on Heterogeneous Time Series write newline

Reference 50

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Pith citing papers

Observation 07204b7e-2494-4507-8369-a99dbede2ceb · inbound

Federated Weather Modeling on Sensor Data cites this paper.

Federated Weather Modeling on Sensor Data Federated Foundation Models on Heterogeneous Time Series

Reference 5

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Source-reported events for the cited work

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