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Paper Citation Record · LEDGER

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting

As of 10 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2509.06311.

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

pith.paper-citation-record.v1
2509.06311 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T23:57:19.800583Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-03T17:59:38.427560Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T18:08:45.601746Z

Reference resolution

40 of 40 outbound references displayed

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External citation measurements

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Outbound references

Observation ca1e4e94-41c8-436d-be4b-c01872e6b00d · outbound

This paper cites Kronos: A Foundation Model for the Language of Financial Markets.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Kronos: A Foundation Model for the Language of Financial Markets

Reference 1

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Observation e0c3e197-b638-4c99-8321-2b6944591867 · outbound

This paper cites Image and Video Tokenization with Binary Spherical Quantization.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Image and Video Tokenization with Binary Spherical Quantization

Reference 2

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Observation fe512b93-21aa-4a66-ac9c-d1b067709c97 · outbound

This paper cites Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation

Reference 3

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Observation 6fb37cf8-1ded-4252-abed-1c8d9f2e68c1 · outbound

This paper cites Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges,

Reference 4

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Observation fb30ca48-6000-407c-bf41-d19dcf1e171d · outbound

This paper cites The wind integration national dataset (wind) toolkit,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting The wind integration national dataset (wind) toolkit,

Reference 5

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Observation 113f628f-425c-4e7b-bab8-3509a726d572 · outbound

This paper cites Global wind report 2024,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Global wind report 2024,

Reference 6

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Observation 5e08e1c3-7252-41f2-ade3-a4189996f42e · outbound

This paper cites WWEA annual report 2024: A challenging year for windpower,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting WWEA annual report 2024: A challenging year for windpower,

Reference 7

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Observation 796b8ddc-b0b8-44f5-bdba-996e1a0bc774 · outbound

This paper cites A survey on wind power forecasting with machine learning approaches,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting A survey on wind power forecasting with machine learning approaches,

Reference 8

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Observation ef37bb81-8108-4a2f-9bde-dafb4afd9097 · outbound

This paper cites Deep learning model-transformer based wind power forecasting approach,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Deep learning model-transformer based wind power forecasting approach,

Reference 9

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Observation db29e85e-e44e-4c92-a984-6592c44adc46 · outbound

This paper cites Chronos: Learning the Language of Time Series.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Chronos: Learning the Language of Time Series

Reference 10

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Observation 875d2aba-456f-433a-a8df-83e318b7f895 · outbound

This paper cites Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Time-MoE: Billion-Scale Time Series Foundation Models with Mixture of Experts

Reference 11

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Observation 5b1675bc-3a69-4923-86d7-1362905f4fa2 · outbound

This paper cites Temporal collaborative attention for wind power forecasting,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Temporal collaborative attention for wind power forecasting,

Reference 12

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Observation 823fe82b-8f5a-4155-8d80-e928d9c90666 · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 13

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Observation 977f8199-3536-44ed-9191-c6543795d952 · outbound

This paper cites Fedformer: Frequency enhanced de- composed transformer for long-term series forecasting,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Fedformer: Frequency enhanced de- composed transformer for long-term series forecasting,

Reference 14

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Observation 8e6f6693-20e3-4d5a-8da3-fc92e761108c · outbound

This paper cites Timexer: Empowering transformers for time series forecasting with exogenous variables,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Timexer: Empowering transformers for time series forecasting with exogenous variables,

Reference 15

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Observation b03f8001-ba99-4da6-b666-6cd4fe0482b2 · outbound

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

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting A Time Series is Worth 64 Words: Long-term Forecasting with Transformers

Reference 16

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Observation fb071a29-6b17-4c27-a9b6-55812442d2fd · outbound

This paper cites Non-stationary transformers: Exploring the stationarity in time series forecasting,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Non-stationary transformers: Exploring the stationarity in time series forecasting,

Reference 17

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Observation d3b01e61-8f9a-4c95-ab0c-15c19b6ca1fa · outbound

This paper cites TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting

Reference 18

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Observation 1bd22d54-a8d0-4baa-876a-d395e9784067 · outbound

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

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis

Reference 19

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Observation fe084aea-fdcb-4a39-96b5-9f8d5a72a5de · outbound

This paper cites Are transformers effective for time series forecasting?.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Are transformers effective for time series forecasting?

Reference 20

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Observation 3c7ce6ad-5008-41ff-8485-46ec99e2ac62 · outbound

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

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting MOMENT: A Family of Open Time-series Foundation Models

Reference 21

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Observation 155ce11b-48f0-4cb2-bed5-260bd892080b · outbound

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

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting A decoder-only foundation model for time-series forecasting,

Reference 22

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Observation a945e6dd-3d27-47f8-b90e-526f2865ca68 · outbound

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

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Unified Training of Universal Time Series Forecasting Transformers

Reference 23

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Observation 49e450a3-44f1-45ba-aa11-8a94e6cb0bfd · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Roformer: Enhanced transformer with rotary position embedding,

Reference 24

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Observation 17fe73f3-59ce-4e25-ab0c-7528612115a7 · outbound

This paper cites On layer normalization in the trans- former architecture,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting On layer normalization in the trans- former architecture,

Reference 25

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Observation f7aca0ed-7a89-4e2d-b80e-08346c1e881d · outbound

This paper cites Root mean square layer normalization,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Root mean square layer normalization,

Reference 26

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Observation 9de8f9ac-0220-4ee4-afb1-8fc830db864e · outbound

This paper cites Decoupled Weight Decay Regularization.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Decoupled Weight Decay Regularization

Reference 27

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Observation b8621331-7a03-4bb3-a524-a76d03ddc87e · outbound

This paper cites Empower pre-trained large language models for building-level load forecasting,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Empower pre-trained large language models for building-level load forecasting,

Reference 28

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Observation 18e2c04c-9535-4410-a300-3eec8cfdf714 · outbound

This paper cites Exploring the capabilities and limitations of large language models in the electric energy sector,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Exploring the capabilities and limitations of large language models in the electric energy sector,

Reference 29

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Observation 73f013b3-f79c-4411-aa39-3d93c65ba9d4 · outbound

This paper cites High and low frequency wind power prediction based on transformer and bigru-attention,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting High and low frequency wind power prediction based on transformer and bigru-attention,

Reference 30

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Observation 62a9ee3a-5bb2-4b0a-97d3-2c20c92cd203 · outbound

This paper cites Multi-source and temporal attention network for probabilistic wind power prediction,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Multi-source and temporal attention network for probabilistic wind power prediction,

Reference 31

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 9175d61b-d5c4-439e-8b9e-126835568e1c · outbound

This paper cites Augmented convolutional network for wind power prediction: A new recurrent architecture design with spatial- temporal image inputs,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Augmented convolutional network for wind power prediction: A new recurrent architecture design with spatial- temporal image inputs,

Reference 32

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Observation e6b26f3f-7cab-42d5-83bf-b09c895da5b6 · outbound

This paper cites Eplus-llm: A large language model- based computing platform for automated building energy modeling,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Eplus-llm: A large language model- based computing platform for automated building energy modeling,

Reference 33

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Observation 94b5931f-aaed-4e92-bace-85257b602fa5 · outbound

This paper cites Continuous and distribution-free probabilistic wind power forecasting: A conditional normalizing flow approach,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Continuous and distribution-free probabilistic wind power forecasting: A conditional normalizing flow approach,

Reference 34

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-04T23:57:19.784145Z digest=sha256:51f5198ebfb1e45d3ae0323a9faa25c3cf1ff1c9b4493e8ab5f30b03737726e4

Observation 6c1964c3-6dc2-4065-84e9-e37003b3ad4c · outbound

This paper cites A novel frequency-domain physics-informed neural network for accurate prediction of 3d spatio-temporal wind fields in wind turbine applications,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting A novel frequency-domain physics-informed neural network for accurate prediction of 3d spatio-temporal wind fields in wind turbine applications,

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-04T23:57:20.009173Z

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Observation e45621c8-db2b-46e0-817f-ef5a5050160a · outbound

This paper cites Bert4st:: Fine-tuning pre-trained large language model for wind power forecasting,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Bert4st:: Fine-tuning pre-trained large language model for wind power forecasting,

Reference 36

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raw_fallback, observed 2026-08-04T23:57:19.998320Z

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Observation cdb34c6c-5a10-4523-8688-44c305d4af7b · outbound

This paper cites PriceFM: Foundation Model for Probabilistic Electricity Price Forecasting.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting PriceFM: Foundation Model for Probabilistic Electricity Price Forecasting

Reference 37

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unresolved
no resolver link, observed 2026-08-04T23:57:19.792239Z

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Unavailable: canonical work link unavailable.

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Observation 672ede25-56ea-4d8f-a38e-1c58782b0cdc · outbound

This paper cites A novel genetic lstm model for wind power forecast,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting A novel genetic lstm model for wind power forecast,

Reference 38

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verified fuzzy
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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation d322bd32-b2e5-4c25-8c7e-62fba02546b4 · outbound

This paper cites Wind power fore- casting enhancement utilizing adaptive quantile function and cnn-lstm: a probabilistic approach,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting Wind power fore- casting enhancement utilizing adaptive quantile function and cnn-lstm: a probabilistic approach,

Reference 39

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verified fuzzy
raw_fallback, observed 2026-08-04T23:57:19.977598Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 99e57520-4118-4e8a-9dd8-ea259832ef06 · outbound

This paper cites A novel photovoltaic power probabilistic forecasting model based on monotonic quantile convolutional neural network and multi-objective optimization,.

WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting A novel photovoltaic power probabilistic forecasting model based on monotonic quantile convolutional neural network and multi-objective optimization,

Reference 40

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verified fuzzy
raw_fallback, observed 2026-08-04T23:57:19.966586Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-04T23:57:19.800583Z digest=sha256:4486126f12bebd42fa586b89d63a4b16259db744a641efdd860b83187d802c69

Pith citing papers

Observation 35a40ea9-9b09-4611-8f59-12a27d953c21 · inbound

UniWind: Toward Unified Day-Ahead Wind Power Forecasting via Physics-Informed State Routing cites this paper.

UniWind: Toward Unified Day-Ahead Wind Power Forecasting via Physics-Informed State Routing WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting

Reference 5

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verified exact
arxiv_id, observed 2026-07-03T18:08:45.603749Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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