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Paper Citation Record · LEDGER

Timestep-Conditioned Transformers for Global Weather Forecasting

As of 15 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2608.06241.

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

pith.paper-citation-record.v1
2608.06241 v1

Coverage vector

measured 26 of 26 reference resolution

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Source: paper_references, paper_reference_links, observed 2026-08-07T11:44:12.186344Z

measured 26 of 26 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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Reference resolution

26 of 26 outbound references displayed

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External citation measurements

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Outbound references

Observation 9f3a4057-1d61-422a-8977-2446d3c31a75 · outbound

This paper cites Skillful joint probabilistic weather forecasting from marginals.

Timestep-Conditioned Transformers for Global Weather Forecasting Skillful joint probabilistic weather forecasting from marginals

Reference 1

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Observation 5cf52ccf-c22d-4805-8ce4-790a3415d2ad · outbound

This paper cites GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations.

Timestep-Conditioned Transformers for Global Weather Forecasting GraphDOP: Towards skilful data-driven medium-range weather forecasts learnt and initialised directly from observations

Reference 2

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This paper cites an unresolved cited work.

Timestep-Conditioned Transformers for Global Weather Forecasting Unresolved cited work

Reference 3

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Observation 7b62630b-77f6-4874-b0bd-3df69e4c56d3 · outbound

This paper cites FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale.

Timestep-Conditioned Transformers for Global Weather Forecasting FourCastNet 3: A geometric approach to probabilistic machine-learning weather forecasting at scale

Reference 4

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Observation badb5745-c8ea-42b4-bf35-246704bb22a5 · outbound

This paper cites an unresolved cited work.

Timestep-Conditioned Transformers for Global Weather Forecasting Unresolved cited work

Reference 5

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Observation a76bc181-1e5a-47db-9ab4-0e42f7f7bfca · outbound

This paper cites an unresolved cited work.

Timestep-Conditioned Transformers for Global Weather Forecasting Unresolved cited work

Reference 6

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Observation 57452666-8251-463c-bf11-3438a324e252 · outbound

This paper cites ArchesWeather & ArchesWeatherGen: a deterministic and generative model for efficient ML weather forecasting.

Timestep-Conditioned Transformers for Global Weather Forecasting ArchesWeather & ArchesWeatherGen: a deterministic and generative model for efficient ML weather forecasting

Reference 7

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Observation 35905218-dc01-4232-8e31-e8363ab64ebb · outbound

This paper cites Hassani, S.

Timestep-Conditioned Transformers for Global Weather Forecasting Hassani, S

Reference 8

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Observation e7ed2826-adec-4eea-9f90-dd1b71f2774f · outbound

This paper cites Jordan, Y.

Timestep-Conditioned Transformers for Global Weather Forecasting Jordan, Y

Reference 9

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Observation 16c9d254-88fc-4036-95a6-5c33001bbcf3 · outbound

This paper cites Forecasting Global Weather with Graph Neural Networks.

Timestep-Conditioned Transformers for Global Weather Forecasting Forecasting Global Weather with Graph Neural Networks

Reference 10

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Observation df617a2b-bb5d-4407-be3f-3f3a049d890c · outbound

This paper cites Kochkov, J.

Timestep-Conditioned Transformers for Global Weather Forecasting Kochkov, J

Reference 11

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Observation a674a1f9-0f34-4584-b662-c12b0c0c8a19 · outbound

This paper cites Kossaifi, N.

Timestep-Conditioned Transformers for Global Weather Forecasting Kossaifi, N

Reference 12

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Timestep-Conditioned Transformers for Global Weather Forecasting Unresolved cited work

Reference 13

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Observation aeac2759-79e4-483d-8740-e39c6fe46bc3 · outbound

This paper cites AIFS -- ECMWF's data-driven forecasting system.

Timestep-Conditioned Transformers for Global Weather Forecasting AIFS -- ECMWF's data-driven forecasting system

Reference 14

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Observation fd7b6908-bed2-4e3d-a8e3-e2add1794895 · outbound

This paper cites Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts.

Timestep-Conditioned Transformers for Global Weather Forecasting Can AI Weather Models Predict Beyond Two Weeks? A Quantitative Benchmark and Analysis of Long Rollouts

Reference 15

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Observation ca2074f3-8aaa-4788-87bc-03f0bea86940 · outbound

This paper cites Muon is Scalable for LLM Training.

Timestep-Conditioned Transformers for Global Weather Forecasting Muon is Scalable for LLM Training

Reference 16

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Observation 4196635a-0e2c-477b-990f-9e245dbfdbad · outbound

This paper cites Nguyen, J.

Timestep-Conditioned Transformers for Global Weather Forecasting Nguyen, J

Reference 17

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Observation 84177b30-fdd9-494b-a712-63688d0cf124 · outbound

This paper cites Nguyen, T.

Timestep-Conditioned Transformers for Global Weather Forecasting Nguyen, T

Reference 18

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Observation 7df30323-1e8b-4af9-9d92-3c9c7b2520ee · outbound

This paper cites FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators.

Timestep-Conditioned Transformers for Global Weather Forecasting FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 19

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Observation 4ef5d5de-c688-4238-bd40-b10f8feda1b4 · outbound

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Timestep-Conditioned Transformers for Global Weather Forecasting Peebles and S

Reference 20

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Observation f18b15b7-8b23-412d-88bc-c7750c1086f0 · outbound

This paper cites GenCast: Diffusion-based ensemble forecasting for medium-range weather.

Timestep-Conditioned Transformers for Global Weather Forecasting GenCast: Diffusion-based ensemble forecasting for medium-range weather

Reference 21

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Observation b6e99ce0-6e99-4600-a207-501f34091f00 · outbound

This paper cites Price, A.

Timestep-Conditioned Transformers for Global Weather Forecasting Price, A

Reference 22

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Observation 49e4e1a4-6d57-4a22-928b-7dcc64fe75bb · outbound

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Timestep-Conditioned Transformers for Global Weather Forecasting Rauba, V

Reference 23

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Timestep-Conditioned Transformers for Global Weather Forecasting Stock, T

Reference 24

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Timestep-Conditioned Transformers for Global Weather Forecasting Unresolved cited work

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Timestep-Conditioned Transformers for Global Weather Forecasting Unresolved cited work

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