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Paper Citation Record · LEDGER

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models

As of 13 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2412.13627.

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

pith.paper-citation-record.v1
2412.13627 v2

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T12:59:22.211524Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:53:53.926109Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T11:53:54.915250Z

Reference resolution

30 of 30 outbound references displayed

  • verified exact3
  • verified fuzzy7
  • unresolved20
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 88107b25-2918-4640-a750-2e5b1f49f2c1 · outbound

This paper cites an unresolved cited work.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Unresolved cited work

Reference 1

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Observation efb5c1cc-34df-4a98-869e-62b202120dec · outbound

This paper cites Houser, S.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Houser, S

Reference 2

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Observation f1d01b39-9909-48bb-bf04-57a465957344 · outbound

This paper cites an unresolved cited work.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Unresolved cited work

Reference 3

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Observation 6e399a16-4136-4a16-9d81-162cd6b47bb6 · outbound

This paper cites SEC proposes rules to enhance and standardize climate-related disclosures for investors.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models SEC proposes rules to enhance and standardize climate-related disclosures for investors

Reference 4

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Source-reported events for the cited work

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Observation 62aeacfc-f62c-459c-8daa-0bb0220c0317 · outbound

This paper cites an unresolved cited work.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Unresolved cited work

Reference 5

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Observation bcf65e50-6f7a-4023-a5b6-8cfcad1c67d0 · outbound

This paper cites Hersbach, B.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Hersbach, B

Reference 6

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Observation 2448db19-2948-45a9-bd5c-be8b785ebc77 · outbound

This paper cites an unresolved cited work.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Unresolved cited work

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation 53d49cda-5d49-494c-b16a-8059c1c1ae12 · outbound

This paper cites an unresolved cited work.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Unresolved cited work

Reference 8

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Source-reported events for the cited work

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Observation d2186855-0efd-4fc0-b3f1-92282da64746 · outbound

This paper cites A Multi-Scale Deep Learning Framework for Projecting Weather Extremes.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models A Multi-Scale Deep Learning Framework for Projecting Weather Extremes

Reference 9

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Source-reported events for the cited work

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Observation bf79aab0-dc80-4e83-92ae-8c97b8ec2fce · outbound

This paper cites Capturing Climatic Variability: Using Deep Learning for Stochastic Downscaling.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Capturing Climatic Variability: Using Deep Learning for Stochastic Downscaling

Reference 10

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Observation 845178ee-5c24-4b8f-b89f-0b3abeff6451 · outbound

This paper cites Overview frequency principle/spectral bias in deep learning.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Overview frequency principle/spectral bias in deep learning

Reference 11

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Observation ab06a8b7-9a84-40f8-b5b7-6edcf8668947 · outbound

This paper cites Rampal, P.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Rampal, P

Reference 12

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Observation 9a04ecd1-bd9b-4973-b97b-624e9cb46056 · outbound

This paper cites Generative Adversarial Models for Extreme Geospatial Downscaling.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Generative Adversarial Models for Extreme Geospatial Downscaling

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

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Observation cf6c56b2-a960-4133-9b3e-209ff381cd1a · outbound

This paper cites Residual Corrective Diffusion Modeling for Km-scale Atmospheric Downscaling.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Residual Corrective Diffusion Modeling for Km-scale Atmospheric Downscaling

Reference 14

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Observation fc5a757c-4375-4e3b-9c5f-a286cb28e0b8 · outbound

This paper cites Generative Diffusion-based Downscaling for Climate.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Generative Diffusion-based Downscaling for Climate

Reference 15

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Observation e3e7cf4c-b8d7-4a9a-af99-34bd5ed0a16c · outbound

This paper cites Denoising Diffusion Implicit Models.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Denoising Diffusion Implicit Models

Reference 16

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Observation 312b234b-edbe-4260-860b-cdc4341c90d2 · outbound

This paper cites an unresolved cited work.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Unresolved cited work

Reference 17

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Observation c1a43c8c-96ab-470f-91f0-f8d276ea2dac · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Score-Based Generative Modeling through Stochastic Differential Equations

Reference 18

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Observation 4e067959-bcd1-4657-80b7-d6d603125673 · outbound

This paper cites Karras, M.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Karras, M

Reference 19

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Observation 1135d6fc-fe00-4842-8201-893a4a0ddb7a · outbound

This paper cites Wind speed super-resolution and validation: from ERA5 to CERRA via diffusion models.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Wind speed super-resolution and validation: from ERA5 to CERRA via diffusion models

Reference 20

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Observation 4c7dde92-a245-4c72-8dee-af4c24d53c6c · outbound

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TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Unresolved cited work

Reference 21

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Observation 45c009c4-a8ac-4bb2-ab13-2056849d1650 · outbound

This paper cites Deterministic Guidance Diffusion Model for Probabilistic Weather Forecasting.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Deterministic Guidance Diffusion Model for Probabilistic Weather Forecasting

Reference 22

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TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Unresolved cited work

Reference 23

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TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Unresolved cited work

Reference 24

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Observation a3419e08-46b1-4f82-8963-a493d8c9bef3 · outbound

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TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Song and S

Reference 25

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Observation 845e5484-8258-4caf-bfa7-4999bedc281c · outbound

This paper cites Schröder and W.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Schröder and W

Reference 26

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Observation b3abf026-7600-4061-9691-8579d4481a69 · outbound

This paper cites A Local Spectral Exterior Calculus for the Sphere and Application to the Shallow Water Equations.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models A Local Spectral Exterior Calculus for the Sphere and Application to the Shallow Water Equations

Reference 27

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Observation c58abbfa-b9f8-4cc3-b29e-34c79b603431 · outbound

This paper cites B Neale, J.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models B Neale, J

Reference 28

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Observation 53190ee0-7a0b-4c23-bcd0-5d2ee05d7cb5 · outbound

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TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Unresolved cited work

Reference 29

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Source-reported events for the cited work

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Observation 67ea85cb-e9b3-44b7-9885-edea0120b759 · outbound

This paper cites Cerra sub-daily regional reanalysis data for europe on single levels from 1984 to present.

TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models Cerra sub-daily regional reanalysis data for europe on single levels from 1984 to present

Reference 30

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Pith citing papers

Observation 5274b9bb-4723-4008-9a99-dc5b06cb437b · inbound

Boosting Ensembles for Statistics of Tails at Conditionally Optimal Advance Split Times cites this paper.

Boosting Ensembles for Statistics of Tails at Conditionally Optimal Advance Split Times TAUDiff: Highly efficient kilometer-scale downscaling using generative diffusion models

Reference 56

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