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Paper Citation Record · LEDGER

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems

As of 23 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 3 inbound Pith citation observations for arXiv:2412.20601.

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

pith.paper-citation-record.v1
2412.20601 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:20:52.288160Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:35:43.587308Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

1
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 2bdb9fac-7c4a-4249-9ed8-736513ed8bb0 · outbound

This paper cites (18) The equations are solved by using a finite volume method with nx “ 256, ny“ 256 grid points in x and z directions, respectively.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems (18) The equations are solved by using a finite volume method with nx “ 256, ny“ 256 grid points in x and z directions, respectively

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:20:52.596046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T23:20:52.278104Z digest=sha256:97d020e790ac33b3100696ecf5cba309c35cfb445b4834827d14781d91ca9afa

Observation 887217a8-8077-4698-8be6-705b1303a5c7 · outbound

This paper cites DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems DPOT: Auto-Regressive Denoising Operator Transformer for Large-Scale PDE Pre-Training

Reference 4

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no resolver link, observed 2026-08-10T23:20:52.237026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:20:52.237026Z digest=sha256:ffe7e9077aa0b4286283acdbac7f93afa9a1f5aefe4ffb86c3a9c83208f0c8db

Observation 11a66fe9-766c-4bc9-bc8d-9886627683a5 · outbound

This paper cites Poseidon: Efficient Foundation Models for PDEs.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems Poseidon: Efficient Foundation Models for PDEs

Reference 5

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no resolver link, observed 2026-08-10T23:20:52.242396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:20:52.242396Z digest=sha256:95ead668c6e8d9f4ec6fa4f79818fd9880d44d3c070db7cdb1006e28b3297126

Observation 9712a7f0-33fc-4586-a7ed-dea71c382c82 · outbound

This paper cites Axial Attention in Multidimensional Transformers.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems Axial Attention in Multidimensional Transformers

Reference 6

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unresolved
no resolver link, observed 2026-08-10T23:20:52.247556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:20:52.247556Z digest=sha256:99050c458457d7a66e2ffbd6eb51174371c5ce61ec28565d21339224bfff36f8

Observation 60f105b5-d360-4504-be8c-204ca61ea17b · outbound

This paper cites DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models

Reference 7

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unresolved
no resolver link, observed 2026-08-10T23:20:52.252771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:20:52.252771Z digest=sha256:f807aa75199a4ae962f5c3647c20c4556ff257295a419034dca83941b823e23d

Observation bac9767b-a4bb-4758-9c6b-d1a1b27462b3 · outbound

This paper cites Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-10T23:20:52.257567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:20:52.257567Z digest=sha256:3e51e6732437124ecfd801297625c6e198736aac30586af44ea1070a776702ad

Observation 4fc87ff1-3c54-47bf-925e-6fe9c35dc2ba · outbound

This paper cites Multiple Physics Pretraining for Physical Surrogate Models.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems Multiple Physics Pretraining for Physical Surrogate Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T23:20:52.262740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:20:52.262740Z digest=sha256:838ea1bff1253476c15904dc091ebae42dd46e92ef037482c1c7bfdb6b035b22

Observation d79152ad-bf2d-424c-af07-6fa293294702 · outbound

This paper cites original-date: 2018-07-24T02:29:06Z.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems original-date: 2018-07-24T02:29:06Z

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:20:52.611654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T23:20:52.267474Z digest=sha256:0d552d0ec79ec29759d4ff58c9c5e1f1c5a16970b934ee964f94d9cbca28c66c

Observation f2fd5e92-15c6-47ca-9be2-94543aa9c388 · outbound

This paper cites Adaptive Patching for High-resolution Image Segmentation with Transformers.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems Adaptive Patching for High-resolution Image Segmentation with Transformers

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T23:20:52.272667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:20:52.272667Z digest=sha256:685f616a70c906d4d627fc24c875c914e32d7f4702230c5ba857c58ee30b9c4b

Observation bde07d98-132a-4e72-b5d9-4239d18661fc · outbound

This paper cites A.3 P RETRAINING AND FINE -TUNING A.3.1 P RETRAINING Five 2D datasets from PDEBench Takamoto et al.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems A.3 P RETRAINING AND FINE -TUNING A.3.1 P RETRAINING Five 2D datasets from PDEBench Takamoto et al

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:20:52.580518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T23:20:52.282872Z digest=sha256:90df9d71b74323a336b420b07670cbdfc5b66f5eb06a9a999d8a2147c4272c40

Observation b205b16b-0047-4edd-a024-7798696871cc · outbound

This paper cites Table A1: Cases and datasets Pretraining: PDEBench Takamoto et al.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems Table A1: Cases and datasets Pretraining: PDEBench Takamoto et al

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T23:20:52.565349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-08-10T23:20:52.288160Z digest=sha256:8b4ee6e048cd38f0ad1f936b292216f963449df8802639641f7a2070db91271b

Observation 789d1064-082d-4a6b-a9d0-1db1d9598107 · outbound

This paper cites ViViT: A Video Vision Transformer.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems ViViT: A Video Vision Transformer

Reference 2021

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unresolved
no resolver link, observed 2026-08-10T23:20:52.220620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:20:52.220620Z digest=sha256:c98b914ee088c0a4c3cf6dd1d0c5c6494d8e8cd7ebf9ed936c829c65752298e3

Observation d3e6e55c-6c50-4531-8a5d-c467d03dbf67 · outbound

This paper cites doi: https://doi.org/10.1016/j.jcp.2023.112493.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems doi: https://doi.org/10.1016/j.jcp.2023.112493

Reference 2023

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unresolved
no resolver link, observed 2026-08-10T23:20:52.227113Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:20:52.227113Z digest=sha256:f70f1680913f05fbe28b88708e5b3b1e8ad862ceb923ddc4a1c7d8fdf62011d7

Observation eb545d06-8758-4a8f-968c-2fb1139c6b4f · outbound

This paper cites ViTAR: Vision Transformer with Any Resolution.

MATEY: multiscale adaptive foundation models for spatiotemporal physical systems ViTAR: Vision Transformer with Any Resolution

Reference 2024

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unresolved
no resolver link, observed 2026-08-10T23:20:52.232067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

Observation 5a3247fb-189f-481a-a9e3-e91587e7df9d · inbound

PDE-Transformer: Efficient and Versatile Transformers for Physics Simulations cites this paper.

PDE-Transformer: Efficient and Versatile Transformers for Physics Simulations MATEY: multiscale adaptive foundation models for spatiotemporal physical systems

Reference 96

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unresolved
no resolver link, observed 2026-08-07T12:35:43.587308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:43.587308Z digest=sha256:6a69b34f29fe6c2339a2b8cc20de2bd4ee6c054ae2e0af0457b93594d915b3eb

Observation b93d2792-2d95-458e-b732-8d0dd6cdcfcf · inbound

Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit cites this paper.

Pixel-Resolved Long-Context Learning for Turbulence at Exascale: Resolving Small-scale Eddies Toward the Viscous Limit MATEY: multiscale adaptive foundation models for spatiotemporal physical systems

Reference 16

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unresolved
no resolver link, observed 2026-08-06T15:09:21.687086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:09:21.687086Z digest=sha256:18429b96a702cfbb74e9c381a8b15c3ec33c09a5c507c1bdc51c9e9f92da3f8c

Observation 31b569ad-a26d-429f-a121-a9b094fdcc7e · inbound

Automated Data Readiness for Scientific AI cites this paper.

Automated Data Readiness for Scientific AI MATEY: multiscale adaptive foundation models for spatiotemporal physical systems

Reference 59

Resolution
verified exact
local_arxiv, observed 2026-07-12T07:18:35.116667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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