Paper Citation Record · LEDGER

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems

As of 22 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 8 inbound Pith citation observations for arXiv:2505.12882.

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

pith.paper-citation-record.v1
2505.12882 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:28:18.634470Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:55:41.729854Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T19:05:00.823973Z

Reference resolution

42 of 42 outbound references displayed

verified exact0
verified fuzzy15
unresolved27
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e2513beb-9e74-4b05-afb8-4340abd42470 · outbound

This paper cites A review of operational methods of variational and ensemble-variational data assimilation.Quarterly Journal of the Royal Meteorological Society, 143(703):607–633, 2017.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems A review of operational methods of variational and ensemble-variational data assimilation.Quarterly Journal of the Royal Meteorological Society, 143(703):607–633, 2017

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:19.230217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a7597251-4519-47a4-a29f-bb985097d1b9 · outbound

This paper cites Physics-Informed Diffusion Models.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Physics-Informed Diffusion Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.485827Z

Source-reported events for the cited work

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Observation 3ce89d8c-89d3-4ae8-921e-597b29f3aa16 · outbound

This paper cites Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.489973Z

Source-reported events for the cited work

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Observation 8ebf1f0b-2885-4e28-873a-adafd15cf260 · outbound

This paper cites Clifford neural networks for learning stable dynamical systems.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Clifford neural networks for learning stable dynamical systems

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:19.215616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 18d846fc-ba5d-4653-9c6a-1ab0742a0373 · outbound

This paper cites Data assimilation in the geosciences: An overview of methods, issues, and perspectives.Wiley Interdisciplinary Reviews: Climate Change, 9(5):e535, 2018.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Data assimilation in the geosciences: An overview of methods, issues, and perspectives.Wiley Interdisciplinary Reviews: Climate Change, 9(5):e535, 2018

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.498119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e6ab2bd0-f1bf-4cf9-a896-04cfcf8eba44 · outbound

This paper cites Fengwu: Pushing the skillful global medium-range weather forecast beyond 10 days lead.arXiv preprint arXiv:2304.02948, 2023.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Fengwu: Pushing the skillful global medium-range weather forecast beyond 10 days lead.arXiv preprint arXiv:2304.02948, 2023

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.501770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 800e9511-8273-4555-b072-6576707911f6 · outbound

This paper cites Towards an end-to-end artificial intelligence driven global weather forecasting system.arXiv preprint arXiv:2312.12462, 2023.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Towards an end-to-end artificial intelligence driven global weather forecasting system.arXiv preprint arXiv:2312.12462, 2023

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.506244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47a554e6-cfa6-4813-89fd-0ebf69726440 · outbound

This paper cites Fnp: Fourier neural processes for arbitrary-resolution data assimilation.Advances in Neural Information Processing Systems, 37:137847–137872, 2024.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Fnp: Fourier neural processes for arbitrary-resolution data assimilation.Advances in Neural Information Processing Systems, 37:137847–137872, 2024

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:19.194104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5c9eb6b5-80fd-4c5b-825e-70f09e5c3168 · outbound

This paper cites The ecmwf implementation of three-dimensional variational assimilation (3d-var).

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems The ecmwf implementation of three-dimensional variational assimilation (3d-var)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:19.180143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 80c87b53-8b2b-4b41-b4f2-3f2e0f9af368 · outbound

This paper cites Physics- guided neural networks (pgnn): An application in lake temperature modeling.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Physics- guided neural networks (pgnn): An application in lake temperature modeling

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:19.168031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fa5b983e-dba6-473c-9579-438d5f212862 · outbound

This paper cites Diffusion models beat gans on image synthesis.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Diffusion models beat gans on image synthesis

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.520725Z

Source-reported events for the cited work

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Observation ad691a01-f51c-47ab-ab64-423283fb511d · outbound

This paper cites an unresolved cited work.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:28:19.147716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5c65a736-8a82-46c1-86bc-027e3a87a248 · outbound

This paper cites Convolutional Conditional Neural Processes.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Convolutional Conditional Neural Processes

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.528797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 826569bc-feba-49fb-b59e-60c6b0396c83 · outbound

This paper cites Photorealistic video generation with diffusion models.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Photorealistic video generation with diffusion models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.532755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76f71386-0645-400f-b4c3-4845f0248347 · outbound

This paper cites Era5 monthly averaged data on single levels from 1979 to present.Copernicus Climate Change Service (C3S) Climate Data Store (CDS), 10:252–266, 2019.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Era5 monthly averaged data on single levels from 1979 to present.Copernicus Climate Change Service (C3S) Climate Data Store (CDS), 10:252–266, 2019

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:19.125727Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b7c956cd-b95e-402b-a0dd-7c1e4eec0144 · outbound

This paper cites Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Denoising diffusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.539943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a3c92ce-95c8-4ff6-9942-749c0770ee7d · outbound

This paper cites Holton and Gregory J.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Holton and Gregory J

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:19.102860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 7921b2ed-6264-496e-ad10-4e00ebfb1eae · outbound

This paper cites DiffDA: a Diffusion Model for Weather-scale Data Assimilation.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems DiffDA: a Diffusion Model for Weather-scale Data Assimilation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.547304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0361a625-81b4-4f0e-992a-515c8472b1ea · outbound

This paper cites Physics-informed machine learning.Nature Reviews Physics, 3(6):422–440, 2021.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Physics-informed machine learning.Nature Reviews Physics, 3(6):422–440, 2021

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.551284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1786503e-cba4-4c04-b9c2-c202018a6d46 · outbound

This paper cites Enforcing physical constraints in cnns through differentiable pde layer.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Enforcing physical constraints in cnns through differentiable pde layer

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:19.080699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 09c2e01c-a3ee-4b2e-83e9-972584e10862 · outbound

This paper cites Auto-encoding variational bayes, 2013.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Auto-encoding variational bayes, 2013

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.559274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e31872d7-851f-497b-bd95-4a962d695f58 · outbound

This paper cites Learning skillful medium-range global weather forecasting.Science, 382(6677):1416–1421, 2023.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Learning skillful medium-range global weather forecasting.Science, 382(6677):1416–1421, 2023

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.563109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e37d9d8-10e4-4dc3-9140-99eaaedc05df · outbound

This paper cites Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects.Tellus A: Dynamic Meteorology and Oceanography, 38(2):97–110, 1986.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Variational algorithms for analysis and assimilation of meteorological observations: theoretical aspects.Tellus A: Dynamic Meteorology and Oceanography, 38(2):97–110, 1986

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:19.053676Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6c0c9cab-3039-436b-8679-0c245fd0f293 · outbound

This paper cites Fourier Neural Operator for Parametric Partial Differential Equations.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Fourier Neural Operator for Parametric Partial Differential Equations

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.570243Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c023fcb8-4e4c-492d-a467-b81f6d2dc482 · outbound

This paper cites Neural Operator: Graph Kernel Network for Partial Differential Equations.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Neural Operator: Graph Kernel Network for Partial Differential Equations

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.574119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3087cf3-92cb-4ecb-b5ae-728841a5b701 · outbound

This paper cites Hybridnet: integrating model-based and data-driven learning to predict evolution of dynamical systems.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Hybridnet: integrating model-based and data-driven learning to predict evolution of dynamical systems

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.577944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c62f56e6-7bfe-4e0f-85d8-ea8da150d920 · outbound

This paper cites Analysis methods for numerical weather prediction.Quarterly Journal of the Royal Meteorological Society, 112(474):1177–1194, 1986.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Analysis methods for numerical weather prediction.Quarterly Journal of the Royal Meteorological Society, 112(474):1177–1194, 1986

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:19.030525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 12fdca5c-9b86-4912-9a39-3a3945583ed3 · outbound

This paper cites ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Prediction

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.584846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e40b7e9-17f9-4791-b7a6-287c287f555c · outbound

This paper cites Deep generative data assimilation in multimodal setting.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Deep generative data assimilation in multimodal setting

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:19.015483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation cb56a50b-4b26-45a4-a008-e823aa28b9dc · outbound

This paper cites an unresolved cited work.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Unresolved cited work

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.591982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fc1cf773-d24d-40eb-be2f-d3e0fd564419 · outbound

This paper cites Weatherbench: A benchmark dataset for data-driven weather forecasting.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Weatherbench: A benchmark dataset for data-driven weather forecasting

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:18.992850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation de9a3970-7697-4d71-b884-c9130ee98f98 · outbound

This paper cites Score-based data assimilation.Advances in Neural Informa- tion Processing Systems, 36:40521–40541, 2023.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Score-based data assimilation.Advances in Neural Informa- tion Processing Systems, 36:40521–40541, 2023

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:18.978379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8f81de42-4831-4624-a2cd-5516ac9e57db · outbound

This paper cites Score-based Data Assimilation for a Two-Layer Quasi-Geostrophic Model.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Score-based Data Assimilation for a Two-Layer Quasi-Geostrophic Model

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.602553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f050c99d-2b79-4e08-afb9-d921a152010a · outbound

This paper cites Probablistic emulation of a global climate model with spherical dyffusion.Advances in Neural Information Processing Systems, 37:127610–127644, 2024.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Probablistic emulation of a global climate model with spherical dyffusion.Advances in Neural Information Processing Systems, 37:127610–127644, 2024

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.606144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79dc7399-b3d5-44e5-a34b-274eafdd8165 · outbound

This paper cites an unresolved cited work.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Unresolved cited work

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:28:18.959201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bd3ff0f9-958c-4576-8e8d-1c5bbe721493 · outbound

This paper cites Wallace and Peter V.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Wallace and Peter V

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:18.947569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d3ee717c-bed3-4e9d-95c3-93cc347545c6 · outbound

This paper cites Towards physics- informed deep learning for turbulent flow prediction.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Towards physics- informed deep learning for turbulent flow prediction

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.616217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c7e31d6-bc47-490b-9e0d-1287e7b55b5c · outbound

This paper cites Physics-Guided Deep Learning for Dynamical Systems: A Survey.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Physics-Guided Deep Learning for Dynamical Systems: A Survey

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.619584Z

Source-reported events for the cited work

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Observation 84c3421a-3334-4ee0-b682-7734f43c1c2c · outbound

This paper cites Transolver: A Fast Transformer Solver for PDEs on General Geometries.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Transolver: A Fast Transformer Solver for PDEs on General Geometries

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.623375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c49e708c-d088-4887-ab7d-eb76e503bab7 · outbound

This paper cites Vae-var: Variational autoencoder- enhanced variational methods for data assimilation in meteorology.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Vae-var: Variational autoencoder- enhanced variational methods for data assimilation in meteorology

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.627253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24c5d023-cfd6-414a-9566-b2e8820058c3 · outbound

This paper cites Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T20:28:18.630676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5d89061-52a9-47da-97e2-d8157b2a6e37 · outbound

This paper cites Deep potential molecular dynamics: a scalable model with the accuracy of quantum mechanics.Physical review letters, 120(14):143001, 2018.

PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems Deep potential molecular dynamics: a scalable model with the accuracy of quantum mechanics.Physical review letters, 120(14):143001, 2018

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T20:28:18.919839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

Observation 35dbc792-e57c-4c6b-b0cd-1aa1fc0bc25a · inbound

Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review cites this paper.

Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems

Reference 168

Resolution: unresolved; no resolver link, observed 2026-08-07T11:49:45.737625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f2d66082-f8e8-4e0a-9e86-1154c22d6e7c · inbound

ScIRGen: Synthesize Realistic and Large-Scale RAG Dataset for Scientific Research cites this paper.

ScIRGen: Synthesize Realistic and Large-Scale RAG Dataset for Scientific Research PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T05:34:55.190981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29f38fc2-50a0-4c57-8f0f-930f35e928c6 · inbound

Physics-Constrained Fine-Tuning of Flow-Matching Models for Generation and Inverse Problems cites this paper.

Physics-Constrained Fine-Tuning of Flow-Matching Models for Generation and Inverse Problems PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T04:41:33.581417Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd360231-af23-4d02-b33f-6bf66779e6f5 · inbound

Uncertainty-Aware Spatiotemporal Super-Resolution Data Assimilation with Diffusion Models cites this paper.

Uncertainty-Aware Spatiotemporal Super-Resolution Data Assimilation with Diffusion Models PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:41:18.480961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2bcfcd07-7478-4c24-becc-37c575ef33d5 · inbound

Learning to Think in Physics: Breaking Shortcut Learning in Scientific Diffusion via Representation Alignment cites this paper.

Learning to Think in Physics: Breaking Shortcut Learning in Scientific Diffusion via Representation Alignment PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-21T06:24:41.357689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fed91687-9922-454e-a17b-e50506211d9b · inbound

Towards a Foundation Model for the Martian Atmosphere cites this paper.

Towards a Foundation Model for the Martian Atmosphere PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems

Reference 134

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T19:05:00.825459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 90dc2cb4-b5e5-4617-88f6-039ef3e09441 · inbound

Multimodal Spatiotemporal Atmospheric Data Assimilation with Latent Video Flow-matching cites this paper.

Multimodal Spatiotemporal Atmospheric Data Assimilation with Latent Video Flow-matching PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems

Reference 67

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Observation 82565dcb-faf1-4636-978a-eae3fcdf0585 · inbound

Multimodal Spatiotemporal Atmospheric Data Assimilation with Latent Video Flow-matching cites this paper.

Multimodal Spatiotemporal Atmospheric Data Assimilation with Latent Video Flow-matching PhyDA: Physics-Guided Diffusion Models for Data Assimilation in Atmospheric Systems

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-08T16:55:41.729854Z

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