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Paper Citation Record · LEDGER

ExEBench: Benchmarking Foundation Models on Extreme Earth Events

As of 23 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 5 inbound Pith citation observations for arXiv:2505.08529.

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

pith.paper-citation-record.v1
2505.08529 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:56:35.460898Z

measured 52 of 52 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T18:44:35.361287Z

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

47 of 47 outbound references displayed

  • verified exact0
  • verified fuzzy38
  • unresolved8
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 02f7c4e6-61f1-40c0-a2ba-71d1a3e343c1 · outbound

This paper cites Weather and climate extreme events in a changing climate,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Weather and climate extreme events in a changing climate,

Reference 1

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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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Observation 7d182c95-601c-43ae-8c73-6104023a2461 · outbound

This paper cites thesis, GIEC, 2022.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events thesis, GIEC, 2022

Reference 2

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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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Observation 618d47b4-97d1-448e-acd3-9ab3c4cbe528 · outbound

This paper cites Antici- pating cascading effects of extreme precipitation with pathway schemes-three case studies from europe,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Antici- pating cascading effects of extreme precipitation with pathway schemes-three case studies from europe,

Reference 3

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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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Observation 5bcd6840-175a-4459-9899-d1cdaaec8790 · outbound

This paper cites Crimmins, Justin M.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Crimmins, Justin M

Reference 4

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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=2026-08-15T21:56:35.284849Z digest=sha256:792af4f555649c32851371de29b7975dfc6dd040da797e62e5cfdb61e9adfc6d

Observation 4ec4c3d0-7368-44f9-b7e1-c7331ec71005 · outbound

This paper cites On the Foundations of Earth and Climate Foundation Models.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events On the Foundations of Earth and Climate Foundation Models

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:56:35.288801Z digest=sha256:2161a6db94d2e90a956cf79a6d464cb392453ae2b1e48260726f40f534bd74b8

Observation dd85c724-6054-42ef-a623-26d7746054b9 · outbound

This paper cites Neural plasticity- inspired foundation model for observing the earth crossing modalities,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Neural plasticity- inspired foundation model for observing the earth crossing modalities,

Reference 6

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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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Observation beca7c7a-bbcf-4e38-94fb-bc5cbef7ab12 · outbound

This paper cites Satmae: Pre-training transformers for temporal and multi-spectral satellite imagery,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Satmae: Pre-training transformers for temporal and multi-spectral satellite imagery,

Reference 7

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Source-reported events for the cited work

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

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Observation 95aa5424-e95c-48b9-bad2-f85adb7aa9ce · outbound

This paper cites Prithvi WxC: Foundation Model for Weather and Climate.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Prithvi WxC: Foundation Model for Weather and Climate

Reference 8

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no resolver link, observed 2026-08-15T21:56:35.301900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d5da250c-21a1-4395-acf8-3cca41c4ad4f · outbound

This paper cites Climax: A foundation model for weather and climate,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Climax: A foundation model for weather and climate,

Reference 9

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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=2026-08-15T21:56:35.306177Z digest=sha256:5fbebf10ef9522bae3403ba69de54eb697e99bd143ed53c7f2af6b2e882f1934

Observation a8f75c99-b5f7-4010-8ebe-0cc185f25805 · outbound

This paper cites What if? numerical weather prediction at the crossroads,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events What if? numerical weather prediction at the crossroads,

Reference 10

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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=2026-08-15T21:56:35.310100Z digest=sha256:965edbf893e2293509d34b57b0ff92415275bd432e6afe986e7065fd06afb44c

Observation 1d85a57d-86e3-4592-9ef7-85c967c92e00 · outbound

This paper cites SustainBench: Benchmarks for monitoring the sustainable development goals with machine learning,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events SustainBench: Benchmarks for monitoring the sustainable development goals with machine learning,

Reference 11

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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=2026-08-15T21:56:35.313795Z digest=sha256:bd11b7167c3866fb2108486ec90d4f1ca2e5bafe076d4d1241979b3ce84c303f

Observation 96797d12-3cb9-4f55-82d0-ef89180cad3d · outbound

This paper cites Geo- bench: Toward foundation models for earth monitoring,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Geo- bench: Toward foundation models for earth monitoring,

Reference 12

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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=2026-08-15T21:56:35.317789Z digest=sha256:8975630be0bbfc196321adc51edfde262b471f77dded5a1fee6a535c8da55bc3

Observation 00e7c3f1-d259-4798-9225-ea44eafb6cc4 · outbound

This paper cites FoMo: Multi-Modal, Multi-Scale and Multi-Task Remote Sensing Foundation Models for Forest Monitoring.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events FoMo: Multi-Modal, Multi-Scale and Multi-Task Remote Sensing Foundation Models for Forest Monitoring

Reference 13

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no resolver link, observed 2026-08-15T21:56:35.321685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:56:35.321685Z digest=sha256:e044cd9a13bca919dce055516e0badb849cf57175b686f6832c143db4e1f8985

Observation 0260d873-55d3-45af-9c07-8424bc238eae · outbound

This paper cites Weatherbench: a benchmark data set for data-driven weather forecasting,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Weatherbench: a benchmark data set for data-driven weather forecasting,

Reference 14

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raw_fallback, observed 2026-08-15T21:56:36.125558Z

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=2026-08-15T21:56:35.326044Z digest=sha256:ab6e8c990657bdbfafc7f3d588f858628c78b4f813a5d950c2a3d179cd93e70b

Observation 8ecad59f-9771-4412-a5ae-a81976a1eba6 · outbound

This paper cites Weatherbench 2: A benchmark for the next generation of data-driven global weather models,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Weatherbench 2: A benchmark for the next generation of data-driven global weather models,

Reference 15

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raw_fallback, observed 2026-08-15T21:56:36.112249Z

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=2026-08-15T21:56:35.330783Z digest=sha256:4e96d827d5e7710a15e1305d9da1788a804ad5f73e3ed7b6d09e9ab942f45538

Observation 8f704efa-1828-4267-84a1-278dc621933e · outbound

This paper cites Defining extreme events: A cross-disciplinary review,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Defining extreme events: A cross-disciplinary review,

Reference 16

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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=2026-08-15T21:56:35.335301Z digest=sha256:cf269de3b9d60ddd9b0210dab975dea726887b245cf3cbc11bd723ec8079418c

Observation ccf6a48f-3bee-4265-bfb6-ef1b203a327e · outbound

This paper cites Heatwave,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Heatwave,

Reference 17

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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=2026-08-15T21:56:35.340626Z digest=sha256:d676e6550c0bb57ed80ca044a9d1a5b40944a84ca2985adb81d4d5d681a39ac2

Observation 541b2ef6-7d63-4f0f-bd1a-25b314d1aeef · outbound

This paper cites Heat-related mortality in europe during the summer of 2022,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Heat-related mortality in europe during the summer of 2022,

Reference 18

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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=2026-08-15T21:56:35.344698Z digest=sha256:9cf647036b5ca66e57348ef13886f5181a65e072841122fca488320495ec466b

Observation 851d301d-8991-4a3c-866d-7d118505e0c1 · outbound

This paper cites EM-DAT: The International Disaster Database,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events EM-DAT: The International Disaster Database,

Reference 19

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raw_fallback, observed 2026-08-15T21:56:36.066344Z

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=2026-08-15T21:56:35.349051Z digest=sha256:772079116c62825136ec5783b71fd53829bb382643c9f7eb455836faca749834

Observation e3d66714-7bae-4fd3-a4da-078baafeedb0 · outbound

This paper cites The ERA5 global reanalysis,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events The ERA5 global reanalysis,

Reference 20

Resolution
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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=2026-08-15T21:56:35.353158Z digest=sha256:97931195a4022872084146932f0bb0200c7a09f32f3436e4e931779bf28e030c

Observation 99c6990c-f006-4d31-a1d4-616b7330b63a · outbound

This paper cites Exploring geo- metric deep learning for precipitation nowcasting,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Exploring geo- metric deep learning for precipitation nowcasting,

Reference 21

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raw_fallback, observed 2026-08-15T21:56:36.042498Z

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=2026-08-15T21:56:35.357675Z digest=sha256:6ca7a3d8bdd6e8070d5c7767ddf35ca40b013671944e9427f4bfc1abca5d0c25

Observation 0ae0371d-3ac5-47e3-95fe-9e3a3a7444b2 · outbound

This paper cites Rainnet v1. 0: a convolutional neural network for radar-based precipitation nowcasting,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Rainnet v1. 0: a convolutional neural network for radar-based precipitation nowcasting,

Reference 22

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raw_fallback, observed 2026-08-15T21:56:36.030068Z

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=2026-08-15T21:56:35.361521Z digest=sha256:a686fc9823e977b84411ca39a7ba2aebe2bb7e307b872e8272bb52397b579b7d

Observation 95dbcc71-e000-4f64-963f-0b3b671501c9 · outbound

This paper cites TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events TAASRAD19, a high-resolution weather radar reflectivity dataset for precipitation nowcasting,

Reference 23

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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=2026-08-15T21:56:35.365496Z digest=sha256:dd111c88b166aed67b6f86347ab8146c3536c306fd97319b34c4c93c4f1a8f84

Observation 0b83d323-dab4-4df1-993e-f378f048b9c7 · outbound

This paper cites The trmm multisatellite precipitation analysis (tmpa): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events The trmm multisatellite precipitation analysis (tmpa): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales,

Reference 24

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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=2026-08-15T21:56:35.369100Z digest=sha256:d7d0e1a87202c14dbce6a8b72fe17489a6b4981f7d1f3703f7baa8fb650b7865

Observation df2b5378-f5cf-47e9-9768-0c6ac09d977e · outbound

This paper cites Complex networks reveal global pattern of extreme-rainfall teleconnections,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Complex networks reveal global pattern of extreme-rainfall teleconnections,

Reference 25

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raw_fallback, observed 2026-08-15T21:56:35.989944Z

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=2026-08-15T21:56:35.372968Z digest=sha256:bed0723bf7d1743e82d0d086bf05099071f08283282b8c26f63c7f67ff944864

Observation 1f7568a1-e979-46a0-a048-777cf955a6ab · outbound

This paper cites GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07,

Reference 26

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raw_fallback, observed 2026-08-15T21:56:35.974107Z

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=2026-08-15T21:56:35.376906Z digest=sha256:ce1ef283d53283428c584506f0a3a833ce3be852c51e005b3fdbe5f8f4c9be7a

Observation 78ca5863-1840-4f2b-814e-61b01770c9dc · outbound

This paper cites Accurate medium-range global weather forecasting with 3d neural networks,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Accurate medium-range global weather forecasting with 3d neural networks,

Reference 27

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raw_fallback, observed 2026-08-15T21:56:35.959030Z

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=2026-08-15T21:56:35.380758Z digest=sha256:b0630e5df01d36da3151fcee60921cd6b11486ef763d7a93339a05b865b75ae9

Observation 87d7ccf4-424f-4f75-9a75-854324e89acb · outbound

This paper cites Learning skillful medium-range global weather forecasting,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Learning skillful medium-range global weather forecasting,

Reference 28

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raw_fallback, observed 2026-08-15T21:56:35.945894Z

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=2026-08-15T21:56:35.384684Z digest=sha256:318832a359f779aa4bec58f306a693998ea84a8d558f697b994aa2e423b36df4

Observation e359fe97-c130-4fcf-800f-5fd6ee2efbf2 · outbound

This paper cites The international best track archive for climate stewardship (IBTrACS) unifying tropical cyclone data,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events The international best track archive for climate stewardship (IBTrACS) unifying tropical cyclone data,

Reference 29

Resolution
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raw_fallback, observed 2026-08-15T21:56:35.931391Z

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=2026-08-15T21:56:35.388340Z digest=sha256:7312d2fdeaa7868c4a797d65ba8d2480c90f9a347a0e014419a732c8d3ae79f0

Observation 2be43470-f0c9-4751-9814-dd52a66a934e · outbound

This paper cites Wildfire danger prediction and understanding with deep learning,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Wildfire danger prediction and understanding with deep learning,

Reference 30

Resolution
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raw_fallback, observed 2026-08-15T21:56:35.917933Z

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=2026-08-15T21:56:35.392045Z digest=sha256:5eae4ee6bd67362b84ec1cbfa94740a4167f125112d026226b9ea4ac297410da

Observation 6b303b86-fe8f-4e99-ae7d-f7c8ef4c29a6 · outbound

This paper cites HLS Foundation Burnscars Dataset,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events HLS Foundation Burnscars Dataset,

Reference 31

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raw_fallback, observed 2026-08-15T21:56:35.898403Z

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=2026-08-15T21:56:35.396864Z digest=sha256:cd121bdaaea54f018044b1caa819fe5a5f109dcf14c4a80b1098bf14d64d439b

Observation 288c2830-5662-4605-ba4a-e1c56648bf81 · outbound

This paper cites Urban flood mapping using satellite synthetic aperture radar data: A review of characteristics, approaches, and datasets,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Urban flood mapping using satellite synthetic aperture radar data: A review of characteristics, approaches, and datasets,

Reference 32

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raw_fallback, observed 2026-08-15T21:56:35.882985Z

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=2026-08-15T21:56:35.400520Z digest=sha256:ba5e7ab00a520f7b06d31dc65ff2c532bb27863902da92b18378b2019b546102

Observation d710f519-441b-4ff4-98f6-6ade17ca6207 · outbound

This paper cites UrbanSARFloods: Sentinel-1 SLC-based benchmark dataset for urban and open-area flood mapping,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events UrbanSARFloods: Sentinel-1 SLC-based benchmark dataset for urban and open-area flood mapping,

Reference 33

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raw_fallback, observed 2026-08-15T21:56:35.866860Z

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=2026-08-15T21:56:35.404185Z digest=sha256:3eddaf39d0cc6ea3c2e2db37e2dbd3ac2a273fd5c5afaff609402d2ac6090658

Observation 580e5a53-c9b4-4415-b14b-d34c7a4fe189 · outbound

This paper cites Fourcastnet: Acceler- ating global high-resolution weather forecasting using adaptive fourier neural operators,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Fourcastnet: Acceler- ating global high-resolution weather forecasting using adaptive fourier neural operators,

Reference 34

Resolution
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raw_fallback, observed 2026-08-15T21:56:35.851462Z

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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Observation 1040cd99-6b3d-4469-8bea-82843be35096 · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events U-net: Convolutional networks for biomedical image segmentation,

Reference 35

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verified fuzzy
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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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Observation a1104027-3bda-4043-978a-8c88db466130 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Segformer: Simple and efficient design for semantic segmentation with transformers,

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-15T21:56:35.417604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 843aef3d-8fe9-4f87-8a29-ce5d9b8e7eec · outbound

This paper cites A convnet for the 2020s,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events A convnet for the 2020s,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:35.811946Z

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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Observation 401f0173-90d4-4a85-ab4a-ccf1673818eb · outbound

This paper cites Foundation Models for Generalist Geospatial Artificial Intelligence.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Foundation Models for Generalist Geospatial Artificial Intelligence

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-15T21:56:35.425204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:56:35.425204Z digest=sha256:98bc35c470f687f84f1f67262d0b5145b898bc79b936f1e9a9ef99f8b6185f8d

Observation 60719672-377b-449e-a94b-127bafc4eb6f · outbound

This paper cites Prithvi-eo-2.0: A versatile multi-temporal foundation model for earth observation applications,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Prithvi-eo-2.0: A versatile multi-temporal foundation model for earth observation applications,

Reference 39

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 22e24520-1232-4851-9edf-ed12385fb813 · outbound

This paper cites Aurora: A foundation model for the earth system,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Aurora: A foundation model for the earth system,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:35.796888Z

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=2026-08-15T21:56:35.433775Z digest=sha256:fb6167c4acf03ec010980dc002a0793527366b8f40fb86f1a525db648c7cd718

Observation 2cf53f7f-b833-4a58-8e8b-ae59571cb545 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events LoRA: Low-Rank Adaptation of Large Language Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T21:56:35.437274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:56:35.437274Z digest=sha256:2a606ae4d88ed6aecb0680a76f5c02ef4ac0c440bc36537cc113b9bb69269abe

Observation 05762c15-661f-4c6d-9e97-c0f5de423685 · outbound

This paper cites Unified perceptual parsing for scene understanding,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Unified perceptual parsing for scene understanding,

Reference 42

Resolution
verified fuzzy
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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=2026-08-15T21:56:35.441772Z digest=sha256:2db9b60bede138d386f001fdbf0ca8f9c46e118dcf54de4254a33e62d68f89a5

Observation 72a742ca-ba31-40d7-8962-2db135eb0185 · outbound

This paper cites Lgg mri segmentation dataset,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Lgg mri segmentation dataset,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:35.767040Z

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=2026-08-15T21:56:35.445444Z digest=sha256:66f5e26b5d30290395f201898b1261c8438daec53fc219aeac3fadcd087a0428

Observation c7bbba15-800f-457f-a354-95e2e860078b · outbound

This paper cites ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events ExtremeCast: Boosting Extreme Value Prediction for Global Weather Forecast

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T21:56:35.449467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:56:35.449467Z digest=sha256:82789d7a8bf57a4e534802a926fee62f9d786d6618a188e621be5e8f5c9597ba

Observation f1235071-1977-4d06-bf24-9c2afa620d83 · outbound

This paper cites Deep learning for precipitation nowcasting: A benchmark and a new model,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Deep learning for precipitation nowcasting: A benchmark and a new model,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:35.752111Z

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=2026-08-15T21:56:35.453441Z digest=sha256:60e3a6e4dfa72155ce22f96d7c4faf148502a208471a2f77956814ff2f1112d6

Observation 6e763a86-3987-40c8-a458-553fb289160c · outbound

This paper cites Fixing weight decay regularization in adam,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Fixing weight decay regularization in adam,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:56:35.738177Z

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=2026-08-15T21:56:35.457273Z digest=sha256:efbf5a9ad33482448401a650639b1d3f467d22b4fb9ee1b9d640795d503b6427

Observation baad036d-28f4-4696-b130-910bad90a645 · outbound

This paper cites Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations,.

ExEBench: Benchmarking Foundation Models on Extreme Earth Events Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations,

Reference 47

Resolution
malformed identifier
raw_fallback, observed 2026-08-15T21:56:35.571869Z

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=2026-08-15T21:56:35.460898Z digest=sha256:009cc015cf85254d77846466fce2d788fc766f475983d6958b8199e77f628685

Pith citing papers

Observation 819dab8c-36d4-4770-8daf-c5c91da50030 · inbound

SHRUG-FM: Reliability-Aware Foundation Models for Earth Observation cites this paper.

SHRUG-FM: Reliability-Aware Foundation Models for Earth Observation ExEBench: Benchmarking Foundation Models on Extreme Earth Events

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:22:09.038921Z

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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Observation ca55b134-b573-4faf-9516-86b06e7389b8 · inbound

The Rise of AI in Weather and Climate Information and its Impact on Global Inequality cites this paper.

The Rise of AI in Weather and Climate Information and its Impact on Global Inequality ExEBench: Benchmarking Foundation Models on Extreme Earth Events

Reference 89

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T18:44:35.361287Z digest=sha256:5384e8561b4f13fe2ce991390f576f3ac75bd2a5336332384b2a3c1664e00649

Observation bc83df1c-0bc5-4ca9-b974-1794c3d7ff00 · inbound

Instability-Aware Steering of an Extreme Atmospheric River in an AI Weather Foundation Model cites this paper.

Instability-Aware Steering of an Extreme Atmospheric River in an AI Weather Foundation Model ExEBench: Benchmarking Foundation Models on Extreme Earth Events

Reference 16

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T02:38:17.061917Z

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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Observation 7cd9386f-7b2f-41c9-8265-facd47d18cd4 · inbound

Scalable and Trustworthy Earth Observation Foundation Models cites this paper.

Scalable and Trustworthy Earth Observation Foundation Models ExEBench: Benchmarking Foundation Models on Extreme Earth Events

Reference 52

Resolution
metadata mismatch
local_arxiv, observed 2026-07-10T19:07:35.283258Z

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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Observation c709db39-694b-4179-b40d-1c0fb7951ea4 · inbound

Physics-Informed Super-Resolution of Atmospheric Data cites this paper.

Physics-Informed Super-Resolution of Atmospheric Data ExEBench: Benchmarking Foundation Models on Extreme Earth Events

Reference 278

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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