Paper Citation Record · LEDGER

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery

As of 7 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 2 inbound Pith citation observations for arXiv:2507.13385.

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

pith.paper-citation-record.v1
2507.13385 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:08:15.326984Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T11:51:32.351491Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

48 of 48 outbound references displayed

verified exact4
verified fuzzy38
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External citation measurements

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

Outbound references

Observation 040dc9b2-9654-4ed9-a66c-b8e05a1308e6 · outbound

This paper cites L., Uzkent, B., Burke, M., Lobell, D., and Ermon, S.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery L., Uzkent, B., Burke, M., Lobell, D., and Ermon, S

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:26.406458Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 75543c36-568a-4c2e-b70d-ef3a8c0f79ed · outbound

This paper cites Segnet: A deep convolutional encoder–decoder architecture for image segmentation.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery Segnet: A deep convolutional encoder–decoder architecture for image segmentation

Reference 2

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T17:08:17.379186Z

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Observation 8da148b2-92f7-4eb3-862a-286752c50b48 · outbound

This paper cites M ulti-modal learning for geospatial vegetation forecasting.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery M ulti-modal learning for geospatial vegetation forecasting

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:26.146809Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f092386b-d8b9-4716-b0a5-4d5c24251001 · outbound

This paper cites Encoder-decoder with atrous separable convolution for semantic image segmentation.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery Encoder-decoder with atrous separable convolution for semantic image segmentation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:25.924926Z

Source-reported events for the cited work

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Observation aa61e956-ec47-4816-bb6b-22a53b1db2e3 · outbound

This paper cites G eo-aware networks for fine-grained recognition.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery G eo-aware networks for fine-grained recognition

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:25.636988Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1b8b3f29-5097-4620-951e-7c5a08a23415 · outbound

This paper cites reBEN: Refined BigEarthNet Dataset for Remote Sensing Image Analysis.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery reBEN: Refined BigEarthNet Dataset for Remote Sensing Image Analysis

Reference 6

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Observation 2027e01b-0448-4e9b-a8da-492c8339eb9e · outbound

This paper cites S at MAE : P re-training transformers for temporal and multi-spectral satellite imagery.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery S at MAE : P re-training transformers for temporal and multi-spectral satellite imagery

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:25.435914Z

Source-reported events for the cited work

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Observation 4b765645-9577-4827-957a-ffd354dfecac · outbound

This paper cites V ision T ransformers N eed R egisters.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery V ision T ransformers N eed R egisters

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:25.207672Z

Source-reported events for the cited work

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Observation de9b0d30-397e-4c09-9d28-84dedc5fae21 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 9

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Source-reported events for the cited work

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Observation f290d1ef-4fe9-448f-b9c1-fde542440dac · outbound

This paper cites Ma-net: Multi-scale attention network for liver and tumor segmentation.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery Ma-net: Multi-scale attention network for liver and tumor segmentation

Reference 10

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T17:08:16.881339Z

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Observation 9f04edde-fe9a-46a5-a297-6e352ddd9eeb · outbound

This paper cites C., Patriarca, J., Jesus, I., and Duarte, D.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery C., Patriarca, J., Jesus, I., and Duarte, D

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:24.961874Z

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Observation f4ba6551-234d-4036-9ad5-26ca64c566ac · outbound

This paper cites and Weber, P.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery and Weber, P

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:24.701851Z

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Observation 24ddb845-53b9-475a-9e7e-61ef2c33e024 · outbound

This paper cites D eep R esidual L earning for I mage R ecognition.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery D eep R esidual L earning for I mage R ecognition

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:24.470137Z

Source-reported events for the cited work

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Observation 722161a1-9fb4-4034-8b36-8557b8eda3b7 · outbound

This paper cites Continental europe digital terrain model at 30 m resolution based on gedi, icesat-2, aw3d, glo-30, eudem, merit dem and background layers.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery Continental europe digital terrain model at 30 m resolution based on gedi, icesat-2, aw3d, glo-30, eudem, merit dem and background layers

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:24.314945Z

Source-reported events for the cited work

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Observation 4505c790-f627-4512-82fe-5310945026a7 · outbound

This paper cites C-unet: Complement unet for remote sensing road extraction.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery C-unet: Complement unet for remote sensing road extraction

Reference 15

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Observation 42051a22-82ac-440d-a718-3362d143b7a7 · outbound

This paper cites V isual P rompt T uning.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery V isual P rompt T uning

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:24.158202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e3889207-b244-4ccd-8e83-5828755dbf5c · outbound

This paper cites O pensentinelmap: A large-scale land use dataset using O pen S treet M ap and S entinel-2 imagery.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery O pensentinelmap: A large-scale land use dataset using O pen S treet M ap and S entinel-2 imagery

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:24.006265Z

Source-reported events for the cited work

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Observation b53190be-3e75-45bf-b616-5128e4ad53d2 · outbound

This paper cites S at CLIP : G lobal, general-purpose location embeddings with satellite imagery.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery S at CLIP : G lobal, general-purpose location embeddings with satellite imagery

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:23.809084Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f3d76c21-bd21-4203-b05b-3f1dad2e931a · outbound

This paper cites Fully convolutional networks for semantic segmentation.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery Fully convolutional networks for semantic segmentation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:23.567669Z

Source-reported events for the cited work

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Observation 4eab40c6-245a-41e2-8688-9e870d741ddf · outbound

This paper cites P resence-only G eographical P riors for fine-grained image classification.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery P resence-only G eographical P riors for fine-grained image classification

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:23.370426Z

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Observation 749ad57a-6827-4897-a451-d0dd5df2f3b8 · outbound

This paper cites C sp: S elf-supervised contrastive spatial pre-training for geospatial-visual representations.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery C sp: S elf-supervised contrastive spatial pre-training for geospatial-visual representations

Reference 21

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Observation cb163b4f-302a-4d86-9256-3f4beacb543d · outbound

This paper cites M M E arth: E xploring multi-modal pretext tasks for geospatial representation learning.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery M M E arth: E xploring multi-modal pretext tasks for geospatial representation learning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:22.954786Z

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Observation a1437239-0892-45ff-aaff-eef3fcf8a1cc · outbound

This paper cites A utomatic conversion of O S M data into L U L C maps: comparing F O S S 4 G based approaches towards an enhanced performance.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery A utomatic conversion of O S M data into L U L C maps: comparing F O S S 4 G based approaches towards an enhanced performance

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:22.799951Z

Source-reported events for the cited work

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Observation c4847ff6-a8f7-4d39-a882-1e1b6890f47c · outbound

This paper cites R., Daniel, J., Mehaffey, M., Jackson, L.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery R., Daniel, J., Mehaffey, M., Jackson, L

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:22.508526Z

Source-reported events for the cited work

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Observation 19c0520e-d8ed-48f1-991a-782af041a847 · outbound

This paper cites W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:22.305609Z

Source-reported events for the cited work

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Observation b02c32b4-b102-49b7-8734-04f845d578c9 · outbound

This paper cites J., Gupta, R., Li, S., Brockman, S., Funk, C., Clipp, B., Keutzer, K., Candido, S., Uyttendaele, M., and Darrell, T.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery J., Gupta, R., Li, S., Brockman, S., Funk, C., Clipp, B., Keutzer, K., Candido, S., Uyttendaele, M., and Darrell, T

Reference 26

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Source-reported events for the cited work

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Observation 76b385ea-5ce2-4ad2-8150-222faa8c4ad1 · outbound

This paper cites A generalizable and accessible approach to machine learning with global satellite imagery.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery A generalizable and accessible approach to machine learning with global satellite imagery

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:21.867410Z

Source-reported events for the cited work

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Observation 2ca9c9c2-2a57-4b25-b67a-d865741b13ed · outbound

This paper cites Resolving label uncertainty with implicit posterior models.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery Resolving label uncertainty with implicit posterior models

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:21.689092Z

Source-reported events for the cited work

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Observation fbaace11-d154-4373-bc3b-ca7c74548a2b · outbound

This paper cites P osition: M ission C ritical-- S atellite D ata is a D istinct M odality in M achine L earning.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery P osition: M ission C ritical-- S atellite D ata is a D istinct M odality in M achine L earning

Reference 29

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Source-reported events for the cited work

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Observation 9b2c5f1e-65a9-444d-a8ca-7b28ef21bd8a · outbound

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

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery U-net: Convolutional networks for biomedical image segmentation

Reference 30

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Source-reported events for the cited work

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Observation bac27d5e-a469-417a-b78f-c5cf01ebe62f · outbound

This paper cites U -net: C onvolutional networks for biomedical image segmentation.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery U -net: C onvolutional networks for biomedical image segmentation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:21.022462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3eff8594-9bd7-4669-a106-6d96498cd450 · outbound

This paper cites A., Vakalopoulou, M., Hänsch, R., Hansen, S., Nogueira, K., Prexl, J., and Tuia, D.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery A., Vakalopoulou, M., Hänsch, R., Hansen, S., Nogueira, K., Prexl, J., and Tuia, D

Reference 32

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T17:08:16.571373Z

Source-reported events for the cited work

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Observation d834033a-ee40-40b4-b0da-f4d01a61f1b0 · outbound

This paper cites MultiMAE Meets Earth Observation: Pre-training Multi-modal Multi-task Masked Autoencoders for Earth Observation Tasks.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery MultiMAE Meets Earth Observation: Pre-training Multi-modal Multi-task Masked Autoencoders for Earth Observation Tasks

Reference 33

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Source-reported events for the cited work

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Observation cde90117-7f71-46b1-b4e1-ef2d9ec0f196 · outbound

This paper cites B igearthnet: A large-scale benchmark archive for remote sensing image understanding.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery B igearthnet: A large-scale benchmark archive for remote sensing image understanding

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:20.739093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cce16651-a7ad-4890-ae2c-c614a21dc78c · outbound

This paper cites I mproving image classification with location context.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery I mproving image classification with location context

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:20.462688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7c8a9c52-8ef6-4bff-a150-22a31b2ce0b3 · outbound

This paper cites T raining data-efficient image transformers & distillation through attention.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery T raining data-efficient image transformers & distillation through attention

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:20.171829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9e3a0082-7d2c-4d41-a2d1-57fa5fa32138 · outbound

This paper cites A ttention is all you need.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery A ttention is all you need

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:19.845770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a2c0eaae-8cdb-471d-ac16-c365c9056f7a · outbound

This paper cites K., and Shah, M.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery K., and Shah, M

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:19.602006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 41603e18-ad5b-480a-b351-bc9c3f4c1d70 · outbound

This paper cites R evisiting the P ower of P rompt for V isual T uning.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery R evisiting the P ower of P rompt for V isual T uning

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:19.314740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 67eeec23-5cd0-4a4a-9156-c1c14083cc3e · outbound

This paper cites U rban2 V ec: I ncorporating S treet V iew I magery and P O I S for M ulti- M odal U rban N eighborhood E mbedding.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery U rban2 V ec: I ncorporating S treet V iew I magery and P O I S for M ulti- M odal U rban N eighborhood E mbedding

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:19.063784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3fb6dfce-b106-4cc4-b964-1f15a3761d31 · outbound

This paper cites Water areas segmentation from remote sensing images using a separable residual segnet network.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery Water areas segmentation from remote sensing images using a separable residual segnet network

Reference 41

Resolution: verified exact; doi, observed 2026-08-06T17:08:15.757034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2cac8f70-90d5-4583-b843-d696ca726cd1 · outbound

This paper cites M., and Luo, P.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery M., and Luo, P

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:18.761207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 255c706d-b4fe-42fb-90bf-6660892d2001 · outbound

This paper cites B., and Ermon, S.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery B., and Ermon, S

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:18.489249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 328a5af7-809c-4a2c-9eb4-3daa1a5b0d5c · outbound

This paper cites R., and Zimmermann, R.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery R., and Zimmermann, R

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:18.224717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3325e02e-cee3-48c3-a4cd-2d800bf14164 · outbound

This paper cites Shift pooling pspnet: Rethinking pspnet for building extraction in remote sensing images from entire local feature pooling.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery Shift pooling pspnet: Rethinking pspnet for building extraction in remote sensing images from entire local feature pooling

Reference 45

Resolution: verified exact; doi, observed 2026-08-06T17:08:15.466569Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7aa3f221-dfb4-4566-a51f-d4e3a7dc8d0c · outbound

This paper cites E S A W orld C over 10 m 2021 v200.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery E S A W orld C over 10 m 2021 v200

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:17.963417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 61b89066-c64a-46ae-b2ba-35b38f752840 · outbound

This paper cites Pyramid scene parsing network.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery Pyramid scene parsing network

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T17:08:17.696336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d8021eaf-8d99-4c10-b665-fa0244b7eb7a · outbound

This paper cites write newline.

Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery write newline

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T17:08:15.326984Z

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Unavailable: canonical work link unavailable.

Pith citing papers

Observation 6b963297-b13f-458b-840d-5b7ed0442d08 · inbound

Better Together: Evaluating the Complementarity of Earth Embedding Models cites this paper.

Better Together: Evaluating the Complementarity of Earth Embedding Models Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-20T11:53:14.843080Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8819990c-c83d-413e-88ed-dd04628ca086 · inbound

Better Together: Evaluating the Complementarity of Earth Embedding Models cites this paper.

Better Together: Evaluating the Complementarity of Earth Embedding Models Using Multiple Input Modalities Can Improve Data-Efficiency and O.O.D. Generalization for ML with Satellite Imagery

Reference 17

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T11:53:14.733198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.