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Paper Citation Record · LEDGER

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation

As of 12 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2606.30647.

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

pith.paper-citation-record.v1
2606.30647 v1

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measured 58 of 58 reference resolution

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

58 of 58 outbound references displayed

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External citation measurements

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Outbound references

Observation eae27384-54df-4349-97c4-c4f0a4674b57 · outbound

This paper cites an unresolved cited work.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Unresolved cited work

Reference 1

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Observation d646cd57-c020-45f1-9aae-de93ec6a90d6 · outbound

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

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Accurate medium-range global weather forecasting with 3D neural networks

Reference 2

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Observation 03c64904-d1ce-418d-adfd-ed0649d1f937 · outbound

This paper cites MVS- NeRF: Fast generalizable radiance field reconstruc- tion from multi-view stereo.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation MVS- NeRF: Fast generalizable radiance field reconstruc- tion from multi-view stereo

Reference 3

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Observation a2b42b48-2106-4323-9f48-c8cf97072027 · outbound

This paper cites Intent: Invari- ance and discrimination-aware noise mitigation for ro- bust composed image retrieval.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Intent: Invari- ance and discrimination-aware noise mitigation for ro- bust composed image retrieval

Reference 4

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Observation ec387e6e-0640-4680-aef1-70024f4e7cdd · outbound

This paper cites Invariance and discrimination-aware noise mitigation for robust com- posed image retrieval.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Invariance and discrimination-aware noise mitigation for robust com- posed image retrieval

Reference 5

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Observation 3da14ec0-e846-4310-adc3-925899a21efd · outbound

This paper cites Learning phrase rep- resentations using RNN encoder–decoder for statistical machine translation.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Learning phrase rep- resentations using RNN encoder–decoder for statistical machine translation

Reference 6

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Observation e0dfab9e-8b37-4663-89d5-822bd21ec6f4 · outbound

This paper cites 4D spatio-temporal ConvNets: Minkowski convolutional neural networks.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation 4D spatio-temporal ConvNets: Minkowski convolutional neural networks

Reference 7

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Observation 5b494a5d-85d6-4446-adad-07cc265e0cc2 · outbound

This paper cites Savoy, Yee Hui Lee, and Stefan Winkler.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Savoy, Yee Hui Lee, and Stefan Winkler

Reference 8

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Observation 241e707f-5e6e-4079-bb9e-78371e5ed714 · outbound

This paper cites FlowNet: Learning optical flow with convolutional net- works.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation FlowNet: Learning optical flow with convolutional net- works

Reference 9

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Observation e410a8ee-a967-4f89-b30f-11768271f007 · outbound

This paper cites Academic Press, 2nd edi- tion, 1993.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Academic Press, 2nd edi- tion, 1993

Reference 10

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Observation 7b215527-29d6-4b60-b26c-c86f6656ae7e · outbound

This paper cites Scott Frisch, Graham Feingold, Christopher W.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Scott Frisch, Graham Feingold, Christopher W

Reference 11

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Observation 24e1537a-194e-4187-810b-b4a8697847dd · outbound

This paper cites Air-know: Arbiter-calibrated knowledge-internalizing robust network for composed image retrieval.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Air-know: Arbiter-calibrated knowledge-internalizing robust network for composed image retrieval

Reference 12

Resolution
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Observation a41054ba-c53c-4c37-a592-03d14113931f · outbound

This paper cites Modeling the dynamics of PDE systems with physics-constrained deep auto-regressive networks.Journal of Computa- tional Physics, 403:109056, 2020.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Modeling the dynamics of PDE systems with physics-constrained deep auto-regressive networks.Journal of Computa- tional Physics, 403:109056, 2020

Reference 13

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Observation e37c874f-9089-494f-bba6-058ad333412a · outbound

This paper cites Cambridge University Press, 2nd edition, 2003.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Cambridge University Press, 2nd edition, 2003

Reference 14

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Observation 03a9d8bd-a319-47e0-8f62-cce24449f75f · outbound

This paper cites Au- tomatic cloud classification of whole sky images.Atmo- spheric Measurement Techniques, 3(3):557–567, 2010.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Au- tomatic cloud classification of whole sky images.Atmo- spheric Measurement Techniques, 3(3):557–567, 2010

Reference 15

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Observation b3ddfa5c-7e5d-4c68-a02e-adc78054ef2b · outbound

This paper cites The ERA5 global reanalysis.Quarterly Journal of the Royal Meteorological Society, 146(730):1999–2049, 2020.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation The ERA5 global reanalysis.Quarterly Journal of the Royal Meteorological Society, 146(730):1999–2049, 2020

Reference 16

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Observation da7de48c-a107-481b-96d3-6ee2143920f4 · outbound

This paper cites Denois- ing diffusion probabilistic models.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Denois- ing diffusion probabilistic models

Reference 17

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Observation cf35e7d1-8a20-4ae8-a725-f57ada9a1367 · outbound

This paper cites Horn and Brian G.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Horn and Brian G

Reference 18

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Observation 0d11d0f5-3eaa-4ec7-b4b0-6b413771188c · outbound

This paper cites Refine: Com- posed video retrieval via shared and differential seman- tics enhancement.ACM Transactions on Multimedia Computing, Communications and Applications, 2026.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Refine: Com- posed video retrieval via shared and differential seman- tics enhancement.ACM Transactions on Multimedia Computing, Communications and Applications, 2026

Reference 19

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Observation 29835539-31d2-4e01-a000-5a9e6a5e1aec · outbound

This paper cites Kevrekidis, Lu Lu, Paris Perdikaris, Sifan Wang, and Liu Yang.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Kevrekidis, Lu Lu, Paris Perdikaris, Sifan Wang, and Liu Yang

Reference 20

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Observation 67dc5b58-aa23-496b-8567-abc12abcc275 · outbound

This paper cites Kingma and Max Welling.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Kingma and Max Welling

Reference 21

Resolution
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Observation a6bc4ece-559a-4dad-8061-6ceabec15221 · outbound

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

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Learning skillful medium-range global weather forecasting.Science, 382(6677):1416–1421, 2023

Reference 22

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Observation 5737a3bb-929a-4b02-9105-14ae5f96067f · outbound

This paper cites Airborne three-dimensional cloud to- mography.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Airborne three-dimensional cloud to- mography

Reference 23

Resolution
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Observation 7e64ef22-a8ce-4f8c-bb6a-49cd5f2a922c · outbound

This paper cites Multiple-scattering microphysics tomography.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Multiple-scattering microphysics tomography

Reference 24

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Observation 469b078d-389c-48df-9da7-00826c4cde60 · outbound

This paper cites Multi-view polarimetric scattering cloud tomography and retrieval of droplet size.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Multi-view polarimetric scattering cloud tomography and retrieval of droplet size

Reference 25

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Observation 60d11fa3-a04e-4956-acb7-932369b4cbac · outbound

This paper cites Exploring efficient open-vocabulary segmentation in the remote sensing.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Exploring efficient open-vocabulary segmentation in the remote sensing

Reference 26

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Observation 70c3335c-ff38-4a44-98b8-f5ae606c5aaa · outbound

This paper cites Exploring the underwater world segmentation without extra training.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Exploring the underwater world segmentation without extra training

Reference 27

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Observation b5636670-8f42-4fff-a713-82a9ec9abc43 · outbound

This paper cites Maris: Marine open-vocabulary in- stance segmentation with geometric enhancement and se- mantic alignment.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Maris: Marine open-vocabulary in- stance segmentation with geometric enhancement and se- mantic alignment

Reference 28

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Observation 6e44ef2d-7417-4b3f-b6a5-322bd4cef378 · outbound

This paper cites Stitchfusion: Weaving any visual modal- ities to enhance multimodal semantic segmentation.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Stitchfusion: Weaving any visual modal- ities to enhance multimodal semantic segmentation

Reference 29

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

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Observation 960c1306-098d-4704-9437-9592dd73262d · outbound

This paper cites U3m: Unbiased multiscale modal fusion model for multimodal semantic segmentation.Pattern Recognition, 168:111801, 2025.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation U3m: Unbiased multiscale modal fusion model for multimodal semantic segmentation.Pattern Recognition, 168:111801, 2025

Reference 30

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Observation 5032ec3f-9169-47bd-802f-8b44bb75682b · outbound

This paper cites Retrack: Evidence-driven dual-stream directional anchor calibra- tion network for composed video retrieval.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Retrack: Evidence-driven dual-stream directional anchor calibra- tion network for composed video retrieval

Reference 31

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Observation 94d167a9-274f-448a-9497-54c0946f7236 · outbound

This paper cites Conesep: Cone-based ro- bust noise-unlearning compositional network for com- posed image retrieval.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Conesep: Cone-based ro- bust noise-unlearning compositional network for com- posed image retrieval

Reference 32

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Observation 9a932d89-eca0-4609-a681-b723381f2b45 · outbound

This paper cites Habit: Chrono-synergia robust progressive learning framework for composed image retrieval.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Habit: Chrono-synergia robust progressive learning framework for composed image retrieval

Reference 33

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:69bfb4fa1810ac0ce468449ac4fabf61896f7b783af024f72d9ba94fb688f925

Observation 1d0870e1-ff34-455e-808f-fa83ab30552b · outbound

This paper cites Habit: Chrono-synergia robust progressive learning framework for composed image retrieval.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Habit: Chrono-synergia robust progressive learning framework for composed image retrieval

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.484238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:6c82d8f5d80b8f30d8055de3b681bf25f055f9001a06f9226a5d34350431e3d4

Observation 02e76379-ea31-4dd8-959d-476f21751535 · outbound

This paper cites Decoupled weight decay regularization.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Decoupled weight decay regularization

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.487921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:7886b7f184be096262d1c3bf6f8046287944745abc6fe23264e94c49dc8da85b

Observation cd12745f-9194-4f0c-9662-8735d7ca6751 · outbound

This paper cites NeRF: Representing scenes as neural radiance fields for view synthesis.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation NeRF: Representing scenes as neural radiance fields for view synthesis

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.480506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:43e1603992d6f6faa8f72d2a37fd1bf2c42d81e7deed3b871032e3c0950dd058

Observation 298c2848-a071-4e8b-8d1c-1eae2289dda6 · outbound

This paper cites Determina- tion of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Determina- tion of the optical thickness and effective particle radius of clouds from reflected solar radiation measurements

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.477212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:641409e43725f04aea26e13db150b54d885151b9158151d39f82f7f320ca3a4d

Observation 4aa2ff1f-f604-4fac-aaf8-bdb1f3cc62e8 · outbound

This paper cites King, Steven A.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation King, Steven A

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.478821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:e371badd29258bd3ff04e9bdf68720d0678d9643dde824810209f931165acb50

Observation aa079377-841f-4378-a2fc-9bd2556688fb · outbound

This paper cites Andersson, Andrew El-Kadi, Dominic Masters, Timo Ewalds, Jacklynn Stott, Shakir Mohamed, Peter Battaglia, Remi Lam, Matthew Willson, et al.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Andersson, Andrew El-Kadi, Dominic Masters, Timo Ewalds, Jacklynn Stott, Shakir Mohamed, Peter Battaglia, Remi Lam, Matthew Willson, et al

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.493223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:51d9f08fc1bf5933da207ac1a899e2abf1ca94b83e64132beef0f62b99c4e4e4

Observation e988c3a2-1eff-4a43-996c-fd6aed3efd9b · outbound

This paper cites an unresolved cited work.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Unresolved cited work

Reference 40

Resolution
unresolved
raw_fallback, observed 2026-07-06T15:52:39.465277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:e6d179b8c2eb274165bae443892957b6089d4d504d002925b47420fd3302afb0

Observation 7230a738-91fe-4902-a8de-c96fb8df966a · outbound

This paper cites VIP-CT: Variable importance parametric cloud tomog- raphy.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation VIP-CT: Variable importance parametric cloud tomog- raphy

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.489679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:b1d2e81aaf49b26114b56b0f34ad0da6241382c423a53d090ce9e82f805fb13c

Observation 05eb30de-3d40-4e99-9a13-3d335afd2c6a · outbound

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

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation U-Net: Convolutional networks for biomedical image segmentation

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.458547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:f79183363de2984d168b642e3321bca380b287cdf8b44d67ea7e777008270e10

Observation 84fbf0b1-47e0-466c-8714-46afe2bf30e6 · outbound

This paper cites Sarkar, M.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Sarkar, M

Reference 43

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T08:35:34.275828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:402b7526635dce13e6bc94c7091ffe8f838ef2dd39a61c822ca463135d25a84f

Observation b173be94-c572-4ed2-8ccf-db26df591e64 · outbound

This paper cites A large eddy simula- tion intercomparison study of shallow cumulus convec- tion.Journal of the Atmospheric Sciences, 60(10):1201– 1219, 2003.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation A large eddy simula- tion intercomparison study of shallow cumulus convec- tion.Journal of the Atmospheric Sciences, 60(10):1201– 1219, 2003

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.509381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:c7e5121ffc5def4d6641ac1a10459e0e089f69cfeec4e1efbd9ffa4b83dc90ff

Observation abf1a852-e5ab-415c-9686-15163ecb26cc · outbound

This paper cites Learning structured output representation using deep conditional generative models.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Learning structured output representation using deep conditional generative models

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.513023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:dde8cb11860f7f0e1b4b8aeaeb828e05aca9036331cd019adfc35545eb9ef5e0

Observation bda645cd-87b2-4e56-9dfd-8a6b8ac5e34d · outbound

This paper cites De- noising diffusion implicit models.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation De- noising diffusion implicit models

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.527255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:c9acf3d5d55fb32ceac68cc4414cc0d8ecf8b87cc4144b0caed82db4830c39f0

Observation 0086f0da-403c-41de-a355-ea4f87df1743 · outbound

This paper cites Stephens.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Stephens

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.486009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:128216d686cb9b9012fbbbf4ddba6618b6a77037761bbecc43ba22080847cbbd

Observation d7752927-99aa-42d8-8409-e6b025d0f02a · outbound

This paper cites an unresolved cited work.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-07-06T15:52:39.516438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:2596f21f750694d2cd291dc7cef2299b32c15536a2e0ff8ff70e8bc1324ca6ef

Observation af870071-1e46-4693-934e-6d3f8b7b80ae · outbound

This paper cites RAFT: Recurrent all-pairs field transforms for optical flow.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation RAFT: Recurrent all-pairs field transforms for optical flow

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.444932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:0a32d1076df2b99744bacb6b60259c5f9ff6a17ebfa8725939feb3ad80cb3963

Observation 1c8b3c28-30e6-4692-a85c-f5d9871d6720 · outbound

This paper cites van Heerwaarden, Bart J.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation van Heerwaarden, Bart J

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.448321Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:b3c807b346ec2cc7bc41936f99f2aee1576d283265f45c40a2f74636785cbbfe

Observation 6f2cafea-a745-40c1-8135-67ebc72ed8bc · outbound

This paper cites Three-dimensional scene flow.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Three-dimensional scene flow

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.451626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:18b658329de9d9ed14f6161fd6049ca2c3f6606427f5e67ff6edaaf98ffa2bf5

Observation b0bed5e3-3800-4c11-8dde-2b232e09f44c · outbound

This paper cites Velden, Christopher M.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Velden, Christopher M

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.441439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:2b590a4cbf25403664eef2f71cfd79047770f34cec5b85f689f027a1a945c2a6

Observation 3dbcacac-aa14-42d8-876c-fa1a2005ade9 · outbound

This paper cites MVSNet: Depth inference for unstructured multi- view stereo.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation MVSNet: Depth inference for unstructured multi- view stereo

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.443159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:c13cc8da31fb18ade1592282b7bd54603d186d1b7ec4dcbb38a35109bd8d28a6

Observation 98d55324-082f-4fc3-9337-8fb1f7b5a300 · outbound

This paper cites pixelNeRF: Neural radiance fields from one or few images.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation pixelNeRF: Neural radiance fields from one or few images

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.521665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:3b1b274815a88712c1141188d8ebb3028b8fc2b0fe7e090c7dc26d9f4596b6d6

Observation 88d17aa1-fcac-4b2b-a331-6fc4964854f0 · outbound

This paper cites From Physics to Foundation Models: A Review of AI-Driven Quantitative Remote Sensing Inversion.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation From Physics to Foundation Models: A Review of AI-Driven Quantitative Remote Sensing Inversion

Reference 55

Resolution
verified exact
arxiv_id, observed 2026-07-01T08:35:34.278591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:71ac99435f42cc2c3caecc8c502b98b754c0d88c2baab4cb73e6b2745183f780

Observation 9120f807-2c2b-4fd1-817c-c161cd32d730 · outbound

This paper cites Dinov3-powered multi-task founda- tion model for quantitative remote sensing estimation (student abstract).

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Dinov3-powered multi-task founda- tion model for quantitative remote sensing estimation (student abstract)

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.518235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:3b7d0a953fdebf0040b025e09cab316e81c975d7a45bd7d389136d4e14ff3c5c

Observation 3ba56db6-9b2b-4c01-89c5-f552a4961673 · outbound

This paper cites Spatiotemporal alignment for remote sens- ing image recovery via terrain-aware diffusion.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Spatiotemporal alignment for remote sens- ing image recovery via terrain-aware diffusion

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.519984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:f21972511d3d5e11c657de4fae48f29de85f7c4473b1995fa3ebf88ee2f93717

Observation 17e80292-447f-4b02-a2f4-abb46e469f33 · outbound

This paper cites Qrs-trs: Style transfer-based image- to-image translation for carbon stock estimation in quan- titative remote sensing.IEEE Access, 2025.

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation Qrs-trs: Style transfer-based image- to-image translation for carbon stock estimation in quan- titative remote sensing.IEEE Access, 2025

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-07-06T15:52:39.439605Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-07-01T07:19:36.472441Z digest=sha256:ef6e8012d5e8c1971c340790709ecdba7743e632ffdbf9930a284c6bc8e61e4e

Pith citing papers

No inbound Pith citation observations are available.