Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T16:21:14.250669Z
Paper Citation Record · LEDGER
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing
As of 18 August 2026, this Paper Citation Record lists 86 of 86 outbound references and 3 inbound Pith citation observations for arXiv:2507.13812.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-11T22:49:02.844739Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-10T19:07:35.342402Z
Reference resolution
86 of 86 outbound references displayed
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation ba463af9-5856-4eb8-842a-b27bd8359a46 · outbound
This paper cites Self- supervised material and texture representation learning for remote sensing tasks.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Self- supervised material and texture representation learning for remote sensing tasks
Reference 1
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cc29ad2f-1b5b-482d-92ce-21b721d8180c · outbound
This paper cites AnySat: One Earth Observation Model for Many Resolutions, Scales, and Modalities.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing AnySat: One Earth Observation Model for Many Resolutions, Scales, and Modalities
Reference 2
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 002f7b0f-623e-4df0-abf0-ce79687f5a4c · outbound
This paper cites Geography-aware self-supervised learning.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Geography-aware self-supervised learning
Reference 3
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 39a55ece-38bb-4e45-b45e-466fd015feb6 · outbound
This paper cites Satlaspretrain: A large- scale dataset for remote sensing image understanding.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Satlaspretrain: A large- scale dataset for remote sensing image understanding
Reference 4
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 64723a26-e79d-4329-9ff7-8b5e0d76e5cb · outbound
This paper cites A multi- scale weakly supervised learning method with adaptive on- line noise correction for high-resolution change detection of built-up areas.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing A multi- scale weakly supervised learning method with adaptive on- line noise correction for high-resolution change detection of built-up areas
Reference 5
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b1464326-fd10-4f2b-bf64-ab7bc1fb9fcc · outbound
This paper cites Unsupervised learning of visual features by contrasting cluster assignments.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Unsupervised learning of visual features by contrasting cluster assignments
Reference 6
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8dbedf7e-91d0-4571-84d4-53c2471d8130 · outbound
This paper cites Emerg- ing properties in self-supervised vision transformers.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Emerg- ing properties in self-supervised vision transformers
Reference 7
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 48319c15-b5a1-4410-99aa-9c0046f4f2d0 · outbound
This paper cites A Billion-scale Foundation Model for Remote Sensing Images.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing A Billion-scale Foundation Model for Remote Sensing Images
Reference 8
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bbc2e246-141a-410a-985e-1b88eb1e8492 · outbound
This paper cites A spatial-temporal attention- based method and a new dataset for remote sensing image change detection.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing A spatial-temporal attention- based method and a new dataset for remote sensing image change detection
Reference 9
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c6fbd82f-f83b-45ec-be4d-4fa47503bb66 · outbound
This paper cites Remote sensing im- age change detection with transformers.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Remote sensing im- age change detection with transformers
Reference 10
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7f17f884-c88e-4178-b8e1-1e6b5a1096bb · outbound
This paper cites Collaborative global-local networks for memory-efficient segmentation of ultra-high resolution images.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Collaborative global-local networks for memory-efficient segmentation of ultra-high resolution images
Reference 11
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9acf26c9-280d-4ed3-874d-a37333034483 · outbound
This paper cites A survey on object detec- tion in optical remote sensing images.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing A survey on object detec- tion in optical remote sensing images
Reference 12
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6bcf959a-fe6f-412c-b16a-5c7f299df4be · outbound
This paper cites Remote sens- ing image scene classification: Benchmark and state of the art.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Remote sens- ing image scene classification: Benchmark and state of the art
Reference 13
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 548b61d2-3977-4ff1-a491-2086ae449c7f · outbound
This paper cites Anchor-free oriented proposal generator for object detection.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Anchor-free oriented proposal generator for object detection
Reference 14
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14716760-c0d1-43d1-a1ce-0eb1147ec386 · outbound
This paper cites Satmae: Pre-training transformers for tem- poral and multi-spectral satellite imagery.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Satmae: Pre-training transformers for tem- poral and multi-spectral satellite imagery
Reference 15
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 74594aeb-1459-442a-a1cf-48c5c76a6281 · outbound
This paper cites Vision transformers need registers.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Vision transformers need registers
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:15.354150Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d57b28e5-b8d9-4a71-aefc-43baab3fc937 · outbound
This paper cites Urban change detection for multispectral earth observation using convolutional neural networks.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Urban change detection for multispectral earth observation using convolutional neural networks
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:15.338972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5c37a863-a08a-4a0f-bbb0-2f796bc5da90 · outbound
This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 18
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0a3a32e6-8002-4d37-a3b9-52ef67ff02f5 · outbound
This paper cites Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity
Reference 19
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d0cf9ce5-8014-4553-81d5-b6aae9a63040 · outbound
This paper cites an unresolved cited work.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Unresolved cited work
Reference 20
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 96896739-3c85-41f0-80b0-a190d2a6ca13 · outbound
This paper cites Multi-modal temporal attention models for crop mapping from satellite time series.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Multi-modal temporal attention models for crop mapping from satellite time series
Reference 21
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0291ad69-a549-47d5-b3d2-a3374242f41e · outbound
This paper cites Bootstrap your own latent-a new approach to self-supervised learning.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Bootstrap your own latent-a new approach to self-supervised learning
Reference 22
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 139fd756-f7d9-4047-b6ac-d2b980e680fd · outbound
This paper cites Isdnet: Integrating shallow and deep networks for efficient ultra-high resolution segmentation.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Isdnet: Integrating shallow and deep networks for efficient ultra-high resolution segmentation
Reference 23
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 9653bbc5-eb9d-48e7-b64f-dae444bb244f · outbound
This paper cites Skysense: A multi- modal remote sensing foundation model towards universal interpretation for earth observation imagery.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Skysense: A multi- modal remote sensing foundation model towards universal interpretation for earth observation imagery
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:15.262760Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 402f5b14-1712-4f13-884d-0f99ee7cf38b · outbound
This paper cites Unitr: A uni- fied and efficient multi-modal transformer for bird’s-eye- view representation.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Unitr: A uni- fied and efficient multi-modal transformer for bird’s-eye- view representation
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:15.248394Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5a92b04e-5f77-4d0a-b480-333742a81ca0 · outbound
This paper cites Bridging remote sensors with multisensor geospatial foundation models.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Bridging remote sensors with multisensor geospatial foundation models
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:15.234486Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation c09e2e93-d618-40f3-8d37-69b6fd557c95 · outbound
This paper cites Momentum contrast for unsupervised visual rep- resentation learning.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Momentum contrast for unsupervised visual rep- resentation learning
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:15.220002Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 55577f2d-5ab0-46f5-85b9-ae1e6f30f16b · outbound
This paper cites Spectralgpt: Spectral remote sensing foundation model.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Spectralgpt: Spectral remote sensing foundation model
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:15.205029Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7a81a7db-79a9-4bd7-bbbc-5f02784e5dde · outbound
This paper cites Unsuper- vised domain adaptation using a teacher-student network for cross-city classification of sentinel-2 images.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Unsuper- vised domain adaptation using a teacher-student network for cross-city classification of sentinel-2 images
Reference 29
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e86aa585-b795-4a77-a27f-1fac031f809e · outbound
This paper cites Toward accurate mapping of 30-m time-series global imper- vious surface area (gisa).
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Toward accurate mapping of 30-m time-series global imper- vious surface area (gisa)
Reference 30
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 77feeb2e-5bb6-4885-9fda-6376bdfe3c4d · outbound
This paper cites Joseph Hughes and Robert H.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Joseph Hughes and Robert H
Reference 31
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation abb95afc-217e-4d49-9678-3b75cf8bdebc · outbound
This paper cites Tutel: Adaptive mixture-of-experts at scale, 2022.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Tutel: Adaptive mixture-of-experts at scale, 2022
Reference 32
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 0aa780e5-bc9a-49a5-9530-830dbcf8b282 · outbound
This paper cites Jacobs, Michael I.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Jacobs, Michael I
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 2026-08-18T06:34:40.430872+00:00.
Observation 31c002ee-85a8-42b7-9fdf-aea056eead8a · outbound
This paper cites an unresolved cited work.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Unresolved cited work
Reference 34
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a17c30e3-ee4e-4be6-9423-953bda563412 · outbound
This paper cites Vi- sual prompt tuning.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Vi- sual prompt tuning
Reference 35
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e3e918c6-412b-4846-a86b-73639a4f229f · outbound
This paper cites Object detection in optical remote sensing images: A survey and a new benchmark.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Object detection in optical remote sensing images: A survey and a new benchmark
Reference 36
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 53d66b6c-ce83-47b8-abe6-9cc78cd27c95 · outbound
This paper cites Ori- ented reppoints for aerial object detection.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Ori- ented reppoints for aerial object detection
Reference 37
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b9fea1e8-2ddb-4ff6-be02-bddcce38a3d3 · outbound
This paper cites S2mae: A spatial-spectral pretraining foundation model for spec- tral remote sensing data.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing S2mae: A spatial-spectral pretraining foundation model for spec- tral remote sensing data
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:15.052370Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation de76f34b-3fea-465e-b860-64fc5e93bd47 · outbound
This paper cites Masked angle-aware autoencoder for remote sensing images.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Masked angle-aware autoencoder for remote sensing images
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:15.037534Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 619ba2ad-b435-4cb6-b426-f8cca961ee2f · outbound
This paper cites See- ing beyond the patch: Scale-adaptive semantic segmentation of high-resolution remote sensing imagery based on rein- forcement learning.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing See- ing beyond the patch: Scale-adaptive semantic segmentation of high-resolution remote sensing imagery based on rein- forcement learning
Reference 40
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b2df626e-3182-407d-a469-7626cf66c709 · outbound
This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Swin transformer: Hierarchical vision transformer using shifted windows
Reference 41
- Resolution
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Source-reported events for the cited work
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Observation ea49c95e-247b-4cc2-b90b-994ee66bacde · outbound
This paper cites Swin transformer v2: Scaling up capacity and resolution.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Swin transformer v2: Scaling up capacity and resolution
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.995350Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation af74101d-1fe5-417f-ac70-bfeac841e88a · outbound
This paper cites Task-customized Masked AutoEncoder via Mixture of Cluster-conditional Experts.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Task-customized Masked AutoEncoder via Mixture of Cluster-conditional Experts
Reference 43
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e50faac6-eba6-4c5a-a6c5-9f93c3a39f37 · outbound
This paper cites Fully convolutional networks for semantic segmentation.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Fully convolutional networks for semantic segmentation
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.980899Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation afc172b9-5f29-4294-b9f4-604cd4469a4b · outbound
This paper cites Sgdr: Stochastic gradient descent with warm restarts.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Sgdr: Stochastic gradient descent with warm restarts
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.967221Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 06673f9b-308a-494a-aad6-17746fc32c4c · outbound
This paper cites Decoupled Weight Decay Regularization.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Decoupled Weight Decay Regularization
Reference 46
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 09ad89a6-caa8-41a2-a092-7ea542648abe · outbound
This paper cites Land cover change detection with heterogeneous remote sensing images: Review, progress, and perspective.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Land cover change detection with heterogeneous remote sensing images: Review, progress, and perspective
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.953846Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 1e0541cc-91bd-4d7b-9468-8a28d58d8341 · outbound
This paper cites Change- aware sampling and contrastive learning for satellite images.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Change- aware sampling and contrastive learning for satellite images
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.940148Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 6c93be12-1117-4c2d-bea7-91dc0e91d321 · outbound
This paper cites Seasonal contrast: Un- supervised pre-training from uncurated remote sensing data.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Seasonal contrast: Un- supervised pre-training from uncurated remote sensing data
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.926004Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a2ef150b-54bd-4cc4-8257-e078c54b60a7 · outbound
This paper cites Towards geospatial foundation models via continual pretraining.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Towards geospatial foundation models via continual pretraining
Reference 50
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e61570ff-92e2-4103-a26d-c9a3688c68a5 · outbound
This paper cites Cmid: A unified self-supervised learning framework for remote sensing image understanding.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Cmid: A unified self-supervised learning framework for remote sensing image understanding
Reference 51
- Resolution
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- raw_fallback, observed 2026-08-06T16:21:14.899213Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b4dfc318-9253-4fca-89aa-d48e19939d8c · outbound
This paper cites Rethinking transformers pre-training for multi- spectral satellite imagery.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Rethinking transformers pre-training for multi- spectral satellite imagery
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.885260Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 81732ed3-46be-44f2-85d8-4ea9fbbdf42b · outbound
This paper cites DINOv2: Learning Robust Visual Features without Supervision.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing DINOv2: Learning Robust Visual Features without Supervision
Reference 53
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 93aab074-d092-4a07-8316-045b23f5b531 · outbound
This paper cites Learning transferable visual models from natural language supervi- sion.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Learning transferable visual models from natural language supervi- sion
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.871545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b515dffc-c961-456b-89d9-5e0edca325bc · outbound
This paper cites Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.857237Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 03dc274b-52e3-4d3c-8ea3-6f2cd0555abb · outbound
This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Faster r-cnn: Towards real-time object detection with region proposal networks
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.843383Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 01ab2e02-aeda-4c3f-b75d-eb66b048301f · outbound
This paper cites Scaling vision with sparse mix- ture of experts.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Scaling vision with sparse mix- ture of experts
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.829467Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation faf7bb4c-d272-4f4d-813f-a12446021e5d · outbound
This paper cites U- net: Convolutional networks for biomedical image segmen- tation.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing U- net: Convolutional networks for biomedical image segmen- tation
Reference 58
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation f57fe4bc-9295-435f-a994-bcdf3dc136ee · outbound
This paper cites an unresolved cited work.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Unresolved cited work
Reference 59
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7f7cbdf5-df76-4621-97c0-d9fbb6115ebc · outbound
This paper cites Mixture-of- experts meets instruction tuning: A winning combination for large language models.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Mixture-of- experts meets instruction tuning: A winning combination for large language models
Reference 60
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation de56d701-3418-428c-8871-981d489ba0a4 · outbound
This paper cites Fully Convolutional Networks for Dense Semantic Labelling of High-Resolution Aerial Imagery.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Fully Convolutional Networks for Dense Semantic Labelling of High-Resolution Aerial Imagery
Reference 61
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a850793b-2f08-491d-8629-cbd8de27be48 · outbound
This paper cites Bigearthnet: A large-scale benchmark archive for remote sensing image understanding.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Bigearthnet: A large-scale benchmark archive for remote sensing image understanding
Reference 62
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e11b0098-41b8-4d41-aaab-a74ec9b39b8d · outbound
This paper cites an unresolved cited work.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Unresolved cited work
Reference 63
- Resolution
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- raw_fallback, observed 2026-08-06T16:21:14.759836Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2c17bfc3-f9b0-4564-98b7-66b5b9357c78 · outbound
This paper cites Ringmo: A remote sensing foundation model with masked image modeling.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Ringmo: A remote sensing foundation model with masked image modeling
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.745576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ed77e2ea-0f5c-479a-8958-85d11ebcceed · outbound
This paper cites Fair1m: A benchmark dataset for fine- grained object recognition in high-resolution remote sens- ing imagery.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Fair1m: A benchmark dataset for fine- grained object recognition in high-resolution remote sens- ing imagery
Reference 65
- Resolution
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- raw_fallback, observed 2026-08-06T16:21:14.731348Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 08e825fe-1dbf-4bb8-8017-c1d81b195f9f · outbound
This paper cites Tov: The original vision model for optical re- mote sensing image understanding via self-supervised learn- ing.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Tov: The original vision model for optical re- mote sensing image understanding via self-supervised learn- ing
Reference 66
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 02ae285a-8200-430e-8cf5-beae0fbfff90 · outbound
This paper cites Dynamicearthnet: Daily multi-spectral satellite dataset for semantic change segmentation.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Dynamicearthnet: Daily multi-spectral satellite dataset for semantic change segmentation
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.702750Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation ebafaf56-3042-466a-8d97-594b10612f6f · outbound
This paper cites Enabling country-scale land cover mapping with meter-resolution satellite imagery.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Enabling country-scale land cover mapping with meter-resolution satellite imagery
Reference 68
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 382bb0c7-6dcf-4f98-962d-556e719f9240 · outbound
This paper cites an unresolved cited work.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Unresolved cited work
Reference 69
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 188e0b85-b7ea-4189-9f68-646db3b80b6c · outbound
This paper cites Advancing plain vision transformer toward remote sensing foundation model.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Advancing plain vision transformer toward remote sensing foundation model
Reference 70
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b1bf28b7-9461-4208-8cee-2c74c12d6be2 · outbound
This paper cites Scaling-up remote sensing segmentation dataset with segment anything model.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Scaling-up remote sensing segmentation dataset with segment anything model
Reference 71
- Resolution
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- raw_fallback, observed 2026-08-06T16:21:14.644433Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation e37cc064-0617-4076-85ac-97891e56cc37 · outbound
This paper cites Decoupling Common and Unique Representations for Multimodal Self-supervised Learning.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Decoupling Common and Unique Representations for Multimodal Self-supervised Learning
Reference 72
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 847cb645-3126-416b-a8de-4a368e3c7204 · outbound
This paper cites Ssl4eo-s12: A large-scale multi-modal, multi-temporal dataset for self- supervised learning in earth observation.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Ssl4eo-s12: A large-scale multi-modal, multi-temporal dataset for self- supervised learning in earth observation
Reference 73
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.629993Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation a7156116-e409-430c-906e-f893f4d21322 · outbound
This paper cites Zeng, Zhiyuan Yan, Jian Kang, and Xian Sun.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Zeng, Zhiyuan Yan, Jian Kang, and Xian Sun
Reference 74
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.615418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation b69594ab-27fb-425d-aec5-6425889607a5 · outbound
This paper cites Extending global-local view alignment for self-supervised learning with remote sensing imagery.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Extending global-local view alignment for self-supervised learning with remote sensing imagery
Reference 75
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4fe4be08-11a0-4f69-b044-2c4a27131b10 · outbound
This paper cites isaid: A large-scale dataset for instance segmentation in aerial images.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing isaid: A large-scale dataset for instance segmentation in aerial images
Reference 76
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.600438Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation deb874ef-c7db-41cf-8e04-dc656bd16c3e · outbound
This paper cites A compre- hensive survey of oriented object detection in remote sens- ing images.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing A compre- hensive survey of oriented object detection in remote sens- ing images
Reference 77
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.586635Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 23458f6c-cae9-4d54-9e06-bb082b898981 · outbound
This paper cites Residual Mixture of Experts.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Residual Mixture of Experts
Reference 78
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dbfda68e-cc54-40e5-a789-811a55f59915 · outbound
This paper cites Aid: A benchmark data set for performance evaluation of aerial scene classification.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Aid: A benchmark data set for performance evaluation of aerial scene classification
Reference 79
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.572079Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 7de7f1b0-f648-4b3b-9246-de0a5422d8c5 · outbound
This paper cites Unified perceptual parsing for scene understand- ing.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Unified perceptual parsing for scene understand- ing
Reference 80
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.557275Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 01788259-ecf4-4967-a2e2-fde6059b96e7 · outbound
This paper cites One for all: Toward unified foundation models for earth vision.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing One for all: Toward unified foundation models for earth vision
Reference 81
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.537635Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2f74c175-536a-4da8-9af0-3051afed65ad · outbound
This paper cites Graph adversarial self-supervised learning.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Graph adversarial self-supervised learning
Reference 82
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.521392Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 5bdaba82-64f0-45c8-a9fd-7f250ef37d1c · outbound
This paper cites A review of deep learning methods for semantic segmentation of remote sensing imagery.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing A review of deep learning methods for semantic segmentation of remote sensing imagery
Reference 83
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.506315Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation bb67f243-f6f9-4431-a34b-1e7889d8cf85 · outbound
This paper cites Meta-Transformer: A Unified Framework for Multimodal Learning.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Meta-Transformer: A Unified Framework for Multimodal Learning
Reference 84
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:21:14.242806Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e41e3331-d3d5-46a8-a5b2-c23fba9d3aa5 · outbound
This paper cites Uni- perceiver: Pre-training unified architecture for generic per- ception for zero-shot and few-shot tasks.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Uni- perceiver: Pre-training unified architecture for generic per- ception for zero-shot and few-shot tasks
Reference 85
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.491402Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation 2f4e2310-c2da-45df-80cb-f05ae222ecef · outbound
This paper cites Shazeer, and William Fedus.
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing Shazeer, and William Fedus
Reference 86
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T16:21:14.475522Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Pith citing papers
Observation c2fa9af4-f64f-458d-8fe8-775f780626bf · inbound
CBEN -- A Multimodal Machine Learning Dataset for Cloud Robust Remote Sensing Image Understanding cites this paper.
CBEN -- A Multimodal Machine Learning Dataset for Cloud Robust Remote Sensing Image Understanding SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T23:00:22.931089Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.
Observation d6429a49-fcfa-4941-a7f1-bbc19ecc3e5a · inbound
TESSERA v2: Scaling Pixel-wise Earth Foundation Models cites this paper.
TESSERA v2: Scaling Pixel-wise Earth Foundation Models SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-07-11T22:49:02.844739Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9c676a0b-7d2e-4884-9d09-815914f08980 · inbound
Scalable and Trustworthy Earth Observation Foundation Models cites this paper.
Scalable and Trustworthy Earth Observation Foundation Models SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing
Reference 17
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-10T19:07:35.343671Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.