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Paper Citation Record · LEDGER

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation

As of 7 August 2026, this Paper Citation Record lists 75 of 75 outbound references and 0 inbound Pith citation observations for arXiv:2507.05731.

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

pith.paper-citation-record.v1
2507.05731 v1

Coverage vector

measured 75 of 75 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

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Reference resolution

75 of 75 outbound references displayed

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External citation measurements

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Outbound references

Observation 55083fa5-6e11-4c60-aef4-b940dc2556f0 · outbound

This paper cites Democratizing{Direct- to-Cell} Low Earth Orbit Satellite Networks.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Democratizing{Direct- to-Cell} Low Earth Orbit Satellite Networks

Reference 1

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Observation cbdd103a-d2ed-4d64-9be7-64686e7beac4 · outbound

This paper cites Robust Live Stream- ing over LEO Satellite Constellations: Measurement, Analysis, and Handover-Aware Adaptation.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Robust Live Stream- ing over LEO Satellite Constellations: Measurement, Analysis, and Handover-Aware Adaptation

Reference 2

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Observation 0ea21f90-cfe7-40d8-8af6-1adca316d540 · outbound

This paper cites Spectrumize: Spectrum-Efficient Satellite Networks for the Internet of Things.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Spectrumize: Spectrum-Efficient Satellite Networks for the Internet of Things

Reference 3

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Observation 5fd34b21-7ce5-47d2-991f-bdd643809ecc · outbound

This paper cites SatFed: A Resource-Efficient LEO Satellite-Assisted Heterogeneous Federated Learning Framework.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation SatFed: A Resource-Efficient LEO Satellite-Assisted Heterogeneous Federated Learning Framework

Reference 4

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Observation 3fb0ea6b-ac77-423f-b393-d20ffabbb962 · outbound

This paper cites LEO-Split: A Semi-Supervised Split Learning Framework over LEO Satellite Networks.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation LEO-Split: A Semi-Supervised Split Learning Framework over LEO Satellite Networks

Reference 5

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Observation 9effee8a-874e-4ba3-9507-34c90a97d43f · outbound

This paper cites ESL-LEO: An Efficient Split Learning Framework over LEO Satellite Networks.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation ESL-LEO: An Efficient Split Learning Framework over LEO Satellite Networks

Reference 6

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Observation eea3e657-af02-411c-832d-86851952ddb5 · outbound

This paper cites The Digital Divide in Canada and the Role of LEO Satellites in Bridging the Gap.IEEE Commun.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation The Digital Divide in Canada and the Role of LEO Satellites in Bridging the Gap.IEEE Commun

Reference 7

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Observation 75978c17-17dc-4760-b7b0-5905c78533ce · outbound

This paper cites Available: https://www.planet.com/.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Available: https://www.planet.com/

Reference 8

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Observation 350c21db-a5d8-46df-bc4b-9271b2b7453e · outbound

This paper cites SatSense: Multi-Satellite Collabo- rative Framework for Spectrum Sensing.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation SatSense: Multi-Satellite Collabo- rative Framework for Spectrum Sensing

Reference 9

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Observation 6e8fbcf3-c781-43e3-9422-f9d490f33dac · outbound

This paper cites SigChord: Sniffing Wide Non-sparse Multiband Signals for Terrestrial and Non-terrestrial Wireless Networks.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation SigChord: Sniffing Wide Non-sparse Multiband Signals for Terrestrial and Non-terrestrial Wireless Networks

Reference 10

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Observation d594ce58-a0f3-4fb2-82ac-6c9db69e7add · outbound

This paper cites FedSN: A Federated Learning Framework over Heteroge- neous LEO Satellite Networks.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation FedSN: A Federated Learning Framework over Heteroge- neous LEO Satellite Networks

Reference 11

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Observation aa6753e0-8c02-4df5-9e15-3a4cf9cb3d9a · outbound

This paper cites LEO Satellite Networks Assisted Geo-Distributed Data Processing.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation LEO Satellite Networks Assisted Geo-Distributed Data Processing

Reference 12

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Observation 8757f660-ab83-4af0-8e39-e99c2231ef8a · outbound

This paper cites A Networking Perspective on Starlink’s Self-Driving LEO Mega-Constellation.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation A Networking Perspective on Starlink’s Self-Driving LEO Mega-Constellation

Reference 13

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Observation 4da0584a-3f0d-45c6-9805-4f2d58d1f99e · outbound

This paper cites S4: Self-Supervised Sensing Across the Spectrum.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation S4: Self-Supervised Sensing Across the Spectrum

Reference 14

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Observation cf3c05f3-0454-475c-808c-044bd51eb4c5 · outbound

This paper cites Utilizing Very High-resolution Optical RGB Satellite Imagery in Geo-information Extraction for Fine-scale Map-making.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Utilizing Very High-resolution Optical RGB Satellite Imagery in Geo-information Extraction for Fine-scale Map-making

Reference 15

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Observation 466bda76-4845-4f35-9e2b-2a5059f6d824 · outbound

This paper cites Artificial Intelligence Revolutionises Weather Forecast, Climate Moni- toring and Decadal Prediction.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Artificial Intelligence Revolutionises Weather Forecast, Climate Moni- toring and Decadal Prediction

Reference 16

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Observation 89717fcb-6d04-400d-8c4d-1bca20cab11b · outbound

This paper cites Impacts of Climate Variability and Drought on Surface Water Resources in Sub-Saharan Africa Using Remote Sensing: A Review.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Impacts of Climate Variability and Drought on Surface Water Resources in Sub-Saharan Africa Using Remote Sensing: A Review

Reference 17

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Observation 51ea067f-c6e5-4643-ab60-8a8a798b66dc · outbound

This paper cites Basic Performance and Future Developments of BeiDou Global Navigation Satellite System.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Basic Performance and Future Developments of BeiDou Global Navigation Satellite System

Reference 18

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Observation fd8a54b6-a555-40cf-abc2-a3b04c62432f · outbound

This paper cites Simultaneous Localization and Mapping (SLAM) for Au- tonomous Driving: Concept and Analysis.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Simultaneous Localization and Mapping (SLAM) for Au- tonomous Driving: Concept and Analysis

Reference 19

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Observation b92b6718-7e0e-47e8-8705-f227a360c6ce · outbound

This paper cites Spatial Analysis and GIS in the Study of COVID-19.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Spatial Analysis and GIS in the Study of COVID-19

Reference 20

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Observation 45fef73d-9a6d-4ebe-bf62-3d663a2c2184 · outbound

This paper cites Seeing Through Clouds in Satellite Images.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Seeing Through Clouds in Satellite Images

Reference 21

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Observation d6081de7-6eb8-42aa-9d2e-23666c7148f7 · outbound

This paper cites A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation A Generalizable and Accessible Approach to Machine Learning with Global Satellite Imagery

Reference 22

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Observation 9d4e50e2-19c3-4526-afa1-47d3cf0e1c0d · outbound

This paper cites Large Selective Kernel Network for Remote Sensing Object Detection.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Large Selective Kernel Network for Remote Sensing Object Detection

Reference 23

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Observation eb9bb9ba-5da4-42a0-8257-e721105a7595 · outbound

This paper cites Efficient Parallel Split Learning over Resource-Constrained Wireless Edge Networks.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Efficient Parallel Split Learning over Resource-Constrained Wireless Edge Networks

Reference 24

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Observation 1bad15a1-8dc9-42c2-a6ba-2a48282fb3ca · outbound

This paper cites IC3M: In-Car Multimodal Multi-object Monitoring for Abnormal Status of Both Driver and Passengers.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation IC3M: In-Car Multimodal Multi-object Monitoring for Abnormal Status of Both Driver and Passengers

Reference 25

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Observation 67f4ff11-eb1d-4d1c-9af9-4cbf456ae5f7 · outbound

This paper cites RF-Based Human Activity Recognition Using Signal Adapted 9 ACM MM’25, October, 2025, Dublin, Ireland Y.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation RF-Based Human Activity Recognition Using Signal Adapted 9 ACM MM’25, October, 2025, Dublin, Ireland Y

Reference 26

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

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Observation af6fd3d2-f8de-499e-9f8d-76f799f610a3 · outbound

This paper cites SUMS: Sniffing Unknown Multiband Signals under Low Sampling Rates.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation SUMS: Sniffing Unknown Multiband Signals under Low Sampling Rates

Reference 27

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

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Observation 34fcf758-1205-4a2f-bfeb-fa882ccb5a71 · outbound

This paper cites Constructing 4D Radio Map in LEO Satellite Networks with Limited Samples.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Constructing 4D Radio Map in LEO Satellite Networks with Limited Samples

Reference 28

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

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Observation 4b492ff9-63f1-4545-9980-6fc56b22d189 · outbound

This paper cites Accelerating Federated Learning with Model Segmentation for Edge Networks.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Accelerating Federated Learning with Model Segmentation for Edge Networks

Reference 29

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

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Observation dbdea996-b2fa-4ecf-9373-81dbacc54322 · outbound

This paper cites MERIT: Multimodal Wearable Vital Sign Waveform Monitoring.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation MERIT: Multimodal Wearable Vital Sign Waveform Monitoring

Reference 30

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Observation 227a4a07-cb76-4c68-93a2-133abc0ae34e · outbound

This paper cites Convolutional Neural Networks Based Remote Sensing Scene Classification under Clear and Cloudy Environments.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Convolutional Neural Networks Based Remote Sensing Scene Classification under Clear and Cloudy Environments

Reference 31

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

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Observation 5e4d3b6a-477b-410d-afd0-35fbd2bf8bcc · outbound

This paper cites Graph Learning for Multi-Satellite Based Spectrum Sensing.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Graph Learning for Multi-Satellite Based Spectrum Sensing

Reference 32

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

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Observation 770054e8-dd72-41c5-9768-d654af0509f2 · outbound

This paper cites HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation HASFL: Heterogeneity-aware Split Federated Learning over Edge Computing Systems

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:39.944675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:39.944675Z digest=sha256:1a9fb7f6ead9590fc452a9982a370eccd220e9a14f291c08302716264f4f607b

Observation 6d9e545b-ab63-4d31-94b2-92db1284a837 · outbound

This paper cites Netllm: Adapting Large Language Models for Networking.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Netllm: Adapting Large Language Models for Networking

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:50.719351Z

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.

source=pdf_text observed=2026-08-06T19:24:40.083040Z digest=sha256:b54298a707f3a39fa4ce89a5eed2d8cec4aeda4e8362fb42e37fa6942d2a27f3

Observation dd76fdb9-3330-4977-8e0e-4f591ebe5107 · outbound

This paper cites LCFed: An Efficient Clustered Federated Learning Framework for Heterogeneous Data.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation LCFed: An Efficient Clustered Federated Learning Framework for Heterogeneous Data

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:40.247634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:40.247634Z digest=sha256:2d80c51de9e052b5b98dfb8bfec81b141b6cabb4feda650e31588b4deaa4b4b8

Observation fb4fb4d6-04fe-40ea-b602-0bcd9a44d187 · outbound

This paper cites Gradient free personalized federated learning.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Gradient free personalized federated learning

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:50.573844Z

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.

source=pdf_text observed=2026-08-06T19:24:40.378055Z digest=sha256:e4637d8c8c0ef05867c8af319338ac8b5ebafc05e9d611efb66c3397a2ec02e5

Observation 9749c8ef-bb78-45d4-be6c-c8801eecda1e · outbound

This paper cites Adaptsfl: Adaptive Split Federated Learning in Resource-Constrained Edge Networks.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Adaptsfl: Adaptive Split Federated Learning in Resource-Constrained Edge Networks

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:50.390911Z

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.

source=pdf_text observed=2026-08-06T19:24:40.526470Z digest=sha256:8c595cc5b00b42f1a47dc1d647c1eae0bc22b74456cfbfd020ed48ef13415541

Observation 4e3fa19d-c479-460e-813b-abc9d8168113 · outbound

This paper cites Scaling Laws for Neural Language Models.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Scaling Laws for Neural Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:40.647277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:40.647277Z digest=sha256:707756bdf470b0d18c830163891889df3db188bea3ef6d521e2b739bc8da44e7

Observation c9669ced-1e7c-45a8-a21c-b8ec5d993d04 · outbound

This paper cites SpectralGPT: Spectral Remote Sensing Foundation Model.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation SpectralGPT: Spectral Remote Sensing Foundation Model

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:50.219367Z

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.

source=pdf_text observed=2026-08-06T19:24:40.788859Z digest=sha256:90fdcd151f2c0e384d22a18d0e8f5571e9c2aab87ab1a283b9bda9ec00326463

Observation 99bbbee3-a8d1-4537-88ec-f34ed9ac1369 · outbound

This paper cites HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Models.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Models

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:40.928721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:40.928721Z digest=sha256:107bacd088e8c611311a73efbaf81db85fd6525cf53df39b609bd58faeaf5fed

Observation e354413d-3a8f-411b-bbfe-772865f0e878 · outbound

This paper cites RemoteCLIP: A Vision Language Foundation Model for Remote Sensing.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:50.029291Z

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.

source=pdf_text observed=2026-08-06T19:24:41.075096Z digest=sha256:6d824d4af743103a5fc5833776a61549910221d82aab782a383687291cc51523

Observation 7f11b0c2-d0f6-46fc-9701-6f9647c72847 · outbound

This paper cites EarthGPT: A Universal Multimodal Large Language Model for Multi- sensor Image Comprehension in Remote Sensing Domain.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation EarthGPT: A Universal Multimodal Large Language Model for Multi- sensor Image Comprehension in Remote Sensing Domain

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:49.824297Z

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.

source=pdf_text observed=2026-08-06T19:24:41.198746Z digest=sha256:c76d9c7ad78e02b128b1c98fcef7d8b6cbf7873d6521b7066e1557c7baabad70

Observation 5d82597f-9204-4330-9b61-f341af8fb186 · outbound

This paper cites SkyEyeGPT: Unifying Remote Sensing Vision-Language Tasks via Instruction Tuning with Large Language Model.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation SkyEyeGPT: Unifying Remote Sensing Vision-Language Tasks via Instruction Tuning with Large Language Model

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:41.352311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:41.352311Z digest=sha256:85412e4d03507c9ea9def348c10da95e89a68a7d3634aa12833d4ee17c122901

Observation bc22fc49-abeb-4155-80ab-d9591c8009a2 · outbound

This paper cites Vision- Language Models for Vision Tasks: A Survey.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Vision- Language Models for Vision Tasks: A Survey

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:49.670131Z

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.

source=pdf_text observed=2026-08-06T19:24:41.486221Z digest=sha256:28691c638237fc5da82f7a39b6ddae82d836a437c4b825d18f89b89404d81f3b

Observation 344e520a-b02b-4a8e-afc9-04a035317e68 · outbound

This paper cites PIP: Detecting Adversarial Examples in Large Vision- Language Models via Attention Patterns of Irrelevant Probe Questions.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation PIP: Detecting Adversarial Examples in Large Vision- Language Models via Attention Patterns of Irrelevant Probe Questions

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:49.448270Z

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.

source=pdf_text observed=2026-08-06T19:24:41.635595Z digest=sha256:a77c8230ddc2cee2f8d8af819380774cfcec6e855a332b1eace718e11d23c994

Observation 44316db7-1f0e-4eba-853b-9b9dcba37572 · outbound

This paper cites Break the Visual Perception: Adversarial Attacks Targeting Encoded Visual Tokens of Large Vision-Language Models.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Break the Visual Perception: Adversarial Attacks Targeting Encoded Visual Tokens of Large Vision-Language Models

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:49.309874Z

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.

source=pdf_text observed=2026-08-06T19:24:41.758807Z digest=sha256:d68b715798e6a5459f4b1e953c043d27da7d80835e641546e080d34766365dca

Observation 16ad7491-df97-4212-b036-8887fe027ada · outbound

This paper cites Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:41.857105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:41.857105Z digest=sha256:f15c4f1d59e7a9cbc56fa8281cc84bdc06f7cee90410feb79644884d1b3447a4

Observation 9e4f6592-714a-4863-8e73-5a5840144fc0 · outbound

This paper cites SplitLoRA: A Split Parameter-Efficient Fine-Tuning Framework for Large Language Models.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation SplitLoRA: A Split Parameter-Efficient Fine-Tuning Framework for Large Language Models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:41.982953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:41.982953Z digest=sha256:48c03e8c392a79b564661b71c9ea50d37f1da94063c4bbe69f4938c1966b288f

Observation f51a903b-f5ed-4472-98ce-1e9ade80a063 · outbound

This paper cites Zero-Shot Text-to-Image Generation.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Zero-Shot Text-to-Image Generation

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:49.223125Z

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.

source=pdf_text observed=2026-08-06T19:24:42.146073Z digest=sha256:76fa9b5d98d4c22003b45154912ea28d2611e4521162520403f2af6bbe73d427

Observation 70b63d3a-f6f9-4fbd-91e0-ef39cee1fe17 · outbound

This paper cites GeoChat: Grounded Large Vision-Language Model for Remote Sensing.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation GeoChat: Grounded Large Vision-Language Model for Remote Sensing

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:49.129446Z

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.

source=pdf_text observed=2026-08-06T19:24:42.280070Z digest=sha256:1f5ae11bf9fe3bec7f2d78e40f197510b9026ee1dd526dead32b0299cec43da1

Observation 5384ca31-7b3c-4444-9ebb-2069e32e353d · outbound

This paper cites Orbital Edge Computing: Nanosatellite Constellations as a New Class of Computer System.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Orbital Edge Computing: Nanosatellite Constellations as a New Class of Computer System

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:49.058852Z

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.

source=pdf_text observed=2026-08-06T19:24:42.405170Z digest=sha256:b9170153f2b140f4ff237f9f1d13fec3cd5ea6490cdd9caf066cc40973a06a61

Observation acf3eff6-43f8-41e7-abb1-bbeba0f8ab81 · outbound

This paper cites Small Satellites and Big Antennas.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Small Satellites and Big Antennas

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:48.954398Z

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.

source=pdf_text observed=2026-08-06T19:24:42.557958Z digest=sha256:a837ee558e44a0eb2d15bc9b8c089a6a5ad59b37a9402c044f7808dfa47b76d1

Observation 2108740c-ba93-40f2-95c2-383b0cfb4cf1 · outbound

This paper cites Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:42.692635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:42.692635Z digest=sha256:c64fd2cda151571e5588e788c523d2d9df03c509b34b89ea7c4df7735cbc8dd5

Observation b9d9932d-0a4f-4432-ba52-274dc06312ca · outbound

This paper cites S-leon: An efficient split learning framework over heterogeneous leo satellite networks.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation S-leon: An efficient split learning framework over heterogeneous leo satellite networks

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:48.750035Z

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.

source=pdf_text observed=2026-08-06T19:24:42.781787Z digest=sha256:056d31b82d9ad23eaa35b173cc5a1eda5df8ccf93f7501b2476ae4413765a58f

Observation bdaa1eed-97ac-4a5f-9963-8cda262370bb · outbound

This paper cites L2D2: Low Latency Distributed Downlink for LEO Satellites.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation L2D2: Low Latency Distributed Downlink for LEO Satellites

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:48.624582Z

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.

source=pdf_text observed=2026-08-06T19:24:42.901182Z digest=sha256:fcb71def6cf049bcb44bff402cadb7f82beffb72f7e79552e328c7ae47fcceaa

Observation 6c6c7d04-e943-4092-90f2-98aed2acb93a · outbound

This paper cites DOTA: A Large-Scale Dataset for Object Detection in Aerial Images.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation DOTA: A Large-Scale Dataset for Object Detection in Aerial Images

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:48.476058Z

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.

source=pdf_text observed=2026-08-06T19:24:43.018516Z digest=sha256:ec26d65c2a614c3a0b6140b815c249c334e37cfc01436d9776d181d2d4523c55

Observation 72c110b8-3d9c-45a8-bc18-4c29d402bfba · outbound

This paper cites Deploying Machine Learning Anom- aly Detection Models to Flight Ready AI Boards.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Deploying Machine Learning Anom- aly Detection Models to Flight Ready AI Boards

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:48.304494Z

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.

source=pdf_text observed=2026-08-06T19:24:43.139262Z digest=sha256:df34f66ba635c373252491663f8635cd109e058dbc92f436c6e111e451740d45

Observation 649175f3-cc70-464b-8e20-5e0971572f31 · outbound

This paper cites Machine-Learning Space Applications on SmallSat Platforms with TensorFlow.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Machine-Learning Space Applications on SmallSat Platforms with TensorFlow

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:48.225974Z

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.

source=pdf_text observed=2026-08-06T19:24:43.252288Z digest=sha256:97a440f70cbccc5f19b115cd96221845cf023e2020781ab36a460606ea73f9a6

Observation 79802a19-6fd4-43bb-9752-30b9cde91aa9 · outbound

This paper cites Onboard Processing With Hybrid and Reconfigurable Computing on Small Satellites.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Onboard Processing With Hybrid and Reconfigurable Computing on Small Satellites

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:48.100837Z

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.

source=pdf_text observed=2026-08-06T19:24:43.384790Z digest=sha256:41f7c5fc018e1e0d367c00c9e835c2b5a5203fd67be619e0daf11d154e688b7b

Observation 06e26b74-134c-4dbe-9ca2-cb25b7b294c0 · outbound

This paper cites an unresolved cited work.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Unresolved cited work

Reference 60

Resolution
unresolved
raw_fallback, observed 2026-08-06T19:24:47.969585Z

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.

source=pdf_text observed=2026-08-06T19:24:43.518175Z digest=sha256:223e2cad527c013fa0b08db14a53397d80c8e9dfb0d92bb5f6c1cc961b669ae1

Observation 67f43b8a-0ff5-4a12-869d-59e256a189db · outbound

This paper cites RSVQA: Visual Question Answering for Remote Sensing Data.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation RSVQA: Visual Question Answering for Remote Sensing Data

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:47.828812Z

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.

source=pdf_text observed=2026-08-06T19:24:43.627006Z digest=sha256:3e9614d5f9aae4f6c06ce509c3244c482a957aa8ad9f6c6316a6dc88bdc37bfb

Observation dec5e28f-a01f-40c0-889e-bc1c1f9fbda1 · outbound

This paper cites Remote Sensing Image Scene Classification: Benchmark and State of the Art.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Remote Sensing Image Scene Classification: Benchmark and State of the Art

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:47.728406Z

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.

source=pdf_text observed=2026-08-06T19:24:43.771515Z digest=sha256:f11e919942a2d9182b85a9a259bd48bc9ff08ec7e6f4c05541cc5f77c1836490

Observation 828d0e01-2a55-4c95-b35a-adada1ff4dfb · outbound

This paper cites Planet Labs PBC Announces Real-Time Insights Tech- nology Using NVIDIA Jetson Platform.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Planet Labs PBC Announces Real-Time Insights Tech- nology Using NVIDIA Jetson Platform

Reference 63

Resolution
verified exact
raw_fallback, observed 2026-08-06T19:24:45.769178Z

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.

source=pdf_text observed=2026-08-06T19:24:43.907792Z digest=sha256:19c3157f3d3ea73f314d72bc5a910dd7ccca91a12337bd6a60b3eb37610e2e31

Observation 6b2bb911-a6d7-41a9-8544-bfa9491182a7 · outbound

This paper cites Trans- mitting, Fast and Slow: Scheduling Satellite Traffic Through Space and Time.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Trans- mitting, Fast and Slow: Scheduling Satellite Traffic Through Space and Time

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:47.630192Z

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.

source=pdf_text observed=2026-08-06T19:24:44.012927Z digest=sha256:34d5b6a7232d8657a7b2012a2e7bcd807552ea9e9e9df0a598649e57f79869a1

Observation 7c1c8726-b886-44e2-a5c3-7af66ddb08c7 · outbound

This paper cites NORAD GP Element Sets.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation NORAD GP Element Sets

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:47.536445Z

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.

source=pdf_text observed=2026-08-06T19:24:44.170901Z digest=sha256:879838a559c6ea99147dce9d7fd8e4020a682d7b64ae4dc437676024751332d8

Observation 39b7838a-090a-48fe-8b58-ee12185600fd · outbound

This paper cites UrbanCross: Enhancing Satellite Image-Text Retrieval with Cross-Domain Adaptation.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation UrbanCross: Enhancing Satellite Image-Text Retrieval with Cross-Domain Adaptation

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:47.437601Z

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.

source=pdf_text observed=2026-08-06T19:24:44.332321Z digest=sha256:a53f63ebf6813a7b64452939ae7bd988f4d4a7778cb45a38611ab18f4eb08df1

Observation 04aa7aec-2661-4934-95ee-d6c3bd176657 · outbound

This paper cites The Design and Implementation of Open vSwitch.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation The Design and Implementation of Open vSwitch

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:47.354794Z

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.

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This paper cites On the Fidelity of Single-Machine Network Emulation in Linux.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation On the Fidelity of Single-Machine Network Emulation in Linux

Reference 68

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Observation 6043e123-c52d-4b82-8959-d8e701015879 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Learning Transferable Visual Models From Natural Language Supervision

Reference 69

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Observation cc42d043-7545-435d-a421-c7737cc7900e · outbound

This paper cites Tabi: An Efficient Multi-Level Inference System for Large Language Models.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Tabi: An Efficient Multi-Level Inference System for Large Language Models

Reference 70

Resolution
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Observation b951560c-e7c4-49d9-ae40-466697b51241 · outbound

This paper cites Large Language Models (LLMs) Inference Offloading and Resource Allocation in Cloud-Edge Computing: An Active Inference Approach.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Large Language Models (LLMs) Inference Offloading and Resource Allocation in Cloud-Edge Computing: An Active Inference Approach

Reference 71

Resolution
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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.

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Observation d91cd1ef-41d9-4f02-9fbf-215499192c50 · outbound

This paper cites RSGPT: A Remote Sensing Vision Language Model and Benchmark.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation RSGPT: A Remote Sensing Vision Language Model and Benchmark

Reference 72

Resolution
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Source-reported events for the cited work

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Observation 9907d1fc-6cb8-4f1a-9713-15999a0d8dad · outbound

This paper cites Edge- Cloud Polarization and Collaboration: A Comprehensive Survey for AI.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Edge- Cloud Polarization and Collaboration: A Comprehensive Survey for AI

Reference 73

Resolution
verified fuzzy
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Source-reported events for the cited work

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

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Observation 9c69a53a-860a-430a-bb0e-0a1264eb26cf · outbound

This paper cites FedAC: An Adaptive Clustered Federated Learning Framework for Heterogeneous Data.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation FedAC: An Adaptive Clustered Federated Learning Framework for Heterogeneous Data

Reference 74

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 13f55509-b7cc-4233-9df3-793d9fc1dd26 · outbound

This paper cites Petals: Collaborative Inference and Fine-tuning of Large Models.

A Satellite-Ground Synergistic Large Vision-Language Model System for Earth Observation Petals: Collaborative Inference and Fine-tuning of Large Models

Reference 75

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.