Pith. sign in

Paper Citation Record · LEDGER

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

As of 18 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

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:24:45.399565Z

measured 75 of 75 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

75 of 75 outbound references displayed

  • verified exact2
  • verified fuzzy56
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:55.606197Z

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.

source=pdf_text observed=2026-08-06T19:24:34.940875Z digest=sha256:ceaeb4e410278e4755592ae8606257ebecb1224c4f8062175944791be62012df

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:55.518505Z

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.

source=pdf_text observed=2026-08-06T19:24:35.018756Z digest=sha256:cdd5c5fb8e73faad8665f1464b672b68a9c8439fabc5b297c0ca0ae9298a980d

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:55.441483Z

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.

source=pdf_text observed=2026-08-06T19:24:35.176957Z digest=sha256:1011ff2d7809f06d57c075ec1535c092b53bb6a3a3917dbc1b6922459f33cc2d

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:35.371662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:35.371662Z digest=sha256:628177e242c43f4a42a308b3f951740ba5fc3b3922daafd5e60c77643a2b2624

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:35.533614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:35.533614Z digest=sha256:f5f3559e076fc9db51a025b8032624acb8158a5e4ff95708d8af844dbc61f21f

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:55.366412Z

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.

source=pdf_text observed=2026-08-06T19:24:35.737213Z digest=sha256:6bd07468d601dbace5b37f100581c2a121f31acb31b717d467dd8d450347a855

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:55.224347Z

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.

source=pdf_text observed=2026-08-06T19:24:35.903421Z digest=sha256:9ce022683219c6323393b2e8e8857de87113246ff7f306acb121304723c659c5

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:55.140134Z

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.

source=pdf_text observed=2026-08-06T19:24:36.090026Z digest=sha256:8eb1a118a14bd60aacbe7c676960c567295da404aa2a432e2487e07654977a88

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:55.036945Z

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.

source=pdf_text observed=2026-08-06T19:24:36.239181Z digest=sha256:420d3ed104182feb6bb718b7a2ca7a5e45a76208b2276f631e95d04e3f7a7253

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:36.378057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:36.378057Z digest=sha256:936e23e751eb6a897ca376e6c0d2809f69cccfcf26bd3a65f3b4c9a54facf898

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:54.920063Z

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.

source=pdf_text observed=2026-08-06T19:24:36.543099Z digest=sha256:1fd4c0334d6fc3db87e2a34b5d0f9fa722e9d5ac8e175aaaac1cd7293545e020

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:54.780622Z

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.

source=pdf_text observed=2026-08-06T19:24:36.696637Z digest=sha256:0f5d7239bc54d9681b8640326bd6853093b43a739eebad5bea1a720c23029b3f

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:54.670326Z

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.

source=pdf_text observed=2026-08-06T19:24:36.905075Z digest=sha256:e9fe415e65233318a151fc66012ecf2d7ad5344266ef81622ac4dabd417e5579

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

Resolution
verified exact
local_arxiv, observed 2026-08-06T19:24:46.219626Z

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.

source=pdf_text observed=2026-08-06T19:24:37.069912Z digest=sha256:635a0b0f47baaf204c8787bfc6563bdb8caeb2e8625903791fff7194d9721934

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:54.508410Z

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.

source=pdf_text observed=2026-08-06T19:24:37.215358Z digest=sha256:29cd97ee0447b35986e82d676beca9fca029f571558c125f736bdf583285723c

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:54.247196Z

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.

source=pdf_text observed=2026-08-06T19:24:37.358704Z digest=sha256:914cd1e5a9265512b6f24e477a009fc195fe9f5231b47a9933600d45cc518c08

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:53.968454Z

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.

source=pdf_text observed=2026-08-06T19:24:37.549395Z digest=sha256:fec04df7024e131b8b8c277b19509b6c63d52dc05c0aa9727068cf5d3cff6a0f

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:53.744759Z

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.

source=pdf_text observed=2026-08-06T19:24:37.704405Z digest=sha256:0b645cbb4c00a0b9f73b712215f4698d38b5b7ad55ced9971a99de05ad52e641

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:53.545304Z

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.

source=pdf_text observed=2026-08-06T19:24:37.860339Z digest=sha256:5a43610a8056e0e5c21f637653b3d12ea81861db44236b009baca2f5fe36c664

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:53.275379Z

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.

source=pdf_text observed=2026-08-06T19:24:38.073429Z digest=sha256:a7694b93b7ce5a9ac6be652436902e3680a02eeaa18e14fc915a8b32374aadf4

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:53.000042Z

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.

source=pdf_text observed=2026-08-06T19:24:38.279299Z digest=sha256:01e610b38419c8802f469627680e8cb33f8db0044195d6b2d909d3cd265eef23

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:52.774397Z

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.

source=pdf_text observed=2026-08-06T19:24:38.441452Z digest=sha256:fcee42a35bfa7543dacf22e5d74f0afc3ec846382fae65086c9ada9f67e21a40

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:52.439738Z

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.

source=pdf_text observed=2026-08-06T19:24:38.586796Z digest=sha256:5f0ab7466b9d7e1b1cbddf46078cc83ad4340ccb815a2bf80cb298c1d8aac6fd

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:52.183786Z

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.

source=pdf_text observed=2026-08-06T19:24:38.771401Z digest=sha256:e44b94790ed60ba6ef4d8e70a5666813888dc5f398f22f5534d6c4dd06e78ac5

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:38.929352Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:38.929352Z digest=sha256:46f00ca94eb3216f71182386a9cd0f46bd892c20f4b2ca160f6c3c23fb51ac27

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:51.891946Z

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.

source=pdf_text observed=2026-08-06T19:24:39.110926Z digest=sha256:d2e832bb0baec129174248c586cba2bf18372a2aa2c294f7aa61b2f996bb601b

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:51.568147Z

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.

source=pdf_text observed=2026-08-06T19:24:39.177328Z digest=sha256:b407dc2b10a5ea6ce014f64cb8b986d4db23e7878a91ca1adb738c1e19f1f589

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:51.434931Z

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.

source=pdf_text observed=2026-08-06T19:24:39.292737Z digest=sha256:a268f5dfff70fc41cc663ea57319646ac45c18dbd7bee46adbaa856ee776376e

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:51.250521Z

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.

source=pdf_text observed=2026-08-06T19:24:39.444736Z digest=sha256:fe4d7e1b4490732154cc5368993e06bb4529b34a7add24837810fe57675eb991

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

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:39.555217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:39.555217Z digest=sha256:7215cc4b6abbef8c068315f31a74fc922aa16ee85b195e742167b6e7f8811473

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:51.085391Z

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.

source=pdf_text observed=2026-08-06T19:24:39.664588Z digest=sha256:c7047259ae6b17ba0b05f1093327e1072b0e6d4a921ce2b9104582a091af433d

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:50.900169Z

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.

source=pdf_text observed=2026-08-06T19:24:39.832912Z digest=sha256:07f7fb55ee820c362d677acb54447ea627a6141883e5c3cd4a4eb959b7b98cd9

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:e56d6d4df0b85e4b6b0bbff4a8b3f43dbe86ce71c87ff12cfb10fa2a5411a260

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:40.083040Z digest=sha256:8f2f5f1ac8fa956a35540e5b14592812c885a6da1ab5e739e345a9754e9adfd3

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:ecf2b744466820ebf17d10351055ff791a46e071a2c1df6a817ff6ae96f08710

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:40.378055Z digest=sha256:c094ec8bc0913e010468cc663f9e0dd85d6a91029b11eb033a18e7c30e63305b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:40.526470Z digest=sha256:a55a6e27dfe644f7271ef0f26c73bd64dd033a65a98b6ecb386ba259a25d6beb

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:c025fd7b3638913bf64032d65630f4bd9fbdd077d66c6ec5d06f017b3574884c

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:40.788859Z digest=sha256:27aa537af773381f252137c61e7e4cd51ab64e42cbeda60580f3559bece93da7

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:ef0519d13f49f0ff0890dada090532897729239acdf602107bfa5780fb6db9bb

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:41.075096Z digest=sha256:a50a92ff73c8ebdf264a3f121cc76ec44987b3c0ad5ae7f9d64a4a778b375653

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:41.198746Z digest=sha256:7a4d0e6af558403e5f07d70011df176aacc1ebe716043f8cab4ed4696645a45b

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=sha256:9266cdcdea2abaafd1d3398f29fb864c48871bc86981f1074e28a75b73d9be65

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:41.486221Z digest=sha256:d82938e285896198eb4d4827c8b6ac4cb690bafce9d9f95266d70a8008aadc99

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:41.635595Z digest=sha256:287fb0b061d1a027b0338744d53b16dc63470c4869b443602349f32f29cfcc54

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:41.758807Z digest=sha256:3145e6febfabcc5e9418cd0f60315702597ce10649c6f4cc8381dd1252f84014

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=sha256:2a17817df60b0a8e49f33d410d83a754ea4876109b8b4469748547e7f3fa4b1e

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=sha256:2e63a1d3ac0ff170ec6b5e7707eff979a2f6a4efdd20cf6064549d81ea3a2c7b

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:42.146073Z digest=sha256:0b163d29cacaed86f6dbc8f2734e1f189311b46bf4c0f05eca52ad7a51762e43

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:42.280070Z digest=sha256:d0b2a9ac5d78c8740d9abd60effb10d1104ed76bbb514699d8fd1fa9634bc052

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:42.405170Z digest=sha256:2c1b437e45ea624936891ed184e0c9fa1c64e7aab2519744f6e388146f4f5ed4

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:42.557958Z digest=sha256:bb8356f51363ed80170367b6f36b93ff85933f3530bd52b0a62f14a6fe7e3867

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=sha256:632f296c55281ace52dd6368f5517d98d524db754cc0ff37378ae0341beddc5a

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:42.781787Z digest=sha256:6670a00eddd9bf075a63e0705130111bc4331e7bbf7de1c03adeb351b34d3d5c

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:42.901182Z digest=sha256:09805648ead45a615135a6bf822b8faa8ef7fd7e10d38c5ef74ad0e39d3b6694

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:43.018516Z digest=sha256:e81ea0eec0f305451cbd860da7374c5d35b1018d6a431421fc94faed5ba32904

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:43.139262Z digest=sha256:2f5e5b0b8b7482c767501fc9021f3bad005f062df15e6a1f801896324c64df29

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:43.252288Z digest=sha256:0d2b8c200cbc3fd0c7d8860cbdffb67cfce3b6c6d3af6dc7aef5ba23a507e5c4

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:43.384790Z digest=sha256:386b68288bb3bf2ed0b49a6605d520c5589ae0a07966f9e6795f6c431ca7ced0

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:43.518175Z digest=sha256:50c5366b9e374d22ad0bb72b52a14adf69adce7ef6a993457218d959ca7ce29d

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:43.627006Z digest=sha256:7eaaca3e2c2c8bcfc33d1197ff6f87a03ae70f6a47b9ee101d22869e28f37614

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:43.771515Z digest=sha256:17b728330578f766fb595b3c2461467fb35817c2e6541f2619cdbde6d6ecf520

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:43.907792Z digest=sha256:4628d912d848f166680503af20153c49c52b338e7cb8d21dc6e49f3ba84183d4

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:44.012927Z digest=sha256:82d5353ed6514cfad307e8fab0fc5f56b5a85e85db30307bacf49b40798426fb

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:44.170901Z digest=sha256:0d9ad4c804d283550b9d3efad5fd97b9441a00b43ff876c6b2c78543200e7907

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:44.332321Z digest=sha256:fdfab1afa29d2018535ceda7e0a8d8b86f66a5c486a375eafe0fbbc0fe15b139

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 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T19:24:44.550017Z digest=sha256:9969a53ccb70c1f1f7da90e2e5a5e532bf8b5dfe46255160b999aa47ef12ac0c

Observation e165c1f7-31a8-4ecf-a7e1-9e8d24332746 · outbound

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:47.245943Z

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.

source=pdf_text observed=2026-08-06T19:24:44.624902Z digest=sha256:81bea654a00c87d622c8de4e596668081b5a798099b02d363783a5729988850c

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:47.125016Z

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.

source=pdf_text observed=2026-08-06T19:24:44.695400Z digest=sha256:005401d964e98fa8cc7b8ffe169bf6e6f7cd204641be41139418513c2f0e8abe

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
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:46.920044Z

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.

source=pdf_text observed=2026-08-06T19:24:44.841422Z digest=sha256:3bafeae196b62e054fdea7c0ab5797eec6d1c8c7b0ea234c8e2857c043696739

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
verified fuzzy
raw_fallback, observed 2026-08-06T19:24:46.724005Z

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.

source=pdf_text observed=2026-08-06T19:24:44.955054Z digest=sha256:743bae9d10b2c75ed217c44665116f14f9e15580d56ddba30cb6c89e587c5c16

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
unresolved
no resolver link, observed 2026-08-06T19:24:45.014869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:45.014869Z digest=sha256:0d9942b0fa17ff0a0951d20eea81c62549552bc0b8c317c5e3c86da60291e9fb

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
raw_fallback, observed 2026-08-06T19:24:46.422320Z

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.

source=pdf_text observed=2026-08-06T19:24:45.136993Z digest=sha256:cd0dcd08c70bdb40137cc7595088d4ddc96109474e7a63fb8973d65c69503e91

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
unresolved
no resolver link, observed 2026-08-06T19:24:45.283851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:45.283851Z digest=sha256:ebf120f9ac7fcc6568e6156087b0311a5845c25d57cd54e5929d781cf9dc20c5

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
no resolver link, observed 2026-08-06T19:24:45.399565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:24:45.399565Z digest=sha256:01e7d3a2a59465069bffaacce60e82e3846995809da8217fd7c6b5bcc7ce4fa5

Pith citing papers

No inbound Pith citation observations are available.