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Paper Citation Record · LEDGER

RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2306.11029.

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

pith.paper-citation-record.v1
2306.11029 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:11:02.399591Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:27:30.069800Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation bcdb9114-4984-4397-8da9-1f2b74855933 · inbound

DiffCLIP: Few-shot Language-driven Multimodal Classifier cites this paper.

DiffCLIP: Few-shot Language-driven Multimodal Classifier RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-11T19:11:02.399591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T19:11:02.399591Z digest=sha256:0d33db000bb64232d635120d723524079df483b76a097e295e17e5f037d4af6a

Observation bec077b1-cd19-4ef5-95c9-64a454972f70 · inbound

SenCLIP: Enhancing zero-shot land-use mapping for Sentinel-2 with ground-level prompting cites this paper.

SenCLIP: Enhancing zero-shot land-use mapping for Sentinel-2 with ground-level prompting RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-11T17:49:54.330866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T17:49:54.330866Z digest=sha256:22d928d3597cd5a390eb7cea178ec1cf056e64683a521c37ee9ccde5f554d2f5

Observation f7744bfc-229f-4281-b425-20cc50957d69 · inbound

Measuring and Mitigating Hallucinations in Vision-Language Dataset Generation for Remote Sensing cites this paper.

Measuring and Mitigating Hallucinations in Vision-Language Dataset Generation for Remote Sensing RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T14:52:22.130679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T14:52:22.130679Z digest=sha256:839f46a4c5c06bc12d32d0875cc997d17a22e32a400acbca7a51d706615ff1c7

Observation a658f6d8-06aa-46c4-93df-7fe0cc15f357 · inbound

RoofNet: A Global Multimodal Dataset for Roof Material Identification from Earth Observation cites this paper.

RoofNet: A Global Multimodal Dataset for Roof Material Identification from Earth Observation RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-19T12:57:17.742631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-19T12:56:05.671655Z digest=sha256:f11b924b1bd8bf76606dda2b9d0ff7922ef21072ba5d3f50371e83264e79bd91

Observation be0842d1-200d-430c-98d6-27ec7eaa0aeb · inbound

RoofNet: A Global Multimodal Dataset for Roof Material Identification from Earth Observation cites this paper.

RoofNet: A Global Multimodal Dataset for Roof Material Identification from Earth Observation RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T14:19:08.592303Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:19:08.592303Z digest=sha256:9feedc3cd9cdb96a297e266d83cf313f615976558b52dae6133e961403143a8e

Observation 2f5824d0-bc55-4cae-8a51-35f57df81e69 · inbound

Atmos-Bench: 3D Atmospheric Structures for Climate Insight cites this paper.

Atmos-Bench: 3D Atmospheric Structures for Climate Insight RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T17:24:40.559258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:24:40.559258Z digest=sha256:0ff48e3f1c296b0f12b50bf07b3c1cdf6e81104b84f200fd9dfebb859485bf5f

Observation f0c58fda-2fae-4347-a165-95abf63d6aad · inbound

Open-Vocabulary Object Detection in UAV Imagery: A Review and Future Perspectives cites this paper.

Open-Vocabulary Object Detection in UAV Imagery: A Review and Future Perspectives RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T20:20:31.910863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:20:31.910863Z digest=sha256:d6f978c9a5a9b8773ed6063d23504a7b7d4b4796bd3089f327494206f0e7980c

Observation f48b1336-dba8-4226-9f1f-c3d32030a987 · inbound

Low-Data Supervised Adaptation Outperforms Prompting for Cloud Segmentation Under Domain Shift cites this paper.

Low-Data Supervised Adaptation Outperforms Prompting for Cloud Segmentation Under Domain Shift RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-11T07:41:01.066054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-10T17:02:34.229928Z digest=sha256:046ce6c134d297e4881076487184876c827693db66404ccd12ab885a81f1cb28

Observation 5f497f4a-2069-44ba-a569-08cae307dd9c · inbound

Geo2Sound: A Scalable Geo-Aligned Framework for Soundscape Generation from Satellite Imagery cites this paper.

Geo2Sound: A Scalable Geo-Aligned Framework for Soundscape Generation from Satellite Imagery RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-10T10:04:06.917593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-10T09:52:35.741400Z digest=sha256:bf3c454e3cec711a72cfcb61442a064da78be3da930355c758b57cde21b8d443

Observation 28776cbf-ba18-4059-8d5d-115c878aa9c4 · inbound

ChangeQuery: Advancing Remote Sensing Change Analysis for Natural and Human-Induced Disasters from Visual Detection to Semantic Understanding cites this paper.

ChangeQuery: Advancing Remote Sensing Change Analysis for Natural and Human-Induced Disasters from Visual Detection to Semantic Understanding RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-11T19:06:09.856608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-08T12:41:38.571997Z digest=sha256:37728111bf3c4e99174d41d7b98d389fe95e16a2b8c3de41020a2b4e6211f802

Observation e2e4fb6a-9016-420a-aefa-c136eef4988d · inbound

CropVLM: A Domain-Adapted Vision-Language Model for Open-Set Crop Analysis cites this paper.

CropVLM: A Domain-Adapted Vision-Language Model for Open-Set Crop Analysis RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:46:31.160386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-08T01:36:02.920908Z digest=sha256:816419199c15551e9bf2e51a1ffc35f93f37937177763dfcab3183a7d28ace0c

Observation 01f8a5f8-c8e7-46cf-9c54-7ce69ad90018 · inbound

MSD-Score: Multi-Scale Distributional Scoring for Reference-Free Image Caption Evaluation cites this paper.

MSD-Score: Multi-Scale Distributional Scoring for Reference-Free Image Caption Evaluation RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:46:07.533982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-08T14:10:28.941565Z digest=sha256:e2e5af81c1fb3945c619cb999d9e8a168eb9358339afc07c094aeba2c27d5758

Observation 1482bfd7-8825-4b11-974b-ffb7fb0c2af8 · inbound

SemDINO: Foundation Prior-Guided Cross-Temporal Semantic Alignment Network for Remote Sensing Change Detection cites this paper.

SemDINO: Foundation Prior-Guided Cross-Temporal Semantic Alignment Network for Remote Sensing Change Detection RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:27:30.071165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-27T17:09:07.715768Z digest=sha256:0db2cd88712e63131706c9cbe0e1b2377607249e5fad5a5e598d5e288d077d15

Observation ca61deed-fc21-4abb-9b66-b238e0a854f7 · inbound

Finding Change in Satellite Archives from Text: How to Combine Before-and-After Images Efficiently cites this paper.

Finding Change in Satellite Archives from Text: How to Combine Before-and-After Images Efficiently RemoteCLIP: A Vision Language Foundation Model for Remote Sensing

Reference 10

Resolution
unresolved
no resolver link, observed 2026-07-31T03:27:06.036546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T03:27:06.036546Z digest=sha256:3fe4fe68e1644e978e3b2f107ff67e36f34066f7937cba6c25afcf9372b705e7