Paper Citation Record · LEDGER

CRASAR-U-DROIDs: A Large Scale Benchmark Dataset for Building Alignment and Damage Assessment in Georectified sUAS Imagery

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.17673.

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

pith.paper-citation-record.v1
2407.17673 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:49:08.606854Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T01:27:01.819228Z

Reference resolution

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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 7257823f-4123-42ad-a3f1-ba429945ff1f · inbound

Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene cites this paper.

Challenges and Research Directions from the Operational Use of a Machine Learning Damage Assessment System via Small Uncrewed Aerial Systems at Hurricanes Debby and Helene CRASAR-U-DROIDs: A Large Scale Benchmark Dataset for Building Alignment and Damage Assessment in Georectified sUAS Imagery

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T23:49:08.606854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7a65343-df13-4f01-aef0-ea058be9c436 · inbound

Optimizing Start Locations in Ergodic Search for Disaster Response cites this paper.

Optimizing Start Locations in Ergodic Search for Disaster Response CRASAR-U-DROIDs: A Large Scale Benchmark Dataset for Building Alignment and Damage Assessment in Georectified sUAS Imagery

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T20:27:24.895374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e9122a26-b315-479f-8f7a-324d16c27dca · inbound

Survey on Disaster Management Datasets for Remote Sensing Based Emergency Applications cites this paper.

Survey on Disaster Management Datasets for Remote Sensing Based Emergency Applications CRASAR-U-DROIDs: A Large Scale Benchmark Dataset for Building Alignment and Damage Assessment in Georectified sUAS Imagery

Reference 115

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:01:28.437199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6ca7203f-2380-4718-b157-5fb7b16a9585 · inbound

Geometric Flood Depth Estimation: Fusing Transformer-Based Segmentation with Digital Elevation Models cites this paper.

Geometric Flood Depth Estimation: Fusing Transformer-Based Segmentation with Digital Elevation Models CRASAR-U-DROIDs: A Large Scale Benchmark Dataset for Building Alignment and Damage Assessment in Georectified sUAS Imagery

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-12T01:46:14.966612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 0ac492d0-d296-436b-ab76-f65343229a7d · inbound

Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations cites this paper.

Can LLM Agents Respond to Disasters? Benchmarking Heterogeneous Geospatial Reasoning in Emergency Operations CRASAR-U-DROIDs: A Large Scale Benchmark Dataset for Building Alignment and Damage Assessment in Georectified sUAS Imagery

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:27:01.821325Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.