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Paper Citation Record · LEDGER

A Simple Aerial Detection Baseline of Multimodal Language Models

As of 11 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 3 inbound Pith citation observations for arXiv:2501.09720.

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

pith.paper-citation-record.v1
2501.09720 v3

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:48:22.470604Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:33:45.373661Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T21:31:30.211043Z

Reference resolution

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy10
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e8dab782-5c83-424c-9f6e-a7eaeec88645 · outbound

This paper cites Towards vision- language geo-foundation models: A survey,.

A Simple Aerial Detection Baseline of Multimodal Language Models Towards vision- language geo-foundation models: A survey,

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-10T19:48:22.411251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:48:22.411251Z digest=sha256:c05bf4837715bee0a7aee8c9943a9d046e75a0d92ac8c99d1b26af77f61d4ebb

Observation 0e660552-aa90-4c02-b4c4-7588c57a4432 · outbound

This paper cites Geochat: Grounded large vision-language model for remote sensing,.

A Simple Aerial Detection Baseline of Multimodal Language Models Geochat: Grounded large vision-language model for remote sensing,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:48:22.739165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:48:22.416038Z digest=sha256:e4eb17a025c9650665945d11d5a25945498d4993518842bb02bf07bf0b888549

Observation e3094d1d-3cc3-44c7-a3c8-3e62db9a81aa · outbound

This paper cites Earthgpt: A universal multimodal large language model for multisensor image comprehension in remote sensing domain,.

A Simple Aerial Detection Baseline of Multimodal Language Models Earthgpt: A universal multimodal large language model for multisensor image comprehension in remote sensing domain,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:48:22.727951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:48:22.421715Z digest=sha256:3c9e5c1df87d4129c06ca7981221747b5649a2920d0b2deafd1f8f3295a2ab7c

Observation ba9150a4-093c-4345-9f98-20a6603184d5 · outbound

This paper cites SkySenseGPT: A Fine-Grained Instruction Tuning Dataset and Model for Remote Sensing Vision-Language Understanding.

A Simple Aerial Detection Baseline of Multimodal Language Models SkySenseGPT: A Fine-Grained Instruction Tuning Dataset and Model for Remote Sensing Vision-Language Understanding

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T19:48:22.426502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:48:22.426502Z digest=sha256:4e1666e7ecde6c726d78cbdb11307a76f85d7bfc853650892a480a5fbbcd9717

Observation 82487be8-245e-4498-9623-81452d38e6ca · outbound

This paper cites Florence-2: Advancing a unified representation for a variety of vision tasks,.

A Simple Aerial Detection Baseline of Multimodal Language Models Florence-2: Advancing a unified representation for a variety of vision tasks,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:48:22.716281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:48:22.431613Z digest=sha256:1e24477749a0ee57b7a1092e789e9826fd6ce65145ef4447d654f4d7d7356e4d

Observation 12068af9-82e9-4b93-bb58-b4000c9079fc · outbound

This paper cites Dota: A large-scale dataset for object detection in aerial images,.

A Simple Aerial Detection Baseline of Multimodal Language Models Dota: A large-scale dataset for object detection in aerial images,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:48:22.704212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:48:22.435957Z digest=sha256:772bfabba6fc646d3a13b1b66438e264068c6d8834ee358adae8c1649ca9f9fe

Observation aad09d2e-7cea-405b-9a16-880593a83f21 · outbound

This paper cites RSAR: Restricted State Angle Resolver and Rotated SAR Benchmark.

A Simple Aerial Detection Baseline of Multimodal Language Models RSAR: Restricted State Angle Resolver and Rotated SAR Benchmark

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-10T19:48:22.440780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:48:22.440780Z digest=sha256:e248cb13ef5363d7bddecdedf733a59a7b196ccb8124e9df9fb946350f86b5ed

Observation d12f5c2c-075e-46f1-a857-0347cf2ed681 · outbound

This paper cites Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling.

A Simple Aerial Detection Baseline of Multimodal Language Models Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-10T19:48:22.445114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T19:48:22.445114Z digest=sha256:bbfa50d27b49c706e373a3f6001f6285feb94e47cd8db0f2090efeeecd6118de

Observation 912b76e8-9bf1-4860-8dc8-d43a2503e6b3 · outbound

This paper cites Fair1m: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery,.

A Simple Aerial Detection Baseline of Multimodal Language Models Fair1m: A benchmark dataset for fine-grained object recognition in high-resolution remote sensing imagery,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:48:22.690027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:48:22.449068Z digest=sha256:62f611466faf8095b87cd941e8d50c7e0b8353835e8063051f74d68454c471e2

Observation 668bb933-e76e-4187-84a3-54e80b2b4834 · outbound

This paper cites Object detection in optical remote sensing im- ages: A survey and a new benchmark,.

A Simple Aerial Detection Baseline of Multimodal Language Models Object detection in optical remote sensing im- ages: A survey and a new benchmark,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:48:22.675985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:48:22.452803Z digest=sha256:4f8810c21583a6d05260407820d3e1a7e89e9b87ad03fdbd8f7531dbf1444cce

Observation a9722f9b-9f7d-4578-9f97-59bcb1428621 · outbound

This paper cites Srsdd-v1. 0: A high-resolution sar rotation ship detection dataset,.

A Simple Aerial Detection Baseline of Multimodal Language Models Srsdd-v1. 0: A high-resolution sar rotation ship detection dataset,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:48:22.662897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:48:22.457029Z digest=sha256:28f22675fea5babcba215faaa90b78f2de4f7ccdbae8db3ac5e72456784648d0

Observation a0b6d9e3-4def-41a5-b129-09eaa08e4f95 · outbound

This paper cites Focal loss for dense object detection,.

A Simple Aerial Detection Baseline of Multimodal Language Models Focal loss for dense object detection,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:48:22.650581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:48:22.461653Z digest=sha256:5c9e862bfe596ee5b9abfde4ab4dd0abadbcbfd319d32fe8cd7868929a1bac02

Observation 9733181b-e871-43c7-b6f3-6a8ef9dcfb65 · outbound

This paper cites Fcos: A simple and strong anchor-free object detector,.

A Simple Aerial Detection Baseline of Multimodal Language Models Fcos: A simple and strong anchor-free object detector,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:48:22.638304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:48:22.465716Z digest=sha256:3c322aa0b266005047fbae5fd2937169294da2d7c3139ec31e2ce49e12b02297

Observation 13a71d57-6543-4789-a0ea-3bf2026682b8 · outbound

This paper cites Mmrotate: A rotated object detection benchmark using pytorch,.

A Simple Aerial Detection Baseline of Multimodal Language Models Mmrotate: A rotated object detection benchmark using pytorch,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:48:22.625949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T19:48:22.470604Z digest=sha256:c09d35628be46ff30ef7240b948604fedebf17a4d4347e8441aec63ad2b49383

Pith citing papers

Observation 08f0ac6e-12d3-440e-947e-5fef5a726008 · inbound

PointOBB-v3: Expanding Performance Boundaries of Single Point-Supervised Oriented Object Detection cites this paper.

PointOBB-v3: Expanding Performance Boundaries of Single Point-Supervised Oriented Object Detection A Simple Aerial Detection Baseline of Multimodal Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T15:33:45.373661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:33:45.373661Z digest=sha256:1771fcae3188550fc1d0bd277682da93de59563ba33a9a0801f60c7ba0c9e650

Observation 62c4d2e9-7207-4dd9-8079-1fdeaaca690f · inbound

Point2RBox-v2: Rethinking Point-supervised Oriented Object Detection with Spatial Layout Among Instances cites this paper.

Point2RBox-v2: Rethinking Point-supervised Oriented Object Detection with Spatial Layout Among Instances A Simple Aerial Detection Baseline of Multimodal Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-08T23:03:33.950473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T23:03:33.950473Z digest=sha256:c0cc7bcd29399d2138a5e4cfcc1da5b90a0bbd4120f38176736096f40ba637f5

Observation e950283a-cfd5-419c-886b-2273e1790e86 · inbound

Wholly-WOOD: Wholly Leveraging Diversified-quality Labels for Weakly-supervised Oriented Object Detection cites this paper.

Wholly-WOOD: Wholly Leveraging Diversified-quality Labels for Weakly-supervised Oriented Object Detection A Simple Aerial Detection Baseline of Multimodal Language Models

Reference 65

Resolution
verified exact
local_arxiv, observed 2026-08-07T21:31:30.216575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-07T21:31:29.892617Z digest=sha256:275961978fa33885006e05d90ab075b5e4470b2e51d012b83f10b36d142297d1