Paper Citation Record · LEDGER

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images

As of 10 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2505.23193.

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

pith.paper-citation-record.v1
2505.23193 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:55:11.145284Z

measured 49 of 49 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T04:38:06.673737Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T21:41:15.267892Z

Reference resolution

48 of 48 outbound references displayed

verified exact0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b9347312-a164-460d-b871-c78d61a997d5 · outbound

This paper cites Krmaro: Aerial detection of small-size ground moving objects using kinematic regularization and matrix rank optimization,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Krmaro: Aerial detection of small-size ground moving objects using kinematic regularization and matrix rank optimization,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:18.917267Z

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Observation bc0b5023-9e26-492f-b16c-f29459f11973 · outbound

This paper cites Ufpmp-det: Toward accurate and efficient object detection on drone imagery,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Ufpmp-det: Toward accurate and efficient object detection on drone imagery,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:18.733839Z

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 1b76ea31-c78d-43a9-9007-383599a24728 · outbound

This paper cites Adaptive sparse convolutional networks with global context enhancement for faster object detection on drone images,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Adaptive sparse convolutional networks with global context enhancement for faster object detection on drone images,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:18.555866Z

Source-reported events for the cited work

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Observation 69039480-da1d-40c8-aaec-39a3f5f0b553 · outbound

This paper cites Hierarchical mask prompting and robust integrated regression for oriented object detection,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Hierarchical mask prompting and robust integrated regression for oriented object detection,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:18.383092Z

Source-reported events for the cited work

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Observation e0e49791-c529-4446-8253-b7e70bcb1fac · outbound

This paper cites Scale optimization using evolutionary reinforcement learning for object detection on drone imagery,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Scale optimization using evolutionary reinforcement learning for object detection on drone imagery,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:18.172217Z

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 72999c08-1dca-4283-972c-77a22b6bb055 · outbound

This paper cites Learning temporary block- based bidirectional incongruity-aware correlation filters for efficient uav object tracking,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Learning temporary block- based bidirectional incongruity-aware correlation filters for efficient uav object tracking,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:17.949232Z

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 1b0cc3ab-ebf1-465c-ace0-88e5dfb78a05 · outbound

This paper cites Centric probability- based sample selection for oriented object detection,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Centric probability- based sample selection for oriented object detection,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:17.745444Z

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 1753ebe3-0f88-4489-9ad7-e96b35a75d11 · outbound

This paper cites Multi-task learning for uav aerial object detection in foggy weather condition,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Multi-task learning for uav aerial object detection in foggy weather condition,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:17.511935Z

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 014bec83-31d7-41bc-b914-45c7639985d5 · outbound

This paper cites Coderainnet: Collaborative deraining network for drone-view object detection in rainy weather conditions,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Coderainnet: Collaborative deraining network for drone-view object detection in rainy weather conditions,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:17.324986Z

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 33d09752-291b-4f50-acac-9e51c54d6958 · outbound

This paper cites Visual perception in the human brain: How the brain perceives and understands real-world scenes,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Visual perception in the human brain: How the brain perceives and understands real-world scenes,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:17.081152Z

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 52b0a456-6d39-4a2f-8b7c-ce5613843a65 · outbound

This paper cites Tph-yolov5: Improved yolov5 based on transformer prediction head for object detection on drone- captured scenarios,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Tph-yolov5: Improved yolov5 based on transformer prediction head for object detection on drone- captured scenarios,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:16.878461Z

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 a270c559-08e0-4d56-83d9-73d92efc463a · outbound

This paper cites Tiny object detection via regional cross self-attention network,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Tiny object detection via regional cross self-attention network,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:16.698655Z

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 802473bc-eb38-4de0-b1b6-2024e0460658 · outbound

This paper cites Plug-and-play robust aerial object detection under hazy conditions,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Plug-and-play robust aerial object detection under hazy conditions,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:16.515502Z

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 99468ccc-469a-4e15-96cc-7ee9a33052a7 · outbound

This paper cites Detclip: Dictionary-enriched visual-concept paralleled pre- training for open-world detection,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Detclip: Dictionary-enriched visual-concept paralleled pre- training for open-world detection,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:16.323675Z

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 92c3c7e3-5b42-4081-af55-6e8c60f20e4f · outbound

This paper cites Text-driven traffic anomaly detection with temporal high-frequency modeling in driving videos,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Text-driven traffic anomaly detection with temporal high-frequency modeling in driving videos,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:16.120435Z

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 72acff9d-43cf-4715-bfc4-fd259c0cd0a1 · outbound

This paper cites Learning domain-aware detection head with prompt tuning,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Learning domain-aware detection head with prompt tuning,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:15.949830Z

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 d231bb73-451a-481f-b9bb-957cf1665ea9 · outbound

This paper cites Dst-det: Open- vocabulary object detection via dynamic self-training,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Dst-det: Open- vocabulary object detection via dynamic self-training,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:15.779084Z

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 3a9c0243-cfca-4312-9919-5bb0d8cecdd2 · outbound

This paper cites Llms meet vlms: Boost open vocabulary object detection with fine-grained descriptors,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Llms meet vlms: Boost open vocabulary object detection with fine-grained descriptors,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:15.628221Z

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 e24d651c-31ad-43f9-92f4-0156c06e071b · outbound

This paper cites Generative region- language pretraining for open-ended object detection,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Generative region- language pretraining for open-ended object detection,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:15.480096Z

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 eacce466-56ab-4327-8460-679ad8baad1a · outbound

This paper cites Lenna: Language Enhanced Reasoning Detection Assistant.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Lenna: Language Enhanced Reasoning Detection Assistant

Reference 20

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Source-reported events for the cited work

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Observation a73d116d-7ee6-4db8-8cca-814f8ccc664b · outbound

This paper cites Detgpt: Detect what you need via reasoning,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Detgpt: Detect what you need via reasoning,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:15.353359Z

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 aecf9d06-d979-454e-b93d-4dd11734d884 · outbound

This paper cites Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,

Reference 22

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Observation 267effc5-f670-443f-ad4a-4922103c0220 · outbound

This paper cites Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality,

Reference 23

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Observation 293de081-f3b7-4bc4-8c65-b9872839423e · outbound

This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T12:55:09.428104Z

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Observation d6da1e74-46c8-4539-b99c-6f99939662f7 · outbound

This paper cites Clip the gap: A single domain generalization approach for object detection,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Clip the gap: A single domain generalization approach for object detection,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:15.166141Z

Source-reported events for the cited work

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Observation 8b315387-ee03-472c-a0f3-c518a88808a4 · outbound

This paper cites The unmanned aerial vehicle benchmark: Object detection and tracking,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images The unmanned aerial vehicle benchmark: Object detection and tracking,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:14.984115Z

Source-reported events for the cited work

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Observation e7c6366d-3ef0-49b4-847c-11b24fc3981c · outbound

This paper cites Detection and tracking meet drones challenge,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Detection and tracking meet drones challenge,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:14.840286Z

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 5808562a-eea3-4f41-92b0-3df14dfac718 · outbound

This paper cites Delving into robust object detection from unmanned aerial vehicles: A deep nuisance disentanglement approach,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Delving into robust object detection from unmanned aerial vehicles: A deep nuisance disentanglement approach,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:14.689302Z

Source-reported events for the cited work

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Observation 7b4fb60d-30ec-47c5-9810-89e1c42e575e · outbound

This paper cites Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

Reference 29

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Observation 9d807b80-49ce-4adb-9d9e-773a40a8b8e6 · outbound

This paper cites Microsoft coco: Common objects in context,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Microsoft coco: Common objects in context,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:14.499648Z

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 b70af459-3f50-4733-ba52-2f40a7ec4ee8 · outbound

This paper cites Pytorch: An imperative style, high-performance deep learning library,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Pytorch: An imperative style, high-performance deep learning library,

Reference 31

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Observation 70b54a1c-0ba5-4394-8379-29799225ab4f · outbound

This paper cites Detrs beat yolos on real-time object detection,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Detrs beat yolos on real-time object detection,

Reference 32

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Source-reported events for the cited work

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Observation 95dff9cb-6d01-4eba-b894-5a754b288cae · outbound

This paper cites Dense distinct query for end-to-end object detection,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Dense distinct query for end-to-end object detection,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:14.292066Z

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Observation 3db00d25-5644-4259-b42f-ad9d629d9229 · outbound

This paper cites Mistral 7B.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Mistral 7B

Reference 34

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Observation 1b8bb593-2591-4c3f-8b37-98ee05c81a67 · outbound

This paper cites Mistral-7b-instruct-v0.3,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Mistral-7b-instruct-v0.3,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:14.009062Z

Source-reported events for the cited work

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Observation 43dccc4c-eaa5-44df-9aae-8e665389886b · outbound

This paper cites Mpnet: Masked and permuted pre-training for language understanding,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Mpnet: Masked and permuted pre-training for language understanding,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:13.799164Z

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 f59bf3ec-7efd-4954-8ca9-442426787e94 · outbound

This paper cites Detecting small objects using a channel-aware deconvolutional network,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Detecting small objects using a channel-aware deconvolutional network,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:13.592626Z

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 bfd71539-0b25-4d23-bee8-a80922b8f530 · outbound

This paper cites Guided attention network for object detection and counting on drones,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Guided attention network for object detection and counting on drones,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:13.404167Z

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 474beef0-4f36-4fca-a61d-f187a5859c6f · outbound

This paper cites Improving multiscale object detection with off-centered semantics refinement,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Improving multiscale object detection with off-centered semantics refinement,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:13.211716Z

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 da9b181b-54c5-48e0-94e0-cddfb3a3b32d · outbound

This paper cites Training domain-invariant object detector faster with feature replay and slow learner,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Training domain-invariant object detector faster with feature replay and slow learner,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:12.996147Z

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 1ccfa7be-496a-488b-9ad0-78a116235c28 · outbound

This paper cites Spotnet: Self-attention multi-task network for object detection,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Spotnet: Self-attention multi-task network for object detection,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:12.808554Z

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 a5a1a97b-c56d-4070-a2c5-ced54453046c · outbound

This paper cites Flsl: Feature-level self-supervised learning,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Flsl: Feature-level self-supervised learning,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:12.610142Z

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 f64918a0-8eaf-47ec-a90b-b63271b0505c · outbound

This paper cites Focus-and- detect: A small object detection framework for aerial images,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Focus-and- detect: A small object detection framework for aerial images,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:12.404675Z

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 52ca168f-2318-4fad-a732-fe8632763e7f · outbound

This paper cites Towards resolving the challenge of long-tail distribution in uav images for object detection,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Towards resolving the challenge of long-tail distribution in uav images for object detection,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:12.256397Z

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 723a296c-2937-4847-b2cd-7749491df40b · outbound

This paper cites Fldet: Faster and lighter aerial object detector,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Fldet: Faster and lighter aerial object detector,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:12.101396Z

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 b9693ed7-3986-48ae-946f-0d1b439db18e · outbound

This paper cites Yolc: You only look clusters for tiny object detection in aerial images,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Yolc: You only look clusters for tiny object detection in aerial images,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:11.936170Z

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 697de622-6d4b-465f-b4ca-f187a9625f71 · outbound

This paper cites Ogmn: Occlusion-guided multi-task network for object detection in uav images,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Ogmn: Occlusion-guided multi-task network for object detection in uav images,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:11.656277Z

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 d74d3547-b983-473c-839e-f284bc33d0eb · outbound

This paper cites Pareto refocusing for drone-view object detection,.

Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images Pareto refocusing for drone-view object detection,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:55:11.414872Z

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.

Pith citing papers

Observation f0dcedd0-f893-41c4-8377-4992dee0d7f9 · inbound

Robust Grounding with MLLMs Against Occlusion and Small Objects via Language-Guided Semantic Cues cites this paper.

Robust Grounding with MLLMs Against Occlusion and Small Objects via Language-Guided Semantic Cues Language-guided Learning for Object Detection Tackling Multiple Variations in Aerial Images

Reference 23

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