Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T13:22:13.267737Z
Paper Citation Record · LEDGER
As of 11 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 4 inbound Pith citation observations for arXiv:2512.24561.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T13:22:13.267737Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
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A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T23:18:25.494068Z
70 of 70 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 1407b649-e64b-40d9-8988-2a1232010af3 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Qwen-vl: A versatile vision-language model for un- derstanding, localization, text reading, and beyond, 2023
Reference 1
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Unavailable: canonical work link unavailable.
Observation bb100858-17d2-40bd-8059-6adb8e7479c1 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Uniter: Universal image-text representation learning
Reference 2
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Observation 1ee842d9-9938-44b3-8875-9f63b5e079d2 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Cops-ref: A new dataset and task on composi- tional referring expression comprehension
Reference 3
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Observation 4f01e7a2-af88-41f5-81fe-71e9cd1c16a8 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Unit3d: A unified transformer for 3d dense captioning and visual grounding
Reference 4
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Observation 7e262af5-d149-42b1-92a0-23ca710517fe · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Advancing visual grounding with scene knowl- edge: Benchmark and method
Reference 5
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Observation c45022d3-1c20-4f82-9414-230b44a1a92e · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Transvg: End-to-end visual ground- ing with transformers
Reference 6
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Observation 309e8538-795e-47ea-a566-b1d1f7993058 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Bert: Pre-training of deep bidirectional trans- formers for language understanding
Reference 7
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Observation 49a85298-a2b6-4d7a-99f7-a5e211ef41ab · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios D3t: Distinctive dual-domain teacher zigzagging across rgb- thermal gap for domain-adaptive object detection
Reference 8
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Observation 0af4a103-7809-46c1-9dc7-8b4af125131b · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Reference 9
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Observation bdd8dfea-ecb2-4268-8898-5ba49f84d6a4 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Large-scale adversarial training for vision- and-language representation learning.NeurIPS, 33:6616– 6628, 2020
Reference 10
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Observation fec1444d-f117-40fc-b782-b787c38ec76d · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Room-and-object aware knowledge reasoning for remote embodied referring expression
Reference 11
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Observation b0f35396-7226-4bdd-bae3-aeb7dbf0eff2 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios The iapr tc-12 benchmark: A new eval- uation resource for visual information systems
Reference 12
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Observation cc6a1b54-228b-4f93-a57e-b5970a8e6004 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Deep residual learning for image recognition
Reference 13
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Observation a4bddb92-2038-49c6-b0a5-b5ccd64e6ac0 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022
Reference 14
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Observation 7db8483a-6139-4464-94e5-d1b3dd79514a · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Ei 2 det: Edge-guided illumination-aware interactive learning for visible-infrared object detection.TCSVT, 2025
Reference 15
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Observation d41f7c38-41e1-478f-9bea-ac274ef82114 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Beyond one-to-one: Re- thinking the referring image segmentation
Reference 16
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Observation 2e61ec8c-4d4e-468c-8cd5-b5de161dd86f · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Referitgame: Referring to objects in pho- tographs of natural scenes
Reference 17
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Observation 4f621396-d7f2-4d0c-857b-b445360ee236 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios mplug: Effective and efficient vision-language learning by cross-modal skip-connections
Reference 18
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Observation 567a5f88-d237-42e1-a838-7af3bed1a193 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Rgb-t semantic segmentation with location, activation, and sharpening.TCSVT, 33(3):1223–1235, 2022
Reference 19
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Observation da724d24-8ca5-4d5b-af96-fad6aa94cef9 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Microsoft coco: Common objects in context
Reference 20
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Observation 0f038089-9ff8-44a7-93b0-98721e65a4cd · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Gres: Gen- eralized referring expression segmentation
Reference 21
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Observation 91129e57-d05f-4298-9e37-598bc2d60a90 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Refer-it-in-rgbd: A bottom-up ap- proach for 3d visual grounding in rgbd images
Reference 22
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Observation 805d9a1c-b4cc-4c9d-a0bb-5c60bdf049ce · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Visual instruction tuning.NeurIPS, 36:34892–34916, 2023
Reference 23
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Observation ef9c6c3c-4cfd-49bc-acf8-1c69cd8fed7d · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection
Reference 24
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Observation 2edb6309-ac5c-4d98-8c91-1603d2351ad4 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Cross3dvg: Cross-dataset 3d visual grounding on different rgb-d scans
Reference 25
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Observation 959bbfc9-1512-42d2-9499-e1385b44ed0f · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Mod- eling context between objects for referring expression under- standing
Reference 26
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Observation a25a0121-4167-462c-b42c-b046a3549897 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Flickr30k entities: Collecting region-to-phrase corre- spondences for richer image-to-sentence models
Reference 27
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Observation 031b6ad1-fc67-4964-bacc-bea7a1ee9cf7 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Learn- ing transferable visual models from natural language super- vision
Reference 28
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Observation eb5116eb-af16-4e42-937b-d9932eec4ee4 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Dynamic mdetr: A dynamic multimodal transformer decoder for visual grounding.IEEE Transactions on Pattern Analysis and Machine Intelligence, 46(2):1181–1198, 2023
Reference 29
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Observation 869f0c3c-cdca-453f-9644-63d37f1169f5 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Attention is all you need.NeurIPS, 30, 2017
Reference 30
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Observation e8659ac2-f1dd-4ebf-a7c2-4e7b6a7a8794 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Ofa: Unifying architectures, tasks, and modalities through a simple sequence-to-sequence learning framework
Reference 31
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Observation aa35b809-d83d-43ca-a718-0ed735563433 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Image as a foreign language: Beit pretraining for vision and vision- language tasks
Reference 32
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Observation a43b6454-1678-48d8-b9d4-e4e4a696c5cb · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Clip-vg: Self-paced curriculum adapting of clip for visual grounding.TMM, 26:4334–4347,
Reference 33
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Observation ceb9017f-6716-48c9-bdeb-10dcb348b875 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Towards visual grounding: A survey
Reference 34
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Observation 9cbcbc35-a951-4641-b7ab-2c7b948aa364 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Hivg: Hierarchical multimodal fine- grained modulation for visual grounding
Reference 35
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Observation 1a5d5a3c-e6fa-4de4-81e3-4fa0ff4433bf · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Oneref: Unified one-tower expression grounding and segmentation with mask referring modeling
Reference 36
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Observation 894c0ae2-e442-40e5-bf4b-3d0ed8e4c595 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Described object detection: Liberating ob- ject detection with flexible expressions.NeurIPS, 36:79095– 79107, 2023
Reference 37
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Observation 12bd4718-e362-4862-b9b4-8c237dc051b9 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Mc-bench: A bench- mark for multi-context visual grounding in the era of mllms
Reference 38
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Observation a5317b8b-90d2-4892-949b-1340eea2232c · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Improving one-stage visual grounding by recursive sub-query construction
Reference 39
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Observation 0e63b9eb-7172-4b40-80d8-6b4f06347bfc · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Unitab: Unifying text and box outputs for grounded vision- language modeling
Reference 40
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Observation 1cb76a83-6046-4b61-a18b-eb439b5d1d27 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Vi- sual grounding with multi-modal conditional adaptation
Reference 41
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Observation 2c7be307-2a62-4605-a87a-d3324ed593d0 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Shifting more attention to visual backbone: Query-modulated refinement networks for end-to-end visual grounding
Reference 42
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Observation 183bb79e-93ef-4873-9853-bf4a36d29ada · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Modeling context in referring expres- sions
Reference 43
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Observation ac0055fa-fcb5-4ab3-915c-2aedee084a49 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios C 2former: Calibrated and complementary transformer for rgb-infrared object de- tection.TGRS, 62:1–12, 2024
Reference 44
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Observation f90310fa-9edf-45f6-8e1c-d43a87e061ba · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Trans- lation, scale and rotation: Cross-modal alignment meets rgb-infrared vehicle detection
Reference 45
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Observation 019f9ec1-96dc-4537-91fa-742ced008088 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Improving rgb-infrared object detection with cascade alignment-guided transformer.Information Fusion, 105:102246, 2024
Reference 46
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Observation 7933f4bf-8206-414e-9d2f-76a2fef01119 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Unirgb-ir: A unified frame- work for visible-infrared semantic tasks via adapter tuning
Reference 47
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Observation 5dc45d55-c7c5-452b-95b5-0ee8441e4abf · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Multispectral fusion for object detection with cyclic fuse-and-refine blocks
Reference 48
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Observation ee7be17c-9ea4-40a8-88c4-0ed0c8c9468e · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Abmdrnet: Adaptive-weighted bi-directional modality difference reduc- tion network for rgb-t semantic segmentation
Reference 49
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Observation 81ffd4b3-5722-4dc6-a3e6-57e85c43e6d4 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Removal then selection: A coarse-to-fine fusion perspective for rgb-infrared object detection.arXiv e-prints, pages arXiv–2401, 2024
Reference 50
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Observation e354113d-a2f4-4527-8820-a55cb53aab71 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios be- hind the truck
Reference 51
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Observation c1623795-31fe-4d43-b53b-225543485a47 · outbound
RGBT-GroundBench: Visual Grounding Beyond RGB in Complex Real-World Scenarios Unresolved cited work
Reference 53
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Observation edfd31a8-d30e-41d2-b6fc-ff48332fbe89 · outbound
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Reference 54
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Observation c2fb9113-c4ab-4fc6-b8f0-796a559df62c · outbound
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Reference 56
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Observation f96a5e63-4701-43df-b6b6-4fd64bd69e3e · outbound
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Reference 57
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Observation f32a7b6f-b590-4184-867f-954a7f47a86c · outbound
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Reference 58
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Observation 0a7c6681-4264-499d-bf3a-75c1b9f15d4d · outbound
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Reference 61
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Observation 38d3df62-5325-4b4b-a79a-586a1f9b87c8 · outbound
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Reference 64
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Reference 65
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Observation 400a225d-e54d-46b3-838d-7cec33fbae08 · outbound
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Reference 66
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Observation 7beeb4e8-13a5-4879-bb26-19bbae99ffcc · outbound
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Reference 67
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Reference 68
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Observation 4919d6e8-abb9-4622-94ab-c7e6a8db808f · outbound
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Reference 69
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Reference 70
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Observation 9c91cae0-6661-4ba5-a87e-7c2c9c824b6b · outbound
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Reference 71
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Observation f67d87e2-450c-474c-ae53-981ab63e3435 · outbound
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Reference 72
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Reference 73
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Reference 74
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Reference 75
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Reference 2023
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Observation 88a6f25c-1961-4add-97de-c2a9524ed012 · inbound
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Reference 80
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Reference 80
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