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notes/Сгруппированные ссылки.md
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tags:
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- диссер
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---
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# Gate-Fusion механизмы для мультимодальных CVGL-моделей - Claude
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## GeoText-1652
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#Датасеты #CVGL
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1. https://dl.acm.org/doi/10.1007/978-3-031-73247-8_13
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2. https://github.com/MultimodalGeo/GeoText-1652
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3. https://arxiv.org/html/2412.17007v1
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4. https://link.springer.com/chapter/10.1007/978-3-031-73247-8_13
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5. https://huggingface.co/datasets/GeoText/GeoText-1652
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## Where Am I
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#CVGL
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1. https://arxiv.org/pdf/2212.04074
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2. https://arxiv.org/pdf/1703.07815
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3. https://arxiv.org/pdf/2303.15676
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4. https://github.com/yejy53/CVG-Text
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5. https://arxiv.org/abs/2412.17007
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6. https://arxiv.org/html/2412.17007
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7. https://arxiv.org/pdf/2412.17007
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## DEGF-YOLO Quality Aware Gating Unit 2025
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#CVGL #gate #YOLO
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1. https://arxiv.org/pdf/2405.02591
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2. https://www.sciencedirect.com/science/article/abs/pii/S1474034626000881
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3. https://pmc.ncbi.nlm.nih.gov/articles/PMC11962121/
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4. https://www.mdpi.com/2673-2688/6/7/132
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5. https://arxiv.org/html/2506.23252v1
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6. https://pmc.ncbi.nlm.nih.gov/articles/PMC12473487/
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## Learned Gating residual Connections
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#CVGL #gate
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1. https://www.nature.com/articles/s41598-025-11989-6
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2. https://www.mdpi.com/2076-3417/15/20/11259
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3. https://www.sciencedirect.com/science/article/abs/pii/S0893608025003624
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4. https://dl.acm.org/doi/10.1145/3756423.3756555
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5. https://www.preprints.org/manuscript/202409.1917/v1
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6. https://www.emergentmind.com/topics/early-fusion-methods
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7. https://www.emergentmind.com/topics/gated-fusion-mechanism
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## Multimodal Teacher-Studen Distillation
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#CVGL #дистилляция
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[[Knowledge_Distillation]]
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1. https://arxiv.org/pdf/2509.00039
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2. https://www.sciencedirect.com/science/article/abs/pii/S1566253524005207
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3. https://www.ijcai.org/proceedings/2025/0248.pdf
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4. https://arxiv.org/pdf/2506.08772
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5. https://www.sciencedirect.com/science/article/abs/pii/S1051200424005001
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## UC Merced Saturation
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#CVGL #Датасеты
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1. https://paperswithcode.com/sota/scene-classification-on-uc-merced-land-use
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2. https://www.researchgate.net/figure/UC-Merced-dataset-some-example-images-are-displayed-It-contains-21-scene-categories_fig3_271855526
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3. https://arxiv.org/html/2408.16265
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4. https://www.researchgate.net/publication/381622097_Classification_of_University_of_California_UC_Merced_Land-Use_Dataset_Remote_Sensing_Images_Using_Pre-Trained_Deep_Learning_Models
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5. https://arxiv.org/pdf/1703.00121
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6. https://arxiv.org/pdf/1608.05167
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7. https://onlinelibrary.wiley.com/doi/abs/10.1002/9781394234271.ch4
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## CrossText2Loc method architecture
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#CVGL
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1. https://arxiv.org/html/2510.09586v1
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2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12390620/
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3. https://arxiv.org/pdf/2401.00421
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4. https://voxel51.com/blog/iccv-multimodal-ai
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5. https://arxiv.org/pdf/2412.17007
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6. https://arxiv.org/pdf/2412.17007
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7. https://arxiv.org/html/2504.09925v1
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8. https://arxiv.org/html/2504.09925v1
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## CVGL Adaptive Fusion Gating 2024-25
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#CVGL #gate
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1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12299452/
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2. https://pmc.ncbi.nlm.nih.gov/articles/PMC11207219/
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3. https://arxiv.org/pdf/2509.12673
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4. https://link.springer.com/chapter/10.1007/978-981-95-5628-1_26
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5. https://www.mdpi.com/1424-8220/24/12/3719
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6. https://pmc.ncbi.nlm.nih.gov/articles/PMC11548418/
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7. https://arxiv.org/html/2510.22582v1
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8. https://dl.acm.org/doi/10.1145/3728482.3757381
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## Modality Reliability Score Mahalanobis Fusion DL
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#CVGL
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[[InfoScore for residual routing]]
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1. https://www.sciencedirect.com/science/article/abs/pii/S1566253524004263
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2. https://arxiv.org/pdf/2309.05919
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3. https://arxiv.org/pdf/2303.13810
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4. https://arxiv.org/html/2505.05811
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5. https://arxiv.org/html/2309.05919v2
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6. https://arxiv.org/pdf/2504.16524
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## Multimodal Fusion RS Scene Classification (text, img)
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#CVGL #fusion
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1. https://link.springer.com/article/10.1007/s42452-025-06689-9
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2. https://arxiv.org/pdf/2503.13814
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3. https://www.mdpi.com/2673-2688/7/1/5
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4. https://arxiv.org/pdf/2509.23310
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5. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11838890/
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6. https://arxiv.org/pdf/2412.02531
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## Feature Norm Gating MM Fusion NN
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#CVGL #fusion #gate #method/gate-fusion
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1. https://www.preprints.org/manuscript/202409.1917/v1
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2. https://arxiv.org/pdf/2204.00102
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3. https://arxiv.org/pdf/1807.06233
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4. https://arxiv.org/pdf/1702.01992
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5. https://arxiv.org/pdf/1803.09374
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6. https://www.emergentmind.com/topics/gated-fusion-mechanism
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7. https://arxiv.org/pdf/2512.04943
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8. https://www.emergentmind.com/topics/gated-multimodal-units
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## UAV Remote Sensing CLIP Scene Classification benchmark
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#CVGL #VLM
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1. https://arxiv.org/pdf/1703.00121
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2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7070946/
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3. https://arxiv.org/pdf/2510.24321
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4. https://arxiv.org/abs/2510.24321
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5. https://arxiv.org/html/2510.24321v1
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## Text-Image Teacher Student Distillation (single modality Inference or missing modality)
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#CVGL
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[[Knowledge_Distillation]]
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1. https://arxiv.org/pdf/2207.01426
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2. https://arxiv.org/pdf/2505.21549
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3. https://aclanthology.org/2024.emnlp-main.351.pdf
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4. https://arxiv.org/pdf/2603.24208
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5. https://arxiv.org/pdf/2504.07029
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6. https://arxiv.org/pdf/2309.15238
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7. https://arxiv.org/pdf/2507.18192
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8. https://arxiv.org/pdf/1703.00121
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9. https://arxiv.org/pdf/2303.15083
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10. https://openreview.net/forum?id=S5coB5kqSD¬eId=hUnKfBwGvh
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11. https://arxiv.org/pdf/2512.15311
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12. https://openaccess.thecvf.com/content/CVPR2024/html/Huo_C2KD_Bridging_the_Modality_Gap_for_Cross-Modal_Knowledge_Distillation_CVPR_2024_paper.html
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13. https://papers.nips.cc/paper_files/paper/2024/file/e34d908241aef40440e61d2a27715424-Paper-Conference.pdf
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missing modality RS distillation
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14. https://www.arxiv.org/pdf/2511.11460
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15. https://www.ijcai.org/proceedings/2025/
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16. https://www.researchgate.net/publication/395685476_DPMamba_Distillation_Prompt_Mamba_for_Multimodal_Remote_Sensing_Image_Classification_with_Missing_Modalities
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17. https://arxiv.org/html/2511.11460
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18. https://www.ijcai.org/proceedings/2025/0248.pdf
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## Entropy-Based Modality Weighted Adaptive Fusion
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#CVGL #fusion
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1. https://arxiv.org/pdf/2510.01677
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2. https://www.emergentmind.com/topics/adaptive-modality-fusion-modules
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3. https://arxiv.org/pdf/2505.15417
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4. https://www.emergentmind.com/topics/dynamic-modality-weighting
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5. https://www.emergentmind.com/topics/entropy-gated-contrastive-fusion
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6. https://jrnl.kai.edu.ua/index.php/PIU/article/view/21098
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7. https://www.sciencedirect.com/science/article/abs/pii/S1566253525006530
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8. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513103/
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9. https://dl.acm.org/doi/10.1007/978-981-96-0972-7_2
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## Learnable Scalar Residual MM Fusion and Gate
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#CVGL #fusion #gate
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1. https://www.emergentmind.com/topics/gated-multimodal-units
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2. https://arxiv.org/pdf/1907.00135
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3. https://link.springer.com/article/10.1007/s40747-025-02023-3
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4. https://www.emergentmind.com/topics/gated-fusion-module
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5. https://arxiv.org/html/2510.17078v1
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6. https://www.emergentmind.com/topics/adaptive-modality-fusion-modules
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7. https://www.themoonlight.io/en/review/beyond-simple-fusion-adaptive-gated-fusion-for-robust-multimodal-sentiment-analysis
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8. https://arxiv.org/html/2510.01677v1
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## Region Level Cross-Modal Matching
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#CVGL
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1. https://arxiv.org/pdf/2603.08491
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2. https://www.ecva.net/papers/eccv_2024/papers_ECCV/papers/01738.pdf
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3. https://arxiv.org/pdf/2510.20291
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4. https://arxiv.org/html/2603.08491
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5. https://arxiv.org/pdf/2311.12751
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6. https://link.springer.com/chapter/10.1007/978-3-031-73247-8_13
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7. https://link.springer.com/chapter/10.1007/978-981-95-6123-0_53
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## Gated Residual Feature Fusion RS UAV 2024
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#CVGL #gate #residual
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1. https://www.tandfonline.com/doi/full/10.1080/01431161.2024.2429784
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2. https://www.sciencedirect.com/science/article/abs/pii/S0031320325013858
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3. https://arxiv.org/pdf/2304.11422
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4. https://www.tandfonline.com/doi/abs/10.1080/2150704X.2024.2305177
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5. https://www.tandfonline.com/doi/abs/10.1080/01431161.2024.2425875
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## DEGF-YOLO
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#CVGL #YOLO
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1. https://arxiv.org/pdf/2506.23252
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2. https://pmc.ncbi.nlm.nih.gov/articles/PMC12360555/
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3. https://www.mdpi.com/2504-446X/9/11/804
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4. https://www.mdpi.com/2072-4292/17/24/3936
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5. https://arxiv.org/pdf/2510.10765
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6. https://www.mdpi.com/2504-446X/9/7/479
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## Feature Quality, Norm, MM VL Fusion Gate
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#CVGL #gate #VLM
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1. https://arxiv.org/pdf/2601.10710
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2. https://www.sciencedirect.com/science/article/pii/S1566253525011248
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3. https://arxiv.org/html/2504.02477v1
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4. https://arxiv.org/pdf/2501.08443
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5. https://arxiv.org/pdf/2504.09925
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6. https://arxiv.org/pdf/2410.17779
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7. https://arxiv.org/html/2511.02113v1
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8. https://medium.com/@xiaxiami/exploring-feature-fusion-and-matching-in-vision-language-models-3573b6e529b4
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