Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-04T17:57:10.303017Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 51 of 51 outbound references and 0 inbound Pith citation observations for arXiv:2509.10408.
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 2026-08-04T17:57:10.303017Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
51 of 51 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 7a347fee-22db-4bd8-9b08-f49160e3a192 · outbound
Multimodal SAM-adapter for Semantic Segmentation Layer Normalization
Reference 1
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Observation 321ea4a8-aa7b-4ba6-a1fc-0a6ff5d5630d · outbound
Multimodal SAM-adapter for Semantic Segmentation Muses: The multi- sensor semantic perception dataset for driving un- der uncertainty
Reference 2
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Observation 8d2299ab-02ac-4355-99ef-1496ca893c8b · outbound
Multimodal SAM-adapter for Semantic Segmentation Cafuser: Condition-aware mul- timodal fusion for robust semantic perception of driving scenes.IEEE Robotics and Automation Letters, 10(4):3134–3141, 2025
Reference 3
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Observation b26ff9ed-ab65-4d90-8eec-76772bcc0518 · outbound
Multimodal SAM-adapter for Semantic Segmentation Collaborative compensative trans- former network for salient object detection.Pattern Recognition, 154:110600, 2024
Reference 4
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Observation 10b016f4-dd05-416a-99f8-cfe7d4c2ed01 · outbound
Multimodal SAM-adapter for Semantic Segmentation SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More
Reference 5
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Observation ef1c3248-cc62-4eb5-ae67-4aa45eceb3e0 · outbound
Multimodal SAM-adapter for Semantic Segmentation Sam- adapter: Adapting segment anything in underper- formed scenes
Reference 6
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Observation 2161ec4c-33da-43f1-80c4-97cd035e5390 · outbound
Multimodal SAM-adapter for Semantic Segmentation Vision transformer adapter for dense predictions
Reference 7
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Observation ffbe9424-33be-486b-b66e-6f15318b9758 · outbound
Multimodal SAM-adapter for Semantic Segmentation Segment any event streams via weighted adaptation of piv- otal tokens
Reference 8
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Observation 8c9c4d75-18c7-40d4-a1c8-5299140f9a16 · outbound
Multimodal SAM-adapter for Semantic Segmentation Schwing, Alexander Kirillov, and Rohit Girdhar
Reference 9
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Observation 9587c8bd-cda9-4193-b365-0ce82db1a7d1 · outbound
Multimodal SAM-adapter for Semantic Segmentation Schwing, and Alexander Kirillov
Reference 10
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Observation 4ff29033-4b1c-49c1-bb6b-7118102e7bfe · outbound
Multimodal SAM-adapter for Semantic Segmentation The cityscapes dataset for semantic urban scene understanding.2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages 3213–3223, 2016
Reference 11
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Observation 6e0a3a0e-2d4f-4290-9ec7-9f7e61785b99 · outbound
Multimodal SAM-adapter for Semantic Segmentation Indoor Semantic Segmentation using depth information
Reference 12
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Observation 14aa2558-9aad-4a5a-b0b4-4da990cd9c00 · outbound
Multimodal SAM-adapter for Semantic Segmentation Imagenet: A large-scale hierarchical image database
Reference 13
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Observation afa845c1-4515-4aef-a7e1-0fb2a2eac19c · outbound
Multimodal SAM-adapter for Semantic Segmentation Efficient Multimodal Semantic Segmentation via Dual-Prompt Learning
Reference 14
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Observation 24009656-2c0f-42c1-ae18-1aaeb7b35a1e · outbound
Multimodal SAM-adapter for Semantic Segmentation An image is worth 16x16 words: Transformers for image recognition at scale
Reference 15
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Observation d4ffa69b-a290-4283-8e8a-afb9eea561ea · outbound
Multimodal SAM-adapter for Semantic Segmentation Mfnet: Towards real-time semantic segmentation for au- tonomous vehicles with multi-spectral scenes
Reference 16
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Observation 5af5a4f5-2dd9-4ee7-9551-fc2f0b2ac079 · outbound
Multimodal SAM-adapter for Semantic Segmentation A survey on instance segmentation: state of the art
Reference 17
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Observation 6e8a6288-2c2d-4e71-9f30-7910b71dabe2 · outbound
Multimodal SAM-adapter for Semantic Segmentation Fusenet: Incorporating depth into semantic segmentation via fusion-based cnn architecture
Reference 18
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Observation 01bcface-043d-41b7-b0fa-1fc4fa44f862 · outbound
Multimodal SAM-adapter for Semantic Segmentation Masked au- toencoders are scalable vision learners
Reference 19
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Observation 5b6c5c2f-fa9d-4b74-8902-b85958b2699d · outbound
Multimodal SAM-adapter for Semantic Segmentation Parameter-efficient transfer learning for NLP
Reference 20
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Observation 7805319b-164c-4085-8c3d-e8adddebd491 · outbound
Multimodal SAM-adapter for Semantic Segmentation Lora: Low-rank adaptation of large language models.ICLR, 1(2):3, 2022
Reference 21
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Observation 8f1a1af5-46f5-4160-aba9-c778f5cca0ee · outbound
Multimodal SAM-adapter for Semantic Segmentation Roadformer+: Delivering rgb-x scene parsing through scale-aware information decou- pling and advanced heterogeneous feature fusion
Reference 22
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Observation c52c5a3c-426e-4b1d-a1b9-785491ca7b29 · outbound
Multimodal SAM-adapter for Semantic Segmentation OneFormer: One Transformer to Rule Universal Image Segmenta- tion
Reference 23
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Observation dbb802b1-44af-4d7a-b472-6ac5f4943948 · outbound
Multimodal SAM-adapter for Semantic Segmentation Gemini- Fusion: Efficient pixel-wise multimodal fusion for vision transformer
Reference 24
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Observation c63e47d3-4580-448f-b9bb-c545acac4d55 · outbound
Multimodal SAM-adapter for Semantic Segmentation Attention enhanced machine instinctive vision with human-inspired saliency detection.Image and Vision Computing, 152:105308, 2024
Reference 25
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Observation 13a48c4b-9b69-475e-b3fb-cf79660adc78 · outbound
Multimodal SAM-adapter for Semantic Segmentation Berg, Wan-Yen Lo, Piotr Dollar, and Ross Gir- shick
Reference 26
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Observation bff41114-5f22-4ec9-bd92-f5d60a20d825 · outbound
Multimodal SAM-adapter for Semantic Segmentation StitchFusion: Weaving Any Visual Modalities to Enhance Multimodal Semantic Segmentation
Reference 27
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Observation 10295fea-fd74-43cf-9b98-a0bfe513a6f1 · outbound
Multimodal SAM-adapter for Semantic Segmentation Roadformer: Duplex transformer for rgb-normal semantic road scene parsing.IEEE Transactions on Intelligent Vehicles, 2024
Reference 28
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Observation 5287e19c-3f4c-42aa-8e6d-c9397b8c784e · outbound
Multimodal SAM-adapter for Semantic Segmentation Multi-interactive feature learning and a full- time multi-modality benchmark for image fusion and segmentation
Reference 29
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Observation 2ffc6ece-79bf-48fd-a552-5ceb07405b8e · outbound
Multimodal SAM-adapter for Semantic Segmentation Segmenting anything in the dark via depth perception.IEEE Transactions on Multime- dia, pages 1–12, 2025
Reference 30
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Observation c5fea37f-8238-43df-aa41-f3988d9643af · outbound
Multimodal SAM-adapter for Semantic Segmentation Swin transformer: Hierarchical vision transformer using shifted windows
Reference 31
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Observation 5992e257-fcb6-49f8-8eb5-100c7c6567e3 · outbound
Multimodal SAM-adapter for Semantic Segmentation A convnet for the 2020s.Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
Reference 32
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Observation c126f55d-efe6-4849-b253-45b5d7c9c018 · outbound
Multimodal SAM-adapter for Semantic Segmentation Decoupled weight decay regularization
Reference 33
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Observation 2d1f97ab-94f3-4564-848e-9ba6dcd619ad · outbound
Multimodal SAM-adapter for Semantic Segmentation Image segmentation using deep learn- ing: A survey.IEEE transactions on pattern anal- ysis and machine intelligence, 44(7):3523–3542, 2021
Reference 34
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Observation f9264136-54ee-45f1-a977-77d6d5f7c882 · outbound
Multimodal SAM-adapter for Semantic Segmentation SAM 2: Segment any- thing in images and videos
Reference 35
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Observation 32733f63-bd37-4c62-b959-6b3275abae41 · outbound
Multimodal SAM-adapter for Semantic Segmentation SU-SAM: A Simple Unified Framework for Adapting Segment Anything Model in Underperformed Scenes
Reference 36
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Observation fc436ae8-5d0b-4d19-bcaf-486117b5da63 · outbound
Multimodal SAM-adapter for Semantic Segmentation Rtfnet: Rgb-thermal fusion network for semantic segmen- tation of urban scenes.IEEE Robotics and Au- tomation Letters, 4(3):2576–2583, 2019
Reference 37
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Observation 230a0912-8149-4038-a4b9-d6d09373d600 · outbound
Multimodal SAM-adapter for Semantic Segmentation Semantic segmentation using vision transformers: A survey
Reference 38
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Observation 2082cd3f-be90-465e-84f5-8346df53bdd3 · outbound
Multimodal SAM-adapter for Semantic Segmentation Adapting Segment Anything Model to Multi-modal Salient Object Detection with Semantic Feature Fusion Guidance
Reference 39
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Observation 834e7e1b-6041-4db0-a64c-9c8b88137669 · outbound
Multimodal SAM-adapter for Semantic Segmentation Multi- modal token fusion for vision transformers
Reference 40
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Observation e11ff524-d44d-4b46-b372-17654bd44545 · outbound
Multimodal SAM-adapter for Semantic Segmentation Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
Reference 41
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Observation 0679f528-db9c-4605-b29c-069c9e0a19ba · outbound
Multimodal SAM-adapter for Semantic Segmentation Segment Anything with Multiple Modalities
Reference 42
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Observation 56391f36-4c52-4d92-a294-5cfd60b7218b · outbound
Multimodal SAM-adapter for Semantic Segmentation Seg- former: Simple and efficient design for semantic segmentation with transformers
Reference 43
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Observation 22e54170-aa7d-43a2-9e10-e363942b4729 · outbound
Multimodal SAM-adapter for Semantic Segmentation Parameter-efficient fine-tuning for pre- trained vision models: A survey.arXiv preprint arXiv:2402.02242, 2024
Reference 44
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Observation e72d7695-c7bd-40df-9a41-d37a777a0e66 · outbound
Multimodal SAM-adapter for Semantic Segmentation Sam-event-adapter: Adapting segment anything model for event-rgb se- mantic segmentation
Reference 45
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Observation e7fa07fc-aeb5-4860-ae5d-b375f634f202 · outbound
Multimodal SAM-adapter for Semantic Segmentation Zeiler, Dilip Krishnan, Geoffrey W
Reference 46
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Observation 9a39c179-554c-4663-8330-f54d22db7bae · outbound
Multimodal SAM-adapter for Semantic Segmentation Cmx: Cross-modal fusion for rgb-x semantic segmen- tation with transformers.IEEE Transactions on Intelligent Transportation Systems, 2023
Reference 47
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Observation 1a73dad3-2c41-4073-afdc-9abc20864828 · outbound
Multimodal SAM-adapter for Semantic Segmentation Delivering arbitrary-modal semantic segmentation
Reference 48
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Observation 749ab53f-542a-47d8-a558-4616d11995ab · outbound
Multimodal SAM-adapter for Semantic Segmentation Deep multimodal fusion for semantic image segmentation: A survey.Image and Vision Computing, 105:104042, 2021
Reference 49
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Observation 4b1635b9-56b0-4d54-be00-68dd0d04c5c0 · outbound
Multimodal SAM-adapter for Semantic Segmentation Deformable{detr}: Deformable transformers for end-to-end object de- tection
Reference 50
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Observation 77138987-85c1-44ac-9295-184ca60b8ac8 · outbound
Multimodal SAM-adapter for Semantic Segmentation Segment everything every- where all at once.Advances in Neural Information Processing Systems, 36, 2024
Reference 51
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No inbound Pith citation observations are available.