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Paper Citation Record · LEDGER

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization

As of 8 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2512.03522.

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

pith.paper-citation-record.v1
2512.03522 v4

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T18:49:33.958138Z

measured 30 of 30 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

30 of 30 outbound references displayed

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Outbound references

Observation 17f08c7b-9d19-46b5-9084-51b710b5295c · outbound

This paper cites Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Past, present, and future of simultaneous localization and mapping: Toward the robust-perception age,

Reference 1

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Observation 9b6f9b3a-0494-42fe-a6cc-6f75a485290e · outbound

This paper cites Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Orb-slam2: An open-source slam system for monocular, stereo, and rgb-d cameras,

Reference 2

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Observation 00f24337-4231-47af-b0b4-379be533a1c5 · outbound

This paper cites Oa-slam: Leveraging objects for camera relocalization in visual slam,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Oa-slam: Leveraging objects for camera relocalization in visual slam,

Reference 3

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Observation 229acb6e-b1ce-4332-801f-098589ed6949 · outbound

This paper cites LoFTR: Detector-free local feature matching with transformers,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization LoFTR: Detector-free local feature matching with transformers,

Reference 4

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Observation ad65c6c9-6016-4209-9f4b-6c4b6dd7375b · outbound

This paper cites Not all Views are Created Equal: Analyzing Viewpoint Instabilities in Vision Foundation Models.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Not all Views are Created Equal: Analyzing Viewpoint Instabilities in Vision Foundation Models

Reference 5

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Observation cb530de0-f754-4569-904a-c626db602433 · outbound

This paper cites Object-based loop closure with directional histogram descriptor,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Object-based loop closure with directional histogram descriptor,

Reference 6

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Observation 9f6bb53d-3135-4731-9976-c4e444168c19 · outbound

This paper cites Semantictopoloop: Semantic loop closure with 3d topological graph based on quadric-level object map,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Semantictopoloop: Semantic loop closure with 3d topological graph based on quadric-level object map,

Reference 7

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Observation 4707060c-412f-41b6-9fc6-6cb544c3f203 · outbound

This paper cites An object slam framework for association, mapping, and high-level tasks,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization An object slam framework for association, mapping, and high-level tasks,

Reference 8

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Observation ade98ca0-3730-421b-b986-070a1b1718be · outbound

This paper cites X-view: Graph-based semantic multi-view localization,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization X-view: Graph-based semantic multi-view localization,

Reference 9

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Observation f2fab035-d9dc-4432-a7f7-3f8be2bba2f1 · outbound

This paper cites Semantic histogram based graph matching for real-time multi-robot global localization in large scale environment,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Semantic histogram based graph matching for real-time multi-robot global localization in large scale environment,

Reference 10

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Observation 4d9a3d27-163b-483a-ac1d-d663cd7f8ba2 · outbound

This paper cites Goreloc: Graph-based object-level relocalization for visual slam,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Goreloc: Graph-based object-level relocalization for visual slam,

Reference 11

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Observation adb9271b-d1c9-4977-aab2-393fa9a495c2 · outbound

This paper cites Clip-loc: Multi-modal landmark association for global localization in object-based maps,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Clip-loc: Multi-modal landmark association for global localization in object-based maps,

Reference 12

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Observation 849873e5-6c49-4b91-9940-0a500a5c3c82 · outbound

This paper cites Clip-clique: Graph-based correspon- dence matching augmented by vision language models for object-based global localization,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Clip-clique: Graph-based correspon- dence matching augmented by vision language models for object-based global localization,

Reference 13

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Observation bcab2792-a065-410e-98b2-53e29c48bd2f · outbound

This paper cites Slam++: Simultaneous localisation and mapping at the level of objects,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Slam++: Simultaneous localisation and mapping at the level of objects,

Reference 14

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source=pdf_text observed=2026-08-03T18:49:32.321137Z digest=sha256:694590c2ea6283af96213a57f25ac75ee8b463813bdb815ee69cbcf64e973324

Observation 0bc44936-1b38-4386-902e-16578be9885a · outbound

This paper cites Cubeslam: Monocular 3-d object slam,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Cubeslam: Monocular 3-d object slam,

Reference 15

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source=pdf_text observed=2026-08-03T18:49:32.396133Z digest=sha256:a14dba9da3620cb976f98b6ca8ff219857556625e87216341fb29ee9f9e25dc3

Observation bacb99b6-1677-4677-8575-3486fa9e52ac · outbound

This paper cites Monocular object and plane slam in structured envi- ronments,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Monocular object and plane slam in structured envi- ronments,

Reference 16

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source=pdf_text observed=2026-08-03T18:49:32.515736Z digest=sha256:7f1c404fcc2723342ad9bed1590ffece9ee731f7bbc60b87343168fabfd230e2

Observation 1b076ea7-d041-4147-995a-f140a9341f1e · outbound

This paper cites Quadricslam: Dual quadrics from object detections as landmarks in object-oriented slam,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Quadricslam: Dual quadrics from object detections as landmarks in object-oriented slam,

Reference 17

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Observation 55287452-8d05-4563-a287-449953017104 · outbound

This paper cites Eao-slam: Monocular semi-dense object slam based on ensemble data association,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Eao-slam: Monocular semi-dense object slam based on ensemble data association,

Reference 18

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Observation 0c16699a-7f21-471c-8949-759c27d9dd28 · outbound

This paper cites Qiso-slam: Object-oriented slam using dual quadrics as landmarks based on instance segmentation,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Qiso-slam: Object-oriented slam using dual quadrics as landmarks based on instance segmentation,

Reference 19

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Observation 75f34b57-4da6-4031-b87a-b40131a3c60f · outbound

This paper cites V oom: Robust visual object odometry and mapping using hierarchical landmarks,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization V oom: Robust visual object odometry and mapping using hierarchical landmarks,

Reference 20

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Observation bded1955-ec46-41fa-a41b-73da43ba861c · outbound

This paper cites Robust visual place recognition with graph kernels,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Robust visual place recognition with graph kernels,

Reference 21

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Observation 42368e21-4bc9-4389-ab72-01f47c4802df · outbound

This paper cites A Normalized Gaussian Wasserstein Distance for Tiny Object Detection.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization A Normalized Gaussian Wasserstein Distance for Tiny Object Detection

Reference 22

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Observation c13927e2-90ba-42fa-8235-1e86abc45973 · outbound

This paper cites A benchmark for the evaluation of rgb-d slam systems,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization A benchmark for the evaluation of rgb-d slam systems,

Reference 23

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Observation 40fa18bc-f16e-4a72-8b4f-8ccd40f858b6 · outbound

This paper cites Characterizing visual localization and mapping datasets,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Characterizing visual localization and mapping datasets,

Reference 24

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Observation a637f123-edb2-4528-b089-b455d6a35e7c · outbound

This paper cites Ultralytics yolov8,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Ultralytics yolov8,

Reference 25

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Observation d8399549-d3c1-47ec-825c-2c3e020a9d77 · outbound

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

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Microsoft coco: Common objects in context,

Reference 26

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Observation c9520224-5d91-45ca-8cab-67a5aa7c757d · outbound

This paper cites Lvis: A dataset for large vocabulary instance segmentation,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Lvis: A dataset for large vocabulary instance segmentation,

Reference 27

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Observation be663acb-b986-4f4d-9251-0109626d10d1 · outbound

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

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 28

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Observation 619e85f3-57c2-4c8b-9d80-565b8cfb5c3a · outbound

This paper cites Open-vocabulary sam: Segment and recognize twenty-thousand classes interactively,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Open-vocabulary sam: Segment and recognize twenty-thousand classes interactively,

Reference 29

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Observation a0afae5e-993a-46d2-88e4-b1c23cf1bfa2 · outbound

This paper cites Tokenize anything via prompting,.

MSG-Loc: Multi-Label Likelihood-based Semantic Graph Matching for Object-Level Global Localization Tokenize anything via prompting,

Reference 30

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