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Paper Citation Record · LEDGER

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking

As of 5 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 1 inbound Pith citation observation for arXiv:2511.16618.

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

pith.paper-citation-record.v1
2511.16618 v2

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T21:12:07.539556Z

measured 56 of 56 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T03:40:26.565029Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T17:48:46.259474Z

Reference resolution

55 of 55 outbound references displayed

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External citation measurements

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Outbound references

Observation f9e5af25-d0e8-41fa-b52b-f17266a48fbe · outbound

This paper cites Deep learning for surgical instrument recog- nition and segmentation in robotic-assisted surgeries: a sys- tematic review.Artificial Intelligence Review, 58(1):1, 2024.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Deep learning for surgical instrument recog- nition and segmentation in robotic-assisted surgeries: a sys- tematic review.Artificial Intelligence Review, 58(1):1, 2024

Reference 1

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Observation f8f2e0c1-243e-4836-957d-87b70b40bfb5 · outbound

This paper cites Cholecinstanceseg: A tool instance segmentation dataset for laparoscopic surgery.Scientific Data, 12(1):825, 2025.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Cholecinstanceseg: A tool instance segmentation dataset for laparoscopic surgery.Scientific Data, 12(1):825, 2025

Reference 2

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source=pdf_text observed=2026-08-03T21:12:02.935821Z digest=sha256:76680ca4399aab6d73b06f21ae5ac134956179cacaafc955341da0e77e8b1b5e

Observation 74509df7-e127-46c1-83e0-d7921bde478c · outbound

This paper cites Temporally Constrained Neural Networks (TCNN): A framework for semi-supervised video semantic segmentation.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Temporally Constrained Neural Networks (TCNN): A framework for semi-supervised video semantic segmentation

Reference 3

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Observation 3c0e700d-83ad-4b8c-8c51-7afdc4323fea · outbound

This paper cites A multi-centre polyp detection and segmentation dataset for generalisability assessment.Scientific Data, 10(1):75, 2023.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking A multi-centre polyp detection and segmentation dataset for generalisability assessment.Scientific Data, 10(1):75, 2023

Reference 4

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source=pdf_text observed=2026-08-03T21:12:03.087470Z digest=sha256:a6eb23a8bf3412c75aa9eab80b7a1b17e023760a83b06735751efa3e4f3c9f7c

Observation cd41ac32-1df3-4e41-af6d-4d5d755562fb · outbound

This paper cites 2017 Robotic Instrument Segmentation Challenge.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking 2017 Robotic Instrument Segmentation Challenge

Reference 5

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Observation 1b713460-6f3d-488c-9995-0b5a51ca235a · outbound

This paper cites 2018 Robotic Scene Segmentation Challenge.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking 2018 Robotic Scene Segmentation Challenge

Reference 6

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Observation b2bb9bc7-4309-40e5-a53d-3d716f92ae7e · outbound

This paper cites Matis: Masked-attention transformers for surgical instrument segmentation.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Matis: Masked-attention transformers for surgical instrument segmentation

Reference 7

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Observation 1847944e-7dc9-4d96-9ad3-0b5495a6501b · outbound

This paper cites Pixel-wise recognition for holistic surgical scene understanding.arXiv, 2024.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Pixel-wise recognition for holistic surgical scene understanding.arXiv, 2024

Reference 8

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Observation bb11c067-8efe-44b9-9b80-a49ff863809c · outbound

This paper cites Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Wm-dova maps for accurate polyp highlighting in colonoscopy: Validation vs

Reference 9

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Observation 00208e69-7843-4d05-aa50-a0cd51a7628d · outbound

This paper cites The dresden surgical anatomy dataset for abdominal organ segmentation in surgi- cal data science.Scientific Data, 10(1):1–8, 2023.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking The dresden surgical anatomy dataset for abdominal organ segmentation in surgi- cal data science.Scientific Data, 10(1):1–8, 2023

Reference 10

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Observation 3d95805f-3d08-4d3f-875e-c6bf15af9706 · outbound

This paper cites Xmem: Long- term video object segmentation with an atkinson-shiffrin memory model.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Xmem: Long- term video object segmentation with an atkinson-shiffrin memory model

Reference 11

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Observation fbf5854a-889a-4906-8088-e9c8f274d106 · outbound

This paper cites Putting the object back into video object segmentation.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Putting the object back into video object segmentation

Reference 12

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Observation 727689ab-d726-43c1-ab63-fcf88767dda2 · outbound

This paper cites Mosev2: A more challenging dataset for video object segmentation in complex scenes.arXiv preprint arXiv:2508.05630, 2025.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Mosev2: A more challenging dataset for video object segmentation in complex scenes.arXiv preprint arXiv:2508.05630, 2025

Reference 13

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Observation 40ed8da1-a8d5-44fa-95b3-946c4684ff65 · outbound

This paper cites Sam2long: Enhancing sam 2 for long video segmentation with a training-free memory tree.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Sam2long: Enhancing sam 2 for long video segmentation with a training-free memory tree

Reference 14

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Observation 6e330f1d-be37-451d-b6ad-cfc6be4813df · outbound

This paper cites Patch-based adaptive weighting with segmenta- tion and scale (pawss) for visual tracking in surgical video.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Patch-based adaptive weighting with segmenta- tion and scale (pawss) for visual tracking in surgical video

Reference 15

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source=pdf_text observed=2026-08-03T21:12:04.070011Z digest=sha256:a0baf3d3988e7d1b5191eb9d1a8032e19ce6f0da51c447cd7ecfd70f651602ea

Observation 8f6aa669-3deb-4a98-89a5-dd4d204197ab · outbound

This paper cites Spatio-temporal represen- tation decoupling and enhancement for federated instru- ment segmentation in surgical videos.arXiv preprint arXiv:2506.23759, 2025.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Spatio-temporal represen- tation decoupling and enhancement for federated instru- ment segmentation in surgical videos.arXiv preprint arXiv:2506.23759, 2025

Reference 16

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Observation a37cdca1-9ad8-4c6e-a7a2-77cf2cfabbef · outbound

This paper cites Deep learning for video object segmentation: a review.Artificial Intelligence Review, 56(1):457–531, 2023.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Deep learning for video object segmentation: a review.Artificial Intelligence Review, 56(1):457–531, 2023

Reference 17

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Observation 3f8a0a57-de02-45ff-9afb-fd2ab25754a5 · outbound

This paper cites Image compositing for segmentation of surgical tools without manual annotations.IEEE transactions on medical imaging, 40(5):1450–1460, 2021.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Image compositing for segmentation of surgical tools without manual annotations.IEEE transactions on medical imaging, 40(5):1450–1460, 2021

Reference 18

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Observation 7bd23acf-0db5-4915-b5c8-68e8ae1faf0e · outbound

This paper cites Softseg: Advantages of soft versus binary training for image segmentation.Medical image analysis, 71:102038, 2021.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Softseg: Advantages of soft versus binary training for image segmentation.Medical image analysis, 71:102038, 2021

Reference 19

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Observation 504f777b-7417-498e-a223-b0da66e3f35d · outbound

This paper cites Detection, segmentation, and 3d pose es- timation of surgical tools using convolutional neural net- works and algebraic geometry.Medical Image Analysis, 70: 101994, 2021.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Detection, segmentation, and 3d pose es- timation of surgical tools using convolutional neural net- works and algebraic geometry.Medical Image Analysis, 70: 101994, 2021

Reference 20

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Observation 22b9d0c8-2e4e-4af2-8134-110d42c5bcad · outbound

This paper cites Interac- tive video object segmentation using global and local trans- fer modules.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Interac- tive video object segmentation using global and local trans- fer modules

Reference 21

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Observation 3a05c61a-bc18-4ab0-a56e-ab8844313cbd · outbound

This paper cites Lvos: A benchmark for long-term video object segmentation.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Lvos: A benchmark for long-term video object segmentation

Reference 22

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Observation 5c24f91d-77b2-4514-83ac-2b4c290eefe4 · outbound

This paper cites Lvos: A benchmark for large- scale long-term video object segmentation.IEEE Transac- tions on Pattern Analysis and Machine Intelligence, 2025.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Lvos: A benchmark for large- scale long-term video object segmentation.IEEE Transac- tions on Pattern Analysis and Machine Intelligence, 2025

Reference 23

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Observation 1a820113-e8ee-45a1-b4ab-443be46990d3 · outbound

This paper cites CholecSeg8k: A Semantic Segmentation Dataset for Laparoscopic Cholecystectomy Based on Cholec80.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking CholecSeg8k: A Semantic Segmentation Dataset for Laparoscopic Cholecystectomy Based on Cholec80

Reference 24

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Observation 105801d1-081b-4045-a115-6ccf08f14e4a · outbound

This paper cites Domain and content adaptive convolution based multi- source domain generalization for medical image segmenta- tion.IEEE Transactions on Medical Imaging, 42(1):233– 244, 2022.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Domain and content adaptive convolution based multi- source domain generalization for medical image segmenta- tion.IEEE Transactions on Medical Imaging, 42(1):233– 244, 2022

Reference 25

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Observation f38708f9-c6fe-4e69-aa47-a196dc159168 · outbound

This paper cites Kvasir-seg: A segmented polyp dataset.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Kvasir-seg: A segmented polyp dataset

Reference 26

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Observation 337687a8-e161-417e-8a5c-73da2ad6684d · outbound

This paper cites Exploring intra-and inter-video relation for surgical semantic scene segmentation.IEEE Transactions on Medical Imaging, 41(11):2991–3002, 2022.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Exploring intra-and inter-video relation for surgical semantic scene segmentation.IEEE Transactions on Medical Imaging, 41(11):2991–3002, 2022

Reference 27

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Observation a3074429-dafb-4c91-b399-07b0c6193e1f · outbound

This paper cites Segment any- thing.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Segment any- thing

Reference 28

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Observation b83f2659-3beb-4dd7-bbce-985e76426350 · outbound

This paper cites an unresolved cited work.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Unresolved cited work

Reference 29

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Observation a2143051-8be0-4244-8c12-f02ef0c5484a · outbound

This paper cites Open-vocabulary semantic segmentation with mask-adapted clip.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Open-vocabulary semantic segmentation with mask-adapted clip

Reference 30

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Observation 5bee79b3-b99c-4392-a10b-391692ebe92d · outbound

This paper cites Video object segmentation with adaptive feature bank and uncertain-region refinement.Advances in Neural Informa- tion Processing Systems, 33:3430–3441, 2020.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Video object segmentation with adaptive feature bank and uncertain-region refinement.Advances in Neural Informa- tion Processing Systems, 33:3430–3441, 2020

Reference 31

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Observation 07fe755e-e08b-460a-91d4-ee4a87d7108c · outbound

This paper cites Focal loss for dense object detection.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Focal loss for dense object detection

Reference 32

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Observation 7669acdc-8e09-45a4-b5ab-c2e860b2463a · outbound

This paper cites Surgical sam 2: Real-time segment anything in surgical video by efficient frame pruning.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Surgical sam 2: Real-time segment anything in surgical video by efficient frame pruning

Reference 33

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Observation 9121928a-c066-43f9-8931-f02add9b1640 · outbound

This paper cites ReSurgSAM2: Referring Segment Anything in Surgical Video via Credible Long-term Tracking.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking ReSurgSAM2: Referring Segment Anything in Surgical Video via Credible Long-term Tracking

Reference 34

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source=pdf_text observed=2026-08-03T21:12:05.507774Z digest=sha256:5eaea985f64648467b917fac268f4de4bd8689d41341d31770677e78c013e672

Observation a593f9d3-ea9b-49e0-b295-51b6589df999 · outbound

This paper cites Learning high-quality dynamic memory for video object segmentation.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Learning high-quality dynamic memory for video object segmentation.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

Reference 35

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source=pdf_text observed=2026-08-03T21:12:05.580364Z digest=sha256:08d739fadd627ae5b3d46178776fcc9b86035648f965fbd0f009220c0d708b08

Observation 1d3cf7cc-2a6d-4716-99d6-6d0d7c8131cf · outbound

This paper cites The Endoscapes Dataset for Surgical Scene Segmentation, Object Detection, and Critical View of Safety Assessment: Official Splits and Benchmark.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking The Endoscapes Dataset for Surgical Scene Segmentation, Object Detection, and Critical View of Safety Assessment: Official Splits and Benchmark

Reference 36

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source=pdf_text observed=2026-08-03T21:12:05.663088Z digest=sha256:bd21f4403d9cee83fd2a0b22aafe0ccef42a45e9bd9b21e3b60dcd29489ef344

Observation 59888796-a2f5-4906-8c78-d347431207d3 · outbound

This paper cites Pyramid attention aggregation network for semantic segmentation of surgical instruments.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Pyramid attention aggregation network for semantic segmentation of surgical instruments

Reference 37

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source=pdf_text observed=2026-08-03T21:12:05.743286Z digest=sha256:65aa695604a4dc844eae57baa24fdf7115e6747d9c2ef2ae91210268f9769ea6

Observation c688eb31-da70-471b-9046-ac9eb3d6cd63 · outbound

This paper cites Surginet: Pyramid attention aggregation and class-wise self- distillation for surgical instrument segmentation.Medical Image Analysis, 76:102310, 2022.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Surginet: Pyramid attention aggregation and class-wise self- distillation for surgical instrument segmentation.Medical Image Analysis, 76:102310, 2022

Reference 38

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source=pdf_text observed=2026-08-03T21:12:05.837827Z digest=sha256:1fc61c920eda83b4997815c77ac6a4bb0898e5dc7a8f08993041e69a20efb930

Observation e28a8af9-2099-41f4-b01a-f94ff16eef3d · outbound

This paper cites Video object segmentation using space-time memory networks.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Video object segmentation using space-time memory networks

Reference 39

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source=pdf_text observed=2026-08-03T21:12:05.901934Z digest=sha256:a2c038fff6d858e925e5d775e22b0bd281816c72d42e01425c83bfd9ad783511

Observation eb09073c-733a-4f40-b7f7-e4a0f3ba02b3 · outbound

This paper cites Mvd-net: Semantic segmentation of cataract surgery using multi-view learning.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Mvd-net: Semantic segmentation of cataract surgery using multi-view learning

Reference 40

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source=pdf_text observed=2026-08-03T21:12:05.947673Z digest=sha256:0dc57d55b0088d286a68f037a228b1b851ff10d25d8627e6c8ccfbca26f96b8c

Observation bbc16f62-d5ab-4b3c-ad61-6af75f7cc695 · outbound

This paper cites SAR-RARP50: Segmentation of surgical instrumentation and Action Recognition on Robot-Assisted Radical Prostatectomy Challenge.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking SAR-RARP50: Segmentation of surgical instrumentation and Action Recognition on Robot-Assisted Radical Prostatectomy Challenge

Reference 41

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source=pdf_text observed=2026-08-03T21:12:06.012090Z digest=sha256:056a5602d066d66907fa8ccf916f836ccc4dbf04c3bfc22c357570f3405f4400

Observation 7a6cacfb-6bfd-41b4-8f10-8bd1d86c27b9 · outbound

This paper cites Structure matters: Revisiting boundary refinement in video object seg- mentation.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Structure matters: Revisiting boundary refinement in video object seg- mentation

Reference 42

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source=pdf_text observed=2026-08-03T21:12:06.066615Z digest=sha256:ac60cc189496cd18be081ea13602be68d99e857ff7238034d2f01ae7968a1d0d

Observation 4c8def3f-de2b-40e6-b3c8-12c4c96f3789 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Learning transferable visual models from natural language supervi- sion

Reference 43

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source=pdf_text observed=2026-08-03T21:12:06.147869Z digest=sha256:45471d51ede12776ccbabb2a116190e2fc576bca162e3d450c5b565823a555a5

Observation e2be5e63-9615-4e78-8a23-7d33ef297f87 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking SAM 2: Segment Anything in Images and Videos

Reference 44

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source=pdf_text observed=2026-08-03T21:12:06.211859Z digest=sha256:76f05805d34d6a8c6c510745da2d773a72eab939332f3c0f0b39c704637ae6f6

Observation 956af7f3-636a-46c6-b0fb-9fda72b282eb · outbound

This paper cites Towards real-time multiple surgical tool tracking.Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 9(3): 279–285, 2021.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Towards real-time multiple surgical tool tracking.Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 9(3): 279–285, 2021

Reference 45

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source=pdf_text observed=2026-08-03T21:12:06.282241Z digest=sha256:2d80c6fe085bc88859a727a7eb4b347f7233b6e248a931b10ffcdc869d181992

Observation 1831f7ef-4053-4449-aaaf-a2a76a70d8a2 · outbound

This paper cites FA Davis, 2011.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking FA Davis, 2011

Reference 46

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source=pdf_text observed=2026-08-03T21:12:06.386636Z digest=sha256:3ef3b86e7bced32b939b787c805d7bf7138e6303d5aaf705130991ed6d181b33

Observation 75ab87ee-b5e6-467e-b90e-c27b3232368a · outbound

This paper cites Towards holistic surgical scene understanding.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Towards holistic surgical scene understanding

Reference 47

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source=pdf_text observed=2026-08-03T21:12:06.559018Z digest=sha256:495effdaaf0c190bcd8063b86971c396336e19fe5c8f02ed618bb7385d941ff2

Observation f5052a61-e353-4e7f-b49b-9838ec1ef2a4 · outbound

This paper cites A distractor-aware memory for visual object tracking with sam2.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking A distractor-aware memory for visual object tracking with sam2

Reference 48

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source=pdf_text observed=2026-08-03T21:12:06.667391Z digest=sha256:c69ef2ccc7d791a1e34c71d43368bd378f4a357b7348db05974bea6693c7ab00

Observation 48ec7216-17db-4641-bdc0-e66c91c3d6b6 · outbound

This paper cites Autolaparo: A new dataset of integrated multi-tasks for image-guided surgical automation in laparoscopic hysterectomy.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Autolaparo: A new dataset of integrated multi-tasks for image-guided surgical automation in laparoscopic hysterectomy

Reference 49

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source=pdf_text observed=2026-08-03T21:12:06.753317Z digest=sha256:aa836b41d2baf0f17664b85f5bce6476143bd2ab6462460b8b6f1d6a6d255215

Observation 100ee813-66d0-499d-bf59-2323d51fd4c4 · outbound

This paper cites Scribbleprompt: fast and flexible interactive segmen- tation for any biomedical image.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Scribbleprompt: fast and flexible interactive segmen- tation for any biomedical image

Reference 50

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source=pdf_text observed=2026-08-03T21:12:06.914161Z digest=sha256:d0e88cfb9d77830ea1dea0ddc62617f57c1d125f2a89adfe18a4b09d53656861

Observation 9e220242-c34f-4058-bf0a-10d6acb5ee61 · outbound

This paper cites SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory

Reference 51

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source=pdf_text observed=2026-08-03T21:12:07.077803Z digest=sha256:f1b72d5aa5273ded25f8072d7f02ea8474f9d8e4fa06c269c402a0e9e51827b8

Observation 3a0f717b-0602-4cfd-996a-214190fb733d · outbound

This paper cites Decoupling features in hierar- chical propagation for video object segmentation.Advances in Neural Information Processing Systems, 35:36324–36336,.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Decoupling features in hierar- chical propagation for video object segmentation.Advances in Neural Information Processing Systems, 35:36324–36336,

Reference 52

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source=pdf_text observed=2026-08-03T21:12:07.168173Z digest=sha256:056cd801f9801d0ecc059d3f4bb0f5285d5998c15e0a66ef077f2cf8fd2282cf

Observation a8856b6f-4ad7-4c9e-a0cb-507dae8478ac · outbound

This paper cites Surgicalsam: Efficient class prompt- able surgical instrument segmentation.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Surgicalsam: Efficient class prompt- able surgical instrument segmentation

Reference 53

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source=pdf_text observed=2026-08-03T21:12:07.292236Z digest=sha256:a11ee81c9100711e421fd51d31df89baccb30b2cec5619261d598f44858d9097

Observation bf38a46c-4f22-4ac5-9915-2e6b1a0d8a88 · outbound

This paper cites Sur- gai3.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Sur- gai3

Reference 54

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source=pdf_text observed=2026-08-03T21:12:07.455629Z digest=sha256:57216895bc0c8b910f39060846c70d25df0e2fa9279c86e8ac0d1728a864e179

Observation 9e7a47d7-c2e7-4e64-92fc-b8d33693db6c · outbound

This paper cites Medical SAM 2: Segment medical images as video via Segment Anything Model 2.

SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 55

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source=pdf_text observed=2026-08-03T21:12:07.539556Z digest=sha256:42c49ec11ffffa588903c9d2b01279f414c72928b0f4cf6570a99cae1e53ae5d

Pith citing papers

Observation 902c354f-823e-47d2-9653-11eb33a6a783 · inbound

Training LLMs with Reinforcement Learning over Digital Twin Representations for Reasoning-Intensive Surgical VideoQA cites this paper.

Training LLMs with Reinforcement Learning over Digital Twin Representations for Reasoning-Intensive Surgical VideoQA SurgSLOT: Segment Anything in Surgical Videos via Semantic Long-term Tracking

Reference 15

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verified exact
arxiv_id, observed 2026-07-29T02:25:10.326992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

source=pdf_text observed=2026-06-27T03:40:26.565029Z digest=sha256:4f21a9c6efa51d0a8038ee6d5aa730c2fb61ca77e173e86e4cb9a5da2a0a6769