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Paper Citation Record · LEDGER

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation

As of 9 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2507.09577.

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

pith.paper-citation-record.v1
2507.09577 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:58:48.140418Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

29 of 29 outbound references displayed

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  • verified fuzzy13
  • unresolved16
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 97ada761-057a-4c95-bd27-180dd95dad2d · outbound

This paper cites 2018 Robotic Scene Segmentation Challenge.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation 2018 Robotic Scene Segmentation Challenge

Reference 1

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Observation 1955fe34-18e9-4a0c-80a1-20ff04ae13db · outbound

This paper cites 2017 Robotic Instrument Segmentation Challenge.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation 2017 Robotic Instrument Segmentation Challenge

Reference 2

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source=pdf_text observed=2026-08-06T17:58:44.964081Z digest=sha256:95ff081568f375c495f75eebdf5be22d7be4aba7f8446c618fed204cf51e8bb1

Observation 08c62655-f02b-48ef-8b8a-6b8f7057c681 · outbound

This paper cites In: 2023 IEEE 20th Interna- tional Symposium on Biomedical Imaging (ISBI).

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation In: 2023 IEEE 20th Interna- tional Symposium on Biomedical Imaging (ISBI)

Reference 3

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:45.027662Z digest=sha256:5b23e09d204fb796ebb3b2c4f4c8f944deaeac4aa7491a5318ec34e76022e2c5

Observation f26f4743-2f83-410c-b3da-ee39ce111fc8 · outbound

This paper cites SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree

Reference 4

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source=pdf_text observed=2026-08-06T17:58:45.140596Z digest=sha256:c17bd524950c1ae7ba7dec038ad0da0fd22f5b3b539ce910bfeeb11187f14f15

Observation 9e081e83-cdf0-4890-b649-11c7df70dd78 · outbound

This paper cites In: International Conference on Medical Im- age Computing and Computer-Assisted Intervention.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation In: International Conference on Medical Im- age Computing and Computer-Assisted Intervention

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:45.231766Z digest=sha256:8591f8c106a4292df67c43088ba5c01a474fa83a22f0f0362d437b0c94f2ed30

Observation e047af66-a8d7-4144-b716-f0ccf597ed2d · outbound

This paper cites In: 2020 Digital Image Computing: Techniques and Applications (DICTA).

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation In: 2020 Digital Image Computing: Techniques and Applications (DICTA)

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:45.305762Z digest=sha256:e25227f23dce0e140f289bf810654dcd71a7a91278c34fb6fe48a6e62af56334

Observation f234110f-732d-4c66-9ca5-7d9faf984322 · outbound

This paper cites In: Proceedings of the IEEE/CVF international conference on computer vision.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation In: Proceedings of the IEEE/CVF international conference on computer vision

Reference 7

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source=pdf_text observed=2026-08-06T17:58:45.378454Z digest=sha256:7e2067d763a5a930cf744a0ef0d1ab1f7fa74ac81c9cea681667015928999ae9

Observation cb935502-4c04-4525-868d-28418d07b2e4 · outbound

This paper cites Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Surgical SAM 2: Real-time Segment Anything in Surgical Video by Efficient Frame Pruning

Reference 8

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source=pdf_text observed=2026-08-06T17:58:45.474699Z digest=sha256:1cd6ec66ce72ca28bcdfad42d885be220f557d8f61a42ebd91e7e512fe90e202

Observation e2bd0480-e89d-4d4c-904c-c19f9eaa4e14 · outbound

This paper cites Nature Communications15(1), 654 (2024).

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Nature Communications15(1), 654 (2024)

Reference 9

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source=pdf_text observed=2026-08-06T17:58:45.552306Z digest=sha256:77e5ec3c7297ac19bb0fd8c976d5b03a350d1a0ead0623a29a3bb81c26965dec

Observation 1f789407-04d9-4b77-85f5-d46b09ea16a5 · outbound

This paper cites Medical Image Analysis76, 102310 (2022).

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Medical Image Analysis76, 102310 (2022)

Reference 10

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:45.640231Z digest=sha256:309448d466070aa154c791b4db9d0b60ec275124cb310b6eae1ba40b20142d14

Observation 2bedbf9e-69c4-46e2-b8e9-45c40afd56f3 · outbound

This paper cites Knowledge-Based Systems p.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Knowledge-Based Systems p

Reference 11

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:45.711897Z digest=sha256:2ec7b61c146ccc2a24024988314032f39e95c10d396e9efd751d98d08801bc37

Observation b0098c50-1228-4f8f-bdd8-6caae83a2bd9 · outbound

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

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation SAM 2: Segment Anything in Images and Videos

Reference 12

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Observation 774fa1a6-7662-40fc-9868-fe7d02cf3efc · outbound

This paper cites Science translational medicine 8(337), 337ra64–337ra64 (2016).

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Science translational medicine 8(337), 337ra64–337ra64 (2016)

Reference 13

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:45.922013Z digest=sha256:e7325f285625747dabaac7a763710e2ae000fbd2fbae81ccf8a7a4b8fb9de60d

Observation d689a970-3837-4a74-a7d7-3f52283dfac9 · outbound

This paper cites Performance and Non-adversarial Robustness of the Segment Anything Model 2 in Surgical Video Segmentation.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Performance and Non-adversarial Robustness of the Segment Anything Model 2 in Surgical Video Segmentation

Reference 14

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source=pdf_text observed=2026-08-06T17:58:45.997317Z digest=sha256:c4450233665d0b2eda405fba54e17bae4bba18f9e34a29821655ea5da1b50066

Observation af240613-f959-487d-a9fd-1eb170f88458 · outbound

This paper cites In: 2018 17th IEEE international conference on machine learning and applications (ICMLA).

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation In: 2018 17th IEEE international conference on machine learning and applications (ICMLA)

Reference 15

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:46.061963Z digest=sha256:547b6f329fed5c95a42fc4aae28210a23f8fa87cfb085f88809a5af862cbdc1d

Observation 5822ee9a-c4cd-47e0-ab5f-4b295884bfb1 · outbound

This paper cites Biomedical Signal Processing and Control 102, 107296 (2025) 10 M.Yin et al.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Biomedical Signal Processing and Control 102, 107296 (2025) 10 M.Yin et al

Reference 16

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:46.200085Z digest=sha256:1ca835d8ee1a04da6a7525e63be9761a8ec358926f9ccb273e0f800a9a8c2ba5

Observation 63e2db14-f807-4d63-a404-1cd9eba238f5 · outbound

This paper cites A Distractor-Aware Memory for Visual Object Tracking with SAM2.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation A Distractor-Aware Memory for Visual Object Tracking with SAM2

Reference 17

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source=pdf_text observed=2026-08-06T17:58:46.309927Z digest=sha256:bbc21288b51db2afe34a45a09d12e8b96dfb35d4ac69f3d6303f6573a76b16ec

Observation 405d7050-aafe-4b7d-9541-c033b68a4748 · outbound

This paper cites Smart Agricultural Technology 8, 100515 (2024).

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Smart Agricultural Technology 8, 100515 (2024)

Reference 18

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:46.476938Z digest=sha256:cda1da020ee5179cf562c861c3d8fb59040742acffdd30fae6e7f0588fd98d55

Observation cd4bfa4b-3cc3-4f63-b25a-dc6df4fad9d6 · outbound

This paper cites Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation

Reference 19

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source=pdf_text observed=2026-08-06T17:58:46.645405Z digest=sha256:c46a316ce7ad12089b55d9bdc4766970bd89364700c0b69317fc3f125e9d31e4

Observation 380dd777-cd90-482b-a680-275aca4c058e · outbound

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

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Biomedical SAM 2: Segment Anything in Biomedical Images and Videos

Reference 20

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Observation 9543d116-36d2-4807-8b26-bcfeb0505aa5 · outbound

This paper cites Track Anything: Segment Anything Meets Videos.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Track Anything: Segment Anything Meets Videos

Reference 21

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source=pdf_text observed=2026-08-06T17:58:46.955280Z digest=sha256:6b112c9d3aa9a58fde9e8656722a7c14915bc54705cc823b81f99fe8ff03c2e8

Observation f20af028-2e70-4b0e-a57b-6e77e7db0b1f · outbound

This paper cites Computers in Biology and Medicine 151, 106216 (2022).

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Computers in Biology and Medicine 151, 106216 (2022)

Reference 22

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:47.149777Z digest=sha256:49bad5dc91e7e8e1afa6a25d0e5282b166fc4c2703ed54f2917e541a03196374

Observation 2c66df2e-f685-4d89-a0d4-e8193feb583e · outbound

This paper cites IEEE Transactions on Medical Robotics and Bionics5(2), 323–334 (2023).

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation IEEE Transactions on Medical Robotics and Bionics5(2), 323–334 (2023)

Reference 23

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:47.282753Z digest=sha256:1bd3572b962b4edd8721977db0691a14a8fd1558606fd4a901ed7f8e826bdb98

Observation 21664948-2d9d-4afd-96a4-8c0ef4d8d56c · outbound

This paper cites SAM 2 in Robotic Surgery: An Empirical Evaluation for Robustness and Generalization in Surgical Video Segmentation.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation SAM 2 in Robotic Surgery: An Empirical Evaluation for Robustness and Generalization in Surgical Video Segmentation

Reference 24

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source=pdf_text observed=2026-08-06T17:58:47.453657Z digest=sha256:1f43ee7e15f70c7fccba5f97c44a45daabac5a9bdefd3e4d385d3900e4826f28

Observation 6cb9dd28-4098-452d-bf14-8f68548b8513 · outbound

This paper cites IEEE transactions on medical imag- ing 42(10), 2817–2831 (2023).

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation IEEE transactions on medical imag- ing 42(10), 2817–2831 (2023)

Reference 25

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:47.583504Z digest=sha256:2e33727d8c655ba28a8af8bfc81fd3df20857669bf099b4047641e62673d317e

Observation 3021a606-e2ae-4c99-9259-42d4bdd26ebf · outbound

This paper cites In: Proceedings of the AAAI Conference on Artificial Intelligence.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation In: Proceedings of the AAAI Conference on Artificial Intelligence

Reference 26

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source=pdf_text observed=2026-08-06T17:58:47.698774Z digest=sha256:2337e14b6f552f8742fca2febb75c024555180121a420669045edab4386dc72d

Observation 7aab0d7b-7341-4859-9057-9ac75e6d70a1 · outbound

This paper cites IEEE Internet of Things Journal 8(10), 7789–7817 (2020).

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation IEEE Internet of Things Journal 8(10), 7789–7817 (2020)

Reference 27

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T17:58:47.860432Z digest=sha256:a18cb4d761554fc3c1db967b2d3eab1032d5f3e17291a2750774556d60caade6

Observation 57bd750a-80b1-4e22-9622-a39b05d28e6b · outbound

This paper cites Personalize Segment Anything Model with One Shot.

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Personalize Segment Anything Model with One Shot

Reference 28

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source=pdf_text observed=2026-08-06T17:58:47.977649Z digest=sha256:6a110b917ea9b0f7f9865601ea162812c2089cc610278e289c7eaab15e29b648

Observation 640eb48c-7d40-456e-98a3-1a8c94ae07d0 · outbound

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

Memory-Augmented SAM2 for Training-Free Surgical Video Segmentation Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Reference 29

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Pith citing papers

No inbound Pith citation observations are available.