Paper Citation Record · LEDGER

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model

As of 15 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 1 inbound Pith citation observation for arXiv:2605.18013.

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

pith.paper-citation-record.v1
2605.18013 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-20T12:15:10.404261Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T11:43:11.216668Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

verified exact3
verified fuzzy35
unresolved1
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ede6d64d-0d7b-42e2-81d4-23820965aaa9 · outbound

This paper cites an unresolved cited work.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-05-20T12:18:17.475014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 50681918-f5a8-436e-a915-f941c704f0ea · outbound

This paper cites Rethink- ing space-time networks with improved memory coverage for efficient video object segmentation.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Rethink- ing space-time networks with improved memory coverage for efficient video object segmentation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.458102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 352d936e-de60-4109-8e38-778afdb835f8 · outbound

This paper cites Modular interactive video object segmentation: Interaction-to-mask, propagation and difference-aware fusion.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Modular interactive video object segmentation: Interaction-to-mask, propagation and difference-aware fusion

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.455909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 795d21e1-016f-4330-ae73-ca676cc1ff76 · outbound

This paper cites Tracking anything with decoupled video segmentation.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Tracking anything with decoupled video segmentation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.471280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 62202ecf-59d7-4c80-8511-09f088628af5 · outbound

This paper cites Price, Joon-Young Lee, and Alexander G.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Price, Joon-Young Lee, and Alexander G

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.451818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0f1cbe8b-bec4-4d4c-a8f8-57ee97bddd6d · outbound

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

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Putting the object back into video object segmentation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.473267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1618f641-2c5e-45a4-ad6a-bd7078c05841 · outbound

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

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Interac- tive video object segmentation using global and local trans- fer modules

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.476949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fe3bba5a-4845-46fb-ac3d-072cd2a0f799 · outbound

This paper cites Unsupervised video object segmentation using motion saliency-guided spatio-temporal propagation.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Unsupervised video object segmentation using motion saliency-guided spatio-temporal propagation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.469456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 68d0dce5-51f4-4612-8f50-579e30154098 · outbound

This paper cites Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Berg, Wan-Yen Lo, Piotr Dollar, and Ross Girshick

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.486622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e9ef6b82-3706-431c-955b-e5834e52d406 · outbound

This paper cites Recurrent dynamic embedding for video ob- ject segmentation.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Recurrent dynamic embedding for video ob- ject segmentation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.497123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8c0b26ed-b29c-4d12-93e2-80419c37130d · outbound

This paper cites Unsupervised video object segmenta- tion with motion-based bilateral networks.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Unsupervised video object segmenta- tion with motion-based bilateral networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.462639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 329f18a4-35ca-47ca-afd7-5051f8e754e1 · outbound

This paper cites Decoupled weight de- cay regularization.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Decoupled weight de- cay regularization

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.488746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ad5b204a-8c15-408c-ad20-f3cd7028c7b6 · outbound

This paper cites See more, know more: Unsuper- vised video object segmentation with co-attention siamese networks.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model See more, know more: Unsuper- vised video object segmentation with co-attention siamese networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.499050Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 077016a3-aedb-4342-a052-ca21548e4caf · outbound

This paper cites Segment anything in medical images.Nature Communications, 15(1):654.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Segment anything in medical images.Nature Communications, 15(1):654

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.505212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2e7c519b-be98-4fcb-b0b3-5faab76f2433 · outbound

This paper cites Segment anything model for medical image analysis: an experimental study.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Segment anything model for medical image analysis: an experimental study

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.445804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8ce7ee30-72bd-4ba6-a8e7-0ff621918c07 · outbound

This paper cites Sam- i2v: Upgrading sam to support promptable video segmen- tation with less than 0.2% training cost.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Sam- i2v: Upgrading sam to support promptable video segmen- tation with less than 0.2% training cost

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.464895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation d83ea97a-df12-4503-887c-30ff0c9c468a · outbound

This paper cites Memory aggrega- tion networks for efficient interactive video object segmen- tation.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Memory aggrega- tion networks for efficient interactive video object segmen- tation

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.443764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7cedb340-7504-4412-9d92-408c92007430 · outbound

This paper cites Fast user-guided video object segmentation by interaction-and-propagation networks.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Fast user-guided video object segmentation by interaction-and-propagation networks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.460233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 46e688f3-833e-42a4-a3ca-97557495f664 · outbound

This paper cites The 2017 davis challenge on video object segmentation.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model The 2017 davis challenge on video object segmentation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.467418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8226b73c-4fb3-42d7-a32a-a491458ebb2c · outbound

This paper cites Sam 2: Segment anything in images and videos.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Sam 2: Segment anything in images and videos

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.448102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 928023fa-611f-4c89-b0b0-74890fac7116 · outbound

This paper cites Hiera: A hi- erarchical vision transformer without the bells-and-whistles.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Hiera: A hi- erarchical vision transformer without the bells-and-whistles

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.453872Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 47c6fda8-7484-4c54-acb1-f978c9563fa0 · outbound

This paper cites Ef- ficient video object segmentation via modulated cross- attention memory.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Ef- ficient video object segmentation via modulated cross- attention memory

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.449970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3451defe-77a4-430f-bf0c-c241cd7446b6 · outbound

This paper cites Tinysam: Pushing the envelope for efficient segment any- thing model.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Tinysam: Pushing the envelope for efficient segment any- thing model

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.479309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b1fef65c-c9ea-48c6-a2c8-21188b42fc40 · outbound

This paper cites Dycoke: Dynamic compression of tokens for fast video large language models.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Dycoke: Dynamic compression of tokens for fast video large language models

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:23:28.388652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3d284b79-e87c-40b0-be83-d7fca67ab9b5 · outbound

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

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model A distractor-aware memory for visual object tracking with sam2

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.507450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 40b685f7-d086-4077-a182-b0db35cfa00b · outbound

This paper cites Repvit: Revisiting mobile cnn from vit perspective.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Repvit: Revisiting mobile cnn from vit perspective

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.509600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3dd1dabd-a748-42fb-a5cd-3d37923b1d37 · outbound

This paper cites Learning unsupervised video object segmentation through visual attention.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Learning unsupervised video object segmentation through visual attention

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:23:28.392185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation adc57abc-47e9-49e3-87e6-2dc328cf1d05 · outbound

This paper cites Medical sam adapter: Adapting segment anything model for medical im- age segmentation.Medical image analysis, 102:103547.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Medical sam adapter: Adapting segment anything model for medical im- age segmentation.Medical image analysis, 102:103547

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.503217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 76b3b19a-d30d-4c13-bafb-cfb151291dff · outbound

This paper cites Efficientsam: Leveraged masked image pretraining for efficient segment anything.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Efficientsam: Leveraged masked image pretraining for efficient segment anything

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.493024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1e741841-1965-4a4d-8457-67687d51bcfd · outbound

This paper cites Efficient track anything.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Efficient track anything

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.494997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7957a08d-31b0-464b-85c1-9360065a7996 · outbound

This paper cites Youtube-vos: A large-scale video object segmentation benchmark.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Youtube-vos: A large-scale video object segmentation benchmark

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.500972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 9883c472-6caf-4b25-ae86-81f3f5cffdfc · outbound

This paper cites Track anything: Segment anything meets videos.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Track anything: Segment anything meets videos

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:23:28.390291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 77d1178f-3c85-4ba4-a6d1-ec85859eff2c · outbound

This paper cites Scalable video object seg- mentation with identification mechanism.IEEE Transac- tions on Pattern Analysis and Machine Intelligence, 46(9): 6247–6262.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Scalable video object seg- mentation with identification mechanism.IEEE Transac- tions on Pattern Analysis and Machine Intelligence, 46(9): 6247–6262

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.490920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 569c5346-ec4d-4ec0-a48b-9b8fe15953fa · outbound

This paper cites Faster Segment Anything: Towards Lightweight SAM for Mobile Applications.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Faster Segment Anything: Towards Lightweight SAM for Mobile Applications

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-05-20T12:18:16.653195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 273504ca-132c-4d30-a738-611aa901af34 · outbound

This paper cites Fast Segment Anything.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Fast Segment Anything

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:18:16.650430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4b5c28c1-d9d9-40d9-b8aa-0399555d036d · outbound

This paper cites EdgeSAM: Prompt-In-the-Loop Distillation for SAM.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model EdgeSAM: Prompt-In-the-Loop Distillation for SAM

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:18:16.656549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a080f4a1-cfdf-45cd-a72c-45836c25ab30 · outbound

This paper cites Ed- getam: On-device track anything model.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Ed- getam: On-device track anything model

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.482912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a82e9b9b-0c4e-4b14-9291-0f0e91251b7e · outbound

This paper cites Rmem: Restricted memory banks improve video object segmenta- tion.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Rmem: Restricted memory banks improve video object segmenta- tion

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.481165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 1cd5c504-be5f-449b-ade8-750be7fd906e · outbound

This paper cites Figure 5 illustrates the ability to accurately seg- ment movements among animals.

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model Figure 5 illustrates the ability to accurately seg- ment movements among animals

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-05-20T12:18:17.484748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation c67e17da-b85a-43d2-9b1b-fdaafcfbe305 · inbound

Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2 cites this paper.

Lean-SAM2: Target-Anchored Memory and Encoder Acceleration for SAM2 TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-01T11:43:11.216668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.