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Paper Citation Record · LEDGER

Towards Universal Modal Tracking with Online Dense Temporal Token Learning

As of 18 August 2026, this Paper Citation Record lists 100 of 115 outbound references and 1 inbound Pith citation observation for arXiv:2507.20177.

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

pith.paper-citation-record.v1
2507.20177 v1

Coverage vector

measured 100 of 115 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:53:15.979273Z

measured 101 of 101 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:31:24.946377Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T05:31:25.245822Z

Reference resolution

100 of 115 outbound references displayed

  • verified exact1
  • verified fuzzy47
  • unresolved52
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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Outbound references

Observation be93c374-6062-41b2-8fc3-2251dff6ea35 · outbound

This paper cites Fully-convolutional siamese networks for object tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Fully-convolutional siamese networks for object tracking,

Reference 1

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Observation 96367ad2-66da-41de-bb00-61c8578db0b3 · outbound

This paper cites High performance visual tracking with siamese region proposal network,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning High performance visual tracking with siamese region proposal network,

Reference 2

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Observation 8ae32f4c-e556-4fbe-855e-9552bec4252a · outbound

This paper cites Distractor-aware siamese networks for visual object tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Distractor-aware siamese networks for visual object tracking,

Reference 3

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Observation f06bb1b7-46ac-46a4-b54f-46510e981654 · outbound

This paper cites SiamRPN++: Evolution of siamese visual tracking with very deep networks,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning SiamRPN++: Evolution of siamese visual tracking with very deep networks,

Reference 4

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Observation e47b0c32-71c7-4ce5-bff6-f49ba8255f81 · outbound

This paper cites Fast online object tracking and segmentation: A unifying approach,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Fast online object tracking and segmentation: A unifying approach,

Reference 5

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Observation 99bc8ca4-fe9f-4740-b207-3bd36d3c386f · outbound

This paper cites Deeper and wider siamese networks for real- time visual tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Deeper and wider siamese networks for real- time visual tracking,

Reference 6

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Observation a7eb5785-268d-479d-ba9b-bb8adb440442 · outbound

This paper cites Faster r-cnn: towards real-time object detection with region proposal networks,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Faster r-cnn: towards real-time object detection with region proposal networks,

Reference 7

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Observation de46da54-cafb-42ed-90b3-6288195c86d3 · outbound

This paper cites Object tracking benchmark,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Object tracking benchmark,

Reference 8

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Observation b5c1ef90-b7cc-4bc8-bfe4-062be3ed6ddd · outbound

This paper cites TrackingNet: A large-scale dataset and benchmark for object tracking in the wild,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning TrackingNet: A large-scale dataset and benchmark for object tracking in the wild,

Reference 9

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Observation c20968d1-5f7b-4d19-a3c8-1c7c75f38ddb · outbound

This paper cites LaSOT: A high-quality benchmark for large-scale single object tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning LaSOT: A high-quality benchmark for large-scale single object tracking,

Reference 10

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Observation 8f4524ba-04a1-4280-a5a5-28331abd1624 · outbound

This paper cites Got-10k: A large high-diversity benchmark for generic object tracking in the wild,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Got-10k: A large high-diversity benchmark for generic object tracking in the wild,

Reference 11

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Observation 6a079d8e-0ced-44df-85a0-f2c64a635343 · outbound

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

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Microsoft COCO: Common objects in context,

Reference 12

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Observation 950aa2c0-7595-400e-baf4-2f7cd23885d6 · outbound

This paper cites Generalized intersection over union: A metric and a loss for bounding box regression,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Generalized intersection over union: A metric and a loss for bounding box regression,

Reference 13

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Observation 8c0330db-277e-46fc-94fb-b223b851637c · outbound

This paper cites Learning discrimi- native model prediction for tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Learning discrimi- native model prediction for tracking,

Reference 14

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Observation 5b2ff443-976b-43dd-962c-97e8bbe7217b · outbound

This paper cites ATOM: Accurate tracking by overlap maximization,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning ATOM: Accurate tracking by overlap maximization,

Reference 15

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Observation f4d5e58a-9160-4ac5-bb58-7da8a1ab3289 · outbound

This paper cites ECO: Efficient convolution operators for tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning ECO: Efficient convolution operators for tracking,

Reference 16

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Observation 8b2e9c06-9baf-473a-a923-3f776eaed7e9 · outbound

This paper cites Siamfc++: Towards robust and accurate visual tracking with target estimation guidelines,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Siamfc++: Towards robust and accurate visual tracking with target estimation guidelines,

Reference 17

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Observation 5941de13-4088-4e0f-95c9-2a70b05db128 · outbound

This paper cites Ocean: Object-aware anchor-free tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Ocean: Object-aware anchor-free tracking,

Reference 18

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Observation ba91ed5b-db35-4095-87e0-6cada755024b · outbound

This paper cites an unresolved cited work.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Unresolved cited work

Reference 19

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Observation d1010fd1-5b67-4381-8ae2-1a28fb475720 · outbound

This paper cites Toward accurate pixelwise object tracking via attention retrieval,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Toward accurate pixelwise object tracking via attention retrieval,

Reference 20

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Observation b76586a5-6a56-4db6-a024-9e4fd810f8a5 · outbound

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

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Video object segmentation using space-time memory networks,

Reference 21

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Observation b62c12fe-74be-49d6-a1e2-828043b44080 · outbound

This paper cites D3s-a discriminative single shot segmentation tracker,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning D3s-a discriminative single shot segmentation tracker,

Reference 22

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Observation a8318263-c4e5-477a-8461-2649086e762b · outbound

This paper cites Siamban: Target-aware tracking with siamese box adaptive network,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Siamban: Target-aware tracking with siamese box adaptive network,

Reference 23

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Observation fbab66eb-8422-4aa8-8ce8-d7c395baf728 · outbound

This paper cites Siamcar: Siamese fully convolutional classification and regression for visual tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Siamcar: Siamese fully convolutional classification and regression for visual tracking,

Reference 24

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Observation a8fdef00-91d2-46d8-9053-35f3f9e6af52 · outbound

This paper cites Learning the model update for siamese trackers,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Learning the model update for siamese trackers,

Reference 25

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Observation f6e545dd-79d6-4f42-98d9-9d060b1c6f33 · outbound

This paper cites Learning to filter: Siamese relation network for robust tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Learning to filter: Siamese relation network for robust tracking,

Reference 26

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Observation 38e31f67-ec67-4759-bc95-2c07023cb7a8 · outbound

This paper cites Learning to fuse asymmetric feature maps in siamese trackers,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Learning to fuse asymmetric feature maps in siamese trackers,

Reference 27

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Observation e6b42ca0-3710-4541-a02a-443353608ad9 · outbound

This paper cites Pg-net: Pixel to global matching network for visual tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Pg-net: Pixel to global matching network for visual tracking,

Reference 28

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Observation 4d5a9254-5118-4b71-a734-541925541bf3 · outbound

This paper cites Stmtrack: Template-free visual tracking with space-time memory networks,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Stmtrack: Template-free visual tracking with space-time memory networks,

Reference 29

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Observation 6ecc779a-a454-4d4e-a770-9fcbb54dac1f · outbound

This paper cites Graph attention tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Graph attention tracking,

Reference 30

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Observation b6723bc4-1533-4181-bdf3-db34683ee417 · outbound

This paper cites High- performance transformer tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning High- performance transformer tracking,

Reference 31

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Observation 27461da7-50c2-43a0-a7ee-ee11f052383b · outbound

This paper cites Learning spatio-temporal transformer for visual tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Learning spatio-temporal transformer for visual tracking,

Reference 32

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Observation 13e2ae34-0770-425a-9fd7-eb4e7a11a9e2 · outbound

This paper cites Transformer meets tracker: Exploiting temporal context for robust visual tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Transformer meets tracker: Exploiting temporal context for robust visual tracking,

Reference 33

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Observation e171a303-3584-44b1-9cbb-8f8eb0aee801 · outbound

This paper cites Probabilistic regression for visual tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Probabilistic regression for visual tracking,

Reference 34

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Observation 94223593-b04f-488b-8c4e-9a89c9e1b97a · outbound

This paper cites Decoupled weight decay regularization,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Decoupled weight decay regularization,

Reference 35

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Observation 2d73b067-5b2c-41ca-adf5-9a011ac10d9c · outbound

This paper cites Attention is all you need,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Attention is all you need,

Reference 36

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Observation 0d8aa7d3-3104-41b6-8bfc-a7118b483979 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning An image is worth 16x16 words: Transformers for image recognition at scale,

Reference 37

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Observation 17acecc9-e9cd-49d5-8216-accfd828563d · outbound

This paper cites Cvt: Introducing convolutions to vision transformers,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Cvt: Introducing convolutions to vision transformers,

Reference 38

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.679232Z digest=sha256:2d671eb2f90919227d299ba69a64243b35cc88e46dfbbfda378d944bc5fde76f

Observation 62e00927-5db6-4c43-978d-dacb7feccab1 · outbound

This paper cites End-to-end object detection with transformers,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning End-to-end object detection with transformers,

Reference 39

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raw_fallback, observed 2026-08-15T17:53:17.289565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.683386Z digest=sha256:902eb3e75b2535cf282dcdb35b161905a4521285ee8e671c4824555b35ebeab4

Observation 4648caa1-69c9-4332-9277-ba35ba3586ca · outbound

This paper cites Siam r-cnn: Visual tracking by re-detection,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Siam r-cnn: Visual tracking by re-detection,

Reference 40

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no resolver link, observed 2026-08-15T17:53:15.687830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.687830Z digest=sha256:63be483d224b779574d37e1156f95d036f33b08168d181d094e3d819a3d233b7

Observation fa05a3c8-61f3-480f-b38e-e306a2809c70 · outbound

This paper cites Deformable siamese attention networks for visual object tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Deformable siamese attention networks for visual object tracking,

Reference 41

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verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.261387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.692330Z digest=sha256:bd8ddab7e57721983748a9d4b914119fd4dee521c77f3ddc3492074dc53da36b

Observation 659643ab-9e79-43cb-983b-057d4ec20265 · outbound

This paper cites Learning target candidate association to keep track of what not to track,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Learning target candidate association to keep track of what not to track,

Reference 42

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verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.241583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.696489Z digest=sha256:4e931da6b655f366b6dfae3ceb58df772a9435212a6510e0ff97c103fc31b35d

Observation 3eb4ea7d-c363-4739-be69-ed5eabdd083f · outbound

This paper cites Mixformer: End-to-end track- ing with iterative mixed attention,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Mixformer: End-to-end track- ing with iterative mixed attention,

Reference 43

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verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.226014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.701639Z digest=sha256:768439e4f613f43188104f8823e48173b19b1f3ae5bf4f451d62575e632f851b

Observation 77807240-48f7-4bb3-ba36-84441814d1c6 · outbound

This paper cites Joint feature learning and relation modeling for tracking: A one-stream framework,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Joint feature learning and relation modeling for tracking: A one-stream framework,

Reference 44

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verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.210243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.706494Z digest=sha256:2d57f4a658afd63d866ee6519ef331a25e4663821db10ed477ea0d4425ae649d

Observation 7fec31e2-b7ac-4faf-b54e-fe8703d3b69b · outbound

This paper cites Towards more flexible and accurate object tracking with natural lan- guage: Algorithms and benchmark,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Towards more flexible and accurate object tracking with natural lan- guage: Algorithms and benchmark,

Reference 45

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no resolver link, observed 2026-08-15T17:53:15.711270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.711270Z digest=sha256:4b67bc0cd67c5ab150d7591927eb420f3910d55d733f55fbfc4380fe68340f3b

Observation cee36789-ba28-4ddd-81e3-e9784426cfa5 · outbound

This paper cites Focal loss for dense object detection,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Focal loss for dense object detection,

Reference 46

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no resolver link, observed 2026-08-15T17:53:15.715926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.715926Z digest=sha256:0eae9f21d85654c83307afaec6b28b057accbc0e17009697a955ec8acfef5ee8

Observation 0e8745b4-2dc9-4726-bf9f-5d2be9bcd7c8 · outbound

This paper cites Masked autoencoders are scalable vision learners,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Masked autoencoders are scalable vision learners,

Reference 47

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unresolved
no resolver link, observed 2026-08-15T17:53:15.720530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.720530Z digest=sha256:ff0d0217d1cb9bba43e03597a24f57c0e1e8dec6459cca20d68fd84171f2fed4

Observation ee88c63a-e4a3-4a7f-9eb2-e8a74b81b40b · outbound

This paper cites Lasot: A high-quality large-scale single object tracking benchmark,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Lasot: A high-quality large-scale single object tracking benchmark,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.158499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.725279Z digest=sha256:c457e3bedc225c67bf8aced6bf08f80312b8f477a2e8d67150ae4fb5fb9b6e6a

Observation d76bde2b-c8e5-4edf-8393-a0752fac3b55 · outbound

This paper cites Learning target-aware representation for visual tracking via informative interac- tions,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Learning target-aware representation for visual tracking via informative interac- tions,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.139216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.729800Z digest=sha256:3c7f9e77fbd530cda5357a3cb4ad5eba1a4bd85ea58a654621c725f7c521384d

Observation e0ef0b76-8b4c-4955-8e3d-3de1173288f0 · outbound

This paper cites Correlation-aware deep tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Correlation-aware deep tracking,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.123784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.734213Z digest=sha256:e508a5f0f7f2e63266b78b4fd9a8a05c8c3bf5a3e81e2b3d2e1e0a7da8dcd209

Observation 2855c361-5b58-4b28-9c40-73800e25a123 · outbound

This paper cites Backbone is all your need: A simplified architecture for visual object tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Backbone is all your need: A simplified architecture for visual object tracking,

Reference 51

Resolution
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raw_fallback, observed 2026-08-15T17:53:17.108713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.738994Z digest=sha256:9ba8136a373b9a81074ab45330db261a481ab208374e78145c880ed3173e887a

Observation e6933106-4ef4-4d36-9158-c4190d9aa7de · outbound

This paper cites Aiatrack: Attention in attention for transformer visual tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Aiatrack: Attention in attention for transformer visual tracking,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.092952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.743530Z digest=sha256:2859b91ef3fec9211188f3c0d0ddf2b60ab876df4a0c4f1b6063ba55133aec80

Observation ff577d27-d782-4a31-8992-49f61ec5ca69 · outbound

This paper cites Seqtrack: Sequence to sequence learning for visual object tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Seqtrack: Sequence to sequence learning for visual object tracking,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.076365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.748011Z digest=sha256:9c6e196bd732ec0e03e94f9c6d5466df21f620dc423daeae79533cf7dc2521d8

Observation 45c0c750-4852-4922-a969-33711c56f58c · outbound

This paper cites Autore- gressive visual tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Autore- gressive visual tracking,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.059738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.752432Z digest=sha256:dd71166a2960c1b14d2a55833af0aef9df89120cce9d231562b003287bed284b

Observation 53b742aa-cd81-4380-a51a-9cdf7216f7c6 · outbound

This paper cites Videotrack: Learning to track objects via video transformer,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Videotrack: Learning to track objects via video transformer,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.043958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.756941Z digest=sha256:9a00e754f642d5cb25ee021c6a0862218d139cadd9b51b06c6b04377b462b2a4

Observation c4df4e17-ee5d-42dd-888e-63deb590d2df · outbound

This paper cites Tctrack: Temporal contexts for aerial tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Tctrack: Temporal contexts for aerial tracking,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.026531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.761392Z digest=sha256:b4e885ae4d81d411a32355e4cdd6cd0badfe11ba2736eb3f75f25b2c9709364d

Observation fb2ce780-672d-4d94-a01f-06a13790095a · outbound

This paper cites The eighth visual object tracking vot2020 challenge results,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning The eighth visual object tracking vot2020 challenge results,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:17.009194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.765873Z digest=sha256:07b8098b39bd3dd6bbdd3db9b6d3409d70d74e4e13326d1a4f4c24c6f8399b12

Observation fa4d8d69-771b-4a91-b192-e827b82d6e77 · outbound

This paper cites Alpha-refine: Boosting tracking performance by precise bounding box estimation,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Alpha-refine: Boosting tracking performance by precise bounding box estimation,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.993318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.770346Z digest=sha256:d58ce50b45f41c7300e3329e0c8ace9f4e196498dbfad4fbd775bf347e8b0d87

Observation 5a932296-8fdd-4c2d-b961-945448464233 · outbound

This paper cites Generalized relation modeling for transformer tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Generalized relation modeling for transformer tracking,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.978036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.775006Z digest=sha256:ddbcc2b167a7660f27887ed7ea51f4d909343aa6896f9eb0ae03a06a1f00cf39

Observation b2427539-761c-4da3-8eb9-2c2f10e81841 · outbound

This paper cites Instance-level segmentation for autonomous driving with deep densely connected mrfs,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Instance-level segmentation for autonomous driving with deep densely connected mrfs,

Reference 60

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raw_fallback, observed 2026-08-15T17:53:16.962521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.779490Z digest=sha256:edd8cf5f11296710f721ff1d02cdfe5fa8fdff8ba45cdcd38577adf0fa0b5789

Observation d37bfc42-b256-4b47-bea1-2dd746e836be · outbound

This paper cites VideoChat: Chat-Centric Video Understanding.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning VideoChat: Chat-Centric Video Understanding

Reference 61

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no resolver link, observed 2026-08-15T17:53:15.784030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.784030Z digest=sha256:866bc7c00daa365f46b2aeb1f7f573a9ceea677f65515060fb1790eeeb16baf1

Observation 08ad3ba4-a664-44e2-b86b-84c73e0d7054 · outbound

This paper cites Hand posture recognition using finger geometric feature,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Hand posture recognition using finger geometric feature,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.946270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.789105Z digest=sha256:222de9c013a96f69db1da2ccc42655c4f0d76a686db718aa2c6cbe27a7f5e918

Observation f4d98f0f-480f-4bb1-aba4-a78855cc915b · outbound

This paper cites Visual prompt multi- modal tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Visual prompt multi- modal tracking,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.931688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.793538Z digest=sha256:9b490ffff3b98eb227bb6816e9b33f000047c05fe912e96148443fc2c6b0664e

Observation cb8bdc93-d25a-42b6-8f04-2ea71b66da54 · outbound

This paper cites Multi-modal fusion for end-to-end rgb-t tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Multi-modal fusion for end-to-end rgb-t tracking,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.916485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.798038Z digest=sha256:9a985ce3aadc1dbd6d8304f29c43e3fe1ca31c262bc427f3d7311b4132f29cd6

Observation b3e12001-5b0f-44ae-8508-c7bbc47a3a89 · outbound

This paper cites Bridging search region interaction with template for rgb-t tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Bridging search region interaction with template for rgb-t tracking,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.900847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.804653Z digest=sha256:58a58320e4ff1dd7d5c76c9e13424308b96777caf4e2c773f02c1cfbeb036b01

Observation a903b2d3-cbcb-4d29-9766-6aafab6e6912 · outbound

This paper cites Resource-efficient rgbd aerial tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Resource-efficient rgbd aerial tracking,

Reference 66

Resolution
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raw_fallback, observed 2026-08-15T17:53:16.885625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.809539Z digest=sha256:e98ff66effa5937303e187ba94c1b60a0990a8e8255fe1513f67141826e5614b

Observation 19a3e957-e583-465e-96b4-d243b6481274 · outbound

This paper cites Revisiting Color-Event based Tracking: A Unified Network, Dataset, and Metric.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Revisiting Color-Event based Tracking: A Unified Network, Dataset, and Metric

Reference 67

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unresolved
no resolver link, observed 2026-08-15T17:53:15.814344Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.814344Z digest=sha256:a3f6343118964637a1a314f11941628a95c5ce22940d1ad214829d9c73d6d414

Observation cd337aa6-fc14-4320-a762-5ee4f0c23405 · outbound

This paper cites RGB-T Tracking via Multi-Modal Mutual Prompt Learning.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning RGB-T Tracking via Multi-Modal Mutual Prompt Learning

Reference 68

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unresolved
no resolver link, observed 2026-08-15T17:53:15.819756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.819756Z digest=sha256:9d86a9703fa56f846d01f3b4ce4bd5e8efe1cdf2e06f5353f085ef321b0c51f4

Observation 2dd48326-59fe-4b81-9448-b63b861727b9 · outbound

This paper cites RGBD1K: A large-scale dataset and benchmark for RGB-D object tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning RGBD1K: A large-scale dataset and benchmark for RGB-D object tracking,

Reference 69

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unresolved
no resolver link, observed 2026-08-15T17:53:15.825156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.825156Z digest=sha256:a23e04f53b2894c7d89c2e6808b3d42c4eccc784b7684cd00b460bbcccab2dc5

Observation fa150ea0-bba1-4fef-bd32-029915d308af · outbound

This paper cites Learning dual-fused modality-aware representations for RGBD tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Learning dual-fused modality-aware representations for RGBD tracking,

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.857414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.830223Z digest=sha256:6cd57e0ee6b51e1a8f7030fb5df6b7724cf864f76e452dd7d2fbd8feff29419e

Observation 8b656d98-1398-455b-bba8-84eb896f13ea · outbound

This paper cites Object tracking by jointly exploiting frame and event domain,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Object tracking by jointly exploiting frame and event domain,

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.840820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.835167Z digest=sha256:5391e67748a91b6834ea7631d76cf533c7670be700f436c0866becbd5ed36dd9

Observation b05b50ec-c5a6-4e59-8ff2-57e431265c07 · outbound

This paper cites Lasher: A large-scale high-diversity benchmark for rgbt tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Lasher: A large-scale high-diversity benchmark for rgbt tracking,

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.824505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.839813Z digest=sha256:b3176d9ab0bfded6bbc35a0cafa0ba61a87412955f8ea490609fcc44e6f69414

Observation 0e6c6eaf-9abb-4b04-b653-a7286f6d30de · outbound

This paper cites Rgb-t object tracking: Benchmark and baseline,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Rgb-t object tracking: Benchmark and baseline,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.809095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.844495Z digest=sha256:184f5577ae2b93d57f6c1aff41e9fdbd83b3274c3241bebba798d9a98cc55f29

Observation 9d1ee074-912d-43b2-b008-8e017553ce1f · outbound

This paper cites Visevent: Reliable object tracking via collaboration of frame and event flows,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Visevent: Reliable object tracking via collaboration of frame and event flows,

Reference 74

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unresolved
no resolver link, observed 2026-08-15T17:53:15.850292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.850292Z digest=sha256:d962361202f855d62216a6e7bc5da48e81b66d5789f2ec073b46fda8a5d170c2

Observation ba4bfbb9-2d3a-4622-a230-e0b0faf37047 · outbound

This paper cites Depthtrack: Unveiling the power of rgbd tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Depthtrack: Unveiling the power of rgbd tracking,

Reference 75

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no resolver link, observed 2026-08-15T17:53:15.855085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.855085Z digest=sha256:1b996c7b7806a5a33b298241c5282b8cc823cd5d0b90c8a2f49a4fe62c4b49f8

Observation a3ed2b23-dd4a-4411-a5c1-098d2542f565 · outbound

This paper cites Prompting for multi-modal tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Prompting for multi-modal tracking,

Reference 76

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verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.772673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.859809Z digest=sha256:f59c563cc7b9ce3e97f537ca4c757c9400a0189927dc994bdb6ab2349dc83979

Observation c21d3705-da08-4dd2-8667-3e6afded20da · outbound

This paper cites Attribute-based progressive fusion network for rgbt tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Attribute-based progressive fusion network for rgbt tracking,

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.757000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.865329Z digest=sha256:937c43134c84af1c13fc20650e06474dcdc411207f1f2b167745e0f9253383a8

Observation 3fc23463-053a-4676-a860-89be150cd168 · outbound

This paper cites Duality-gated mutual condition network for rgbt tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Duality-gated mutual condition network for rgbt tracking,

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.741578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.870219Z digest=sha256:f4ac8f1b5f3770a08e1ae4bd3a9f7933323064fbcafd2c33124f991fb8c119f0

Observation b63ec5f3-98e1-4fcc-ac93-428c27325ca2 · outbound

This paper cites Single-Model and Any-Modality for Video Object Tracking.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Single-Model and Any-Modality for Video Object Tracking

Reference 79

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unresolved
no resolver link, observed 2026-08-15T17:53:15.875061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.875061Z digest=sha256:80cbd1742a73c50723ad2eaf94edf3c91bf38a69eb4ae65ede08819373eb7735

Observation 473d07bc-527a-4781-8a03-4efd71c23012 · outbound

This paper cites Context- aware three-dimensional mean-shift with occlusion handling for robust object tracking in rgb-d videos,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Context- aware three-dimensional mean-shift with occlusion handling for robust object tracking in rgb-d videos,

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.726636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.880310Z digest=sha256:5fc8c5e55d73e4967c1251077a7accb88c8cf0e6f5d353238c14932227ab24a4

Observation 64cbe906-eb02-4b5c-b729-8249a441e9b9 · outbound

This paper cites The seventh visual object tracking vot2019 challenge results,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning The seventh visual object tracking vot2019 challenge results,

Reference 81

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verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.711422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.885522Z digest=sha256:07445b4af6aa7aa877ca1a6f8d121af5607fe379c441befad35fc0440e357508

Observation 999eb2a6-fa50-4818-99d7-82ef4c430be7 · outbound

This paper cites The ninth visual object tracking vot2021 challenge results,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning The ninth visual object tracking vot2021 challenge results,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.696973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.890332Z digest=sha256:0d4e4c87e5a071dc940b47c3347b9e7fdbbc9e1c905795c5b65c52f870ff1751

Observation a00296b0-d319-4784-b9f2-d4bee38211f8 · outbound

This paper cites The tenth visual object tracking vot2022 challenge results,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning The tenth visual object tracking vot2022 challenge results,

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.682176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.895702Z digest=sha256:3672650a8abdceec6207baefe6feb7bae365c4133b0d2f5a05aa758b7d2b3ce1

Observation 52cc4e9c-25a8-45d2-bdb5-3ce613c3c2a8 · outbound

This paper cites Visible-thermal uav tracking: A large-scale benchmark and new baseline,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Visible-thermal uav tracking: A large-scale benchmark and new baseline,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.667696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.900637Z digest=sha256:5b3d06bb4f2d639a083b56db9084f039fe465b0322a030cb4bd9b6a3c8b4ddfa

Observation 381da7d8-d16f-4dd5-80b2-c78ce0088c1d · outbound

This paper cites Bi-directional Adapter for Multi-modal Tracking.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Bi-directional Adapter for Multi-modal Tracking

Reference 85

Resolution
verified exact
local_arxiv, observed 2026-08-15T17:53:16.225804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.905600Z digest=sha256:f870f7916a03f4f88658f0e2eb67892deeeaa9e443a5594fe02dddbc694e3f2f

Observation 7ad73c26-3a66-4023-907f-d552d1ee6bf8 · outbound

This paper cites Challenge-aware rgbt tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Challenge-aware rgbt tracking,

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.653030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.910471Z digest=sha256:2468bc15b179909342610ba54087116cd04ab6cc2deb561aff6463d0ca091342

Observation 55e34bfa-b45b-490e-909d-20de2b3d5b4b · outbound

This paper cites Multi- adapter rgbt tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Multi- adapter rgbt tracking,

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.638233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.915261Z digest=sha256:16ef61c9039f801220508e6cc0a38294f8b1baf50b7f4e7226e9c7c87649b3a6

Observation 590a0705-34a6-427a-bc2d-c76cd1a03df9 · outbound

This paper cites Odtrack: Online dense temporal token learning for visual tracking,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Odtrack: Online dense temporal token learning for visual tracking,

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.624349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.919888Z digest=sha256:a97699abe2e65f25a31dd959931a4906623ff6e64faed09c43c96b60538414bb

Observation 6d78d592-71fd-4d5d-9a2d-3f66046f093a · outbound

This paper cites OneLLM: One Framework to Align All Modalities with Language.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning OneLLM: One Framework to Align All Modalities with Language

Reference 89

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unresolved
no resolver link, observed 2026-08-15T17:53:15.924583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.924583Z digest=sha256:e6410b07e20b2016e4145da84acbdcdd58d7c6b710e0fd81aa96364e03b3fe16

Observation 2e29d7c8-6d3c-4d10-a013-551c0e47e808 · outbound

This paper cites Tf-icon: Diffusion-based training-free cross-domain image composition,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Tf-icon: Diffusion-based training-free cross-domain image composition,

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.609953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.929479Z digest=sha256:aa9ea43872156f4417102d84061af43313fdc8c53a2f3d5b5984897b6a9da4ae

Observation 6a1f644f-89f1-4958-9fd0-6c1a1ae3ed31 · outbound

This paper cites Mace: Mass concept erasure in diffusion models,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Mace: Mass concept erasure in diffusion models,

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.594647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.934527Z digest=sha256:cc19e6c5d7641d17dd660e231fdaa12ae25083deb6106ef5e4ac1402e766ce85

Observation 2803ed88-9d76-4eb0-b7be-98be9665acd6 · outbound

This paper cites Robust Watermarking Using Generative Priors Against Image Editing: From Benchmarking to Advances.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Robust Watermarking Using Generative Priors Against Image Editing: From Benchmarking to Advances

Reference 92

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unresolved
no resolver link, observed 2026-08-15T17:53:15.939124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.939124Z digest=sha256:5ba72ee227171e626dc02258754662bbb0bb70e7c3b457d4654f18f1255133d0

Observation 60cd0ac0-62d2-426b-837e-f4882594d9e1 · outbound

This paper cites EraseAnything: Enabling Concept Erasure in Rectified Flow Transformers.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning EraseAnything: Enabling Concept Erasure in Rectified Flow Transformers

Reference 93

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no resolver link, observed 2026-08-15T17:53:15.943930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.943930Z digest=sha256:4d741d4f5b16b66b4415d9aec7b1937cfed7b8669c4ebfd2e9a1a339c9011b2f

Observation e876de26-4698-4ff9-bf03-ea06e71798f4 · outbound

This paper cites Set You Straight: Auto-Steering Denoising Trajectories to Sidestep Unwanted Concepts.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Set You Straight: Auto-Steering Denoising Trajectories to Sidestep Unwanted Concepts

Reference 94

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no resolver link, observed 2026-08-15T17:53:15.949005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.949005Z digest=sha256:d6140339bbc323474769c795cb1144c0c68c0f2379a390233cba65f006e5967f

Observation 868e386f-eb58-4394-b6d6-2037f27644bd · outbound

This paper cites Diffusion models in low-level vision: A survey,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Diffusion models in low-level vision: A survey,

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.580191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.954007Z digest=sha256:e105d868d713d1eb3874f14fb9250b8c8397e4ce690ccd4b96d3605374d7af31

Observation 343de5ff-327b-4c09-a4cc-00d0961a6871 · outbound

This paper cites Segment concealed object with incomplete supervision,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Segment concealed object with incomplete supervision,

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.564354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.959823Z digest=sha256:720dc5d5fdb935659baf789209df32af6af7ce6deade02974696ee89e1e4b1b9

Observation 026071c7-33bf-455a-bb8a-6f1238c7648a · outbound

This paper cites Hqg-net: Unpaired medical image enhancement with high- quality guidance,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Hqg-net: Unpaired medical image enhancement with high- quality guidance,

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.548052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.964856Z digest=sha256:bd9b656d304b0fcdfc3fa2d541150163d41f654019b5580f79d332d5dbc51880

Observation 6157d0f3-eaca-4573-8466-9bf2ad57c516 · outbound

This paper cites UnfoldIR: Rethinking Deep Unfolding Network in Illumination Degradation Image Restoration.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning UnfoldIR: Rethinking Deep Unfolding Network in Illumination Degradation Image Restoration

Reference 98

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unresolved
no resolver link, observed 2026-08-15T17:53:15.969612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:53:15.969612Z digest=sha256:2d8339f9db5e852d93c808dd0a368a7c90639d88bcb8054128d89af6d4c4b0e4

Observation b7c512c8-e9f9-4510-902c-8d92b55f32fd · outbound

This paper cites Run: Reversible unfolding network for concealed object segmentation,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Run: Reversible unfolding network for concealed object segmentation,

Reference 99

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.532014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.974719Z digest=sha256:79ff5449897619f60df201497b2fa9ebfb2de1ee2fbdddb623b416b5c0e50b23

Observation 79520104-5643-49b1-9e5b-c08d1cdbaa82 · outbound

This paper cites Reti-diff: Illumination degradation image restoration with retinex-based latent diffusion model,.

Towards Universal Modal Tracking with Online Dense Temporal Token Learning Reti-diff: Illumination degradation image restoration with retinex-based latent diffusion model,

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:53:16.516649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T17:53:15.979273Z digest=sha256:6b4d7edc5718818a1153ff7e7ac6b65b9b283e43a662c011d2c21acaf32b81b2

Pith citing papers

Observation 3e7d5f95-a730-4ad1-8cf8-4310f2891dd7 · inbound

Enhancing Zero-Shot Brain Tumor Subtype Classification via Fine-Grained Patch-Text Alignment cites this paper.

Enhancing Zero-Shot Brain Tumor Subtype Classification via Fine-Grained Patch-Text Alignment Towards Universal Modal Tracking with Online Dense Temporal Token Learning

Reference 160

Resolution
verified exact
local_arxiv, observed 2026-08-06T05:31:25.255140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-06T05:31:24.946377Z digest=sha256:7510a8bedcb3abce81e7f3aa9c884bcf3055df0bf614413960ef2925e338ea05