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Paper Citation Record · LEDGER

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning

As of 8 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 0 inbound Pith citation observations for arXiv:2608.01488.

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

pith.paper-citation-record.v1
2608.01488 v1

Coverage vector

measured 74 of 74 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:09:45.619182Z

measured 74 of 74 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

74 of 74 outbound references displayed

  • verified exact2
  • verified fuzzy66
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ed7c5e90-7d95-4826-b151-8d826f8327ff · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Joint feature learning and relation modeling for tracking: A one-stream framework,

Reference 1

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 775cfa2d-a4d0-423f-8221-f1413f4af10f · outbound

This paper cites Hhtrack: Hyperspectral object tracking using hybrid attention,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Hhtrack: Hyperspectral object tracking using hybrid attention,

Reference 2

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 87c2d92c-f04b-4c17-9362-e584e3a081e3 · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Mixformer: End-to-end tracking with iterative mixed attention,

Reference 3

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 5e16bc4a-d2f6-4058-a7b8-1f921940bd39 · outbound

This paper cites Cafuser: Condition- aware multimodal fusion for robust semantic perception of driving scenes,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Cafuser: Condition- aware multimodal fusion for robust semantic perception of driving scenes,

Reference 4

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e90ff0d1-0956-49c5-b8a4-68706949d38d · outbound

This paper cites SUTrack: Towards Simple and Unified Single Object Tracking.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning SUTrack: Towards Simple and Unified Single Object Tracking

Reference 5

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 817ff638-167c-4c3c-99b5-15fe748bf163 · outbound

This paper cites Single-model and any-modality for video object tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Single-model and any-modality for video object tracking,

Reference 6

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 446034d2-3dd7-4431-978c-a4626007ebe3 · outbound

This paper cites Sdstrack: Self-distillation symmetric adapter learning for multi-modal visual object tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Sdstrack: Self-distillation symmetric adapter learning for multi-modal visual object tracking,

Reference 7

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.401020Z digest=sha256:f8bfb09669be62e45eb719e479e025dea0635c0a57f184be255a0b8aeb2d1e7c

Observation d118faeb-1e07-4ae5-8151-0f675b966d4a · outbound

This paper cites Cross-modality distillation for multi-modal tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Cross-modality distillation for multi-modal tracking,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.396061Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.404136Z digest=sha256:13c839e7132cbe43717623559ac0afaebf7df78e0ca9034fe9aab8333057e168

Observation 4b5320c6-bad2-49ce-9226-ab4053459c7a · outbound

This paper cites Bi-directional adapter for multimodal tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Bi-directional adapter for multimodal tracking,

Reference 9

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.407190Z digest=sha256:f71ad9da12031c548b4ad75ba598fbcb9dc835de2a294f38baa86493cbf83d3d

Observation d559e0fb-b9f3-4f9d-a453-34f3471397a4 · outbound

This paper cites Visual prompt multi-modal tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Visual prompt multi-modal tracking,

Reference 10

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 70deafe0-b33f-4747-be2d-0c65987427b1 · outbound

This paper cites Onetracker: Unifying visual object tracking with foundation models and efficient tuning,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Onetracker: Unifying visual object tracking with foundation models and efficient tuning,

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.414217Z digest=sha256:a759e12c6aae7f9fd75c386ec7b75a3f9fcf0b7f6e663b9d5b085b820e529814

Observation c9835702-4470-4eba-970f-7c77eb0880fe · outbound

This paper cites Xtrack: Multimodal training boosts rgb-x video object trackers,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Xtrack: Multimodal training boosts rgb-x video object trackers,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.350256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 8fa1deca-c807-4cb9-993f-b74e4e5d0ce3 · outbound

This paper cites What you have is what you track: Adaptive and robust multimodal tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning What you have is what you track: Adaptive and robust multimodal tracking,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.359847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.423086Z digest=sha256:0dfc39bc25eaaea58cfd70cf04288cafa5b6f8d2bc71960df2e45c15f4d97566

Observation c929f761-7a88-45eb-be0e-0b4ac9742667 · outbound

This paper cites Exploiting Multimodal Spatial-temporal Patterns for Video Object Tracking.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Exploiting Multimodal Spatial-temporal Patterns for Video Object Tracking

Reference 15

Resolution
unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:09:45.426152Z digest=sha256:597bccdb7331ac36380def497f5b096c2522b33bb4a3f4989e31de8bdb5b3f22

Observation dd66aa32-c1a9-40e3-a804-24cd734a3ba9 · outbound

This paper cites Mambaevt: Event stream-based visual object tracking using state space model,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Mambaevt: Event stream-based visual object tracking using state space model,

Reference 16

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.430147Z digest=sha256:202cda78fb0941f4b735ec1603b684322d637ea510cc2e628a1f3703140bc482

Observation 7214ca39-0f0e-4d41-8a2f-6fb2d2ceaa9f · outbound

This paper cites Self-supervised learning for rgb-d object tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Self-supervised learning for rgb-d object tracking,

Reference 17

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.433146Z digest=sha256:643d60ccb53eefcbfe4037973612743ef54e7fd649333a7d71ae80f55f46904e

Observation f5b8edf8-eeeb-476b-824a-85f45f0ba6b0 · outbound

This paper cites Fmtrack: Frequency-aware interaction and multi-expert fusion for rgb- t tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Fmtrack: Frequency-aware interaction and multi-expert fusion for rgb- t tracking,

Reference 18

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ce8ad603-1c64-4021-9df9-bcc73348e676 · outbound

This paper cites Cross-modal orthogonal high-rank augmentation for rgb-event transformer-trackers,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Cross-modal orthogonal high-rank augmentation for rgb-event transformer-trackers,

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.313734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.439383Z digest=sha256:3130342f955fdebaea153fe90cd67561b098fbfd641459020bcb52bf53b96e63

Observation a9601beb-feff-43f4-867d-678869979b27 · outbound

This paper cites Lighttrack: Finding lightweight neural networks for object tracking via one-shot architecture search,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Lighttrack: Finding lightweight neural networks for object tracking via one-shot architecture search,

Reference 20

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 009efb01-8016-4fa5-808d-5e09f57737cf · outbound

This paper cites Litetrack: Layer pruning with asynchronous feature extraction for lightweight and efficient visual tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Litetrack: Layer pruning with asynchronous feature extraction for lightweight and efficient visual tracking,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.296271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 76fa55c8-7166-43cc-a878-a8cd58c622e0 · outbound

This paper cites Mixformerv2: Efficient fully transformer tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Mixformerv2: Efficient fully transformer tracking,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.287585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.449211Z digest=sha256:22f543159197f9b2f9327b59cfa7b75c7a349d055728c7faeabaf2b1cc834e30

Observation d24e43af-1b39-4176-b2e8-baab3af45435 · outbound

This paper cites Emtrack: Efficient multimodal object tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Emtrack: Efficient multimodal object tracking,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.278871Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 5b718b61-3029-4be8-abe8-2e11c42da6a7 · outbound

This paper cites Exploring pruning-based efficient object tracking via hybrid knowledge distillation,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Exploring pruning-based efficient object tracking via hybrid knowledge distillation,

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.455707Z digest=sha256:87c6e676e89072d9beb250ae5e432ceb20d15d69881245695a63ff9ef12b509d

Observation 6397810d-a8d0-4a47-a49c-23f481badfed · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Distilling the Knowledge in a Neural Network

Reference 25

Resolution
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no resolver link, observed 2026-08-06T00:09:45.458659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 60633b2c-997f-4567-85b3-ccda3a5951a2 · outbound

This paper cites Decoupled knowledge distillation,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Decoupled knowledge distillation,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.261525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation e5f6d67e-3063-470b-b361-e1ee35c6f21b · outbound

This paper cites Relational knowledge distillation,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Relational knowledge distillation,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.252503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation c62ca8dc-aa47-44cc-91dc-376dae51ef60 · outbound

This paper cites Relational knowledge distillation,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Relational knowledge distillation,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.242536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 02a6d4e8-2988-4656-baec-a6ad88280aac · outbound

This paper cites Learning from multiple teacher networks,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Learning from multiple teacher networks,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.233492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.473211Z digest=sha256:dd58fb216eda9feffa096ef0143abc33561fc943c879115ddb9caf1e6c7a255d

Observation bf1a71c0-11a6-4f2d-b64e-aa61ebc4b7ad · outbound

This paper cites Structured knowledge distillation for semantic segmentation,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Structured knowledge distillation for semantic segmentation,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.224347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.476515Z digest=sha256:f0123b7efaa1ddba02fb91edccfc16e0298e2267e1cf4df5238471d5c5b5237a

Observation ce128d14-3f1a-43e4-84e5-7ab19c03c3ba · outbound

This paper cites Double similarity distillation for semantic image segmentation,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Double similarity distillation for semantic image segmentation,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.214993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.480387Z digest=sha256:f3748e9982fa9a0fd468fa71d374fe878137b1ad8727caeac6189b6d2bc9f914

Observation 1845dbce-2641-4d24-9c7f-5d78031a9d75 · outbound

This paper cites Prompting for multi-modal tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Prompting for multi-modal tracking,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.205993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.483789Z digest=sha256:c1279511e5a0211a025cee7fcdc359e15629277155ba9906be8894c3536deab1

Observation ae711d23-1b69-4479-8a40-efc840626b4c · outbound

This paper cites Siam R-CNN: Visual tracking by re-detection,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Siam R-CNN: Visual tracking by re-detection,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.197170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.486742Z digest=sha256:11534705fa7bd309baeef0474a12b2d419cac16974e35d1cb3189dc59db34dd5

Observation 5b9bcf1f-38db-401e-a9ca-93857f1ee7c0 · outbound

This paper cites Transformer tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Transformer tracking,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.188404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.490016Z digest=sha256:a805563f1368750301de2ee8d8895f65697a000c4fd4d1dfabac35f865b14e9c

Observation 98426767-02ad-47f6-80f7-4b896535fe46 · outbound

This paper cites High-performance long-term tracking with meta-updater,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning High-performance long-term tracking with meta-updater,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.179586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.492700Z digest=sha256:ae9cd5de0c23b87234584603924d900255afce9b748db58b7f19a9d7e68527b7

Observation 6d7af632-8ad0-4cff-b5a1-31259946f8b0 · outbound

This paper cites Probabilistic regression for visual tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Probabilistic regression for visual tracking,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.170762Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.495709Z digest=sha256:9ab38ed5e1e25c2f8f0a76eebd7328416e0f106ad403c4fc195153d5af5b93b4

Observation beaea6ca-00ea-4e26-bbe2-e0f71133dcc7 · outbound

This paper cites Vital: Visual tracking via adversarial learning,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Vital: Visual tracking via adversarial learning,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.162240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.499114Z digest=sha256:46d2325eb7853a73344e3c4f06ab86fd9d951bf2f4fb2e33ed6620441551834f

Observation 77e3817e-642a-41c0-8ceb-9ee0075fca5b · outbound

This paper cites Learning multi-domain convolutional neural networks for visual tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Learning multi-domain convolutional neural networks for visual tracking,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.152519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.501878Z digest=sha256:b9cd68b74ecfe5756eb04e22116bb327385673802ea6ce5e349c5bae0faf84ea

Observation a71c6847-7eef-4bf6-afd6-1950873dc87e · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Atom: Accurate tracking by overlap maximization,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.143466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.504621Z digest=sha256:f3db9ed504db22bd3c45aab806348b6886025061a8faa18203eff7442e84a7bf

Observation 46d6e2b3-afce-4768-b022-b443641ef28f · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Learning spatio-temporal transformer for visual tracking,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.133776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.508394Z digest=sha256:69fe4a5bdadf08a612bf211cc102d930fede26428da163451620badaf2a80d5a

Observation d3736a04-9935-4c84-aafc-549119065670 · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Siamban: Target-aware tracking with siamese box adaptive network,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.123633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.511427Z digest=sha256:95a633b6d34cb875f8f4e30c99e0b8ff40a563d25f4e1f9a34b42337963a0908

Observation 4413f9c7-2fd5-440b-bcf5-c8668d532482 · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Fast online object tracking and segmentation: A unifying approach,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.113825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.514377Z digest=sha256:a91992c7495a662671e35012e62f0f6c6a470f47a2125cbd415c70e15f3ef44b

Observation 3de9d966-018c-47c4-ba50-a09836a49b3e · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Attribute-based progressive fusion network for rgbt tracking,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.104527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.517411Z digest=sha256:c36c84a60fe4305fc18870267585dd962af85456b42d79284b46327e00d5a86c

Observation 7810d613-66be-4904-8011-b5f7dd83115c · outbound

This paper cites Cross-modal pattern-propagation for rgb-t tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Cross-modal pattern-propagation for rgb-t tracking,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.095937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.520289Z digest=sha256:d8ddc21be73a8baef69669d83513bce0f776e991b04ffe28ae445274715ba9f2

Observation effb7b87-3d4a-4f17-8c0d-3306b193efba · outbound

This paper cites Jointly modeling motion and appearance cues for robust RGB-T tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Jointly modeling motion and appearance cues for robust RGB-T tracking,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.087532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.523945Z digest=sha256:99dcda2f80f3cf773a9c21353b42bef4a6a12bf9e6b3d691b633170cddafb924

Observation 1c9c684d-efd0-4ee3-9a82-53e10f4f82f5 · outbound

This paper cites Challenge-aware RGBT tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Challenge-aware RGBT tracking,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.077541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.526650Z digest=sha256:54fdbfb579a7e46a6e990df73f675ac08e6db71654f7a8a84333fc27520b053e

Observation cdcc709a-05ed-44d4-87f2-65f8f76aca66 · outbound

This paper cites Quality-aware feature aggregation network for robust RGBT tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Quality-aware feature aggregation network for robust RGBT tracking,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.068198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.529642Z digest=sha256:17a61e8976b8d92038db4cf56865ca10e5263478aa38d6e12973a4bf66aa59c1

Observation 09459674-ab58-47ec-a941-97cf59504ec7 · outbound

This paper cites Dense feature aggregation and pruning for RGBT tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Dense feature aggregation and pruning for RGBT tracking,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.058630Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.532773Z digest=sha256:a8160f5af6294ee5ec525fcfa36fb5638c814246b378a7cd049d98ed5f4d1e65

Observation 9dd0b79d-0b98-4be5-92f1-58af100f4b20 · outbound

This paper cites Deep adaptive fusion network for high performance RGBT tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Deep adaptive fusion network for high performance RGBT tracking,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.049287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.535769Z digest=sha256:5309c8541a64b9ba2ba5ef0128cfd8216974fd04f9cfbe708e3da743b04ce325

Observation 571e0ec0-4c8e-4f5a-a52c-2880d0ec09dc · outbound

This paper cites Object tracking in RGB-T videos using modal-aware attention network and competitive learning,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Object tracking in RGB-T videos using modal-aware attention network and competitive learning,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.040053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.539077Z digest=sha256:2863e2f3da068401da192283f50c09c99522a7ba3bebe5bafeb9cf510ac1d2a4

Observation b3efdcb1-b796-499c-8c63-465fc0f908bf · outbound

This paper cites Exploring Enhanced Contextual Information for Video-Level Object Tracking.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Exploring Enhanced Contextual Information for Video-Level Object Tracking

Reference 51

Resolution
verified exact
local_arxiv, observed 2026-08-06T00:09:45.804317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.541820Z digest=sha256:023afd33fcec7e1f1a6189f7c969f07c0d6e4768d82ea6059fd36d89ef23c976

Observation 254a2210-1dbb-44f1-b6e8-943f9fc73006 · outbound

This paper cites Fast-itpn: Integrally pre-trained transformer pyramid network with token migration,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Fast-itpn: Integrally pre-trained transformer pyramid network with token migration,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.031085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.545175Z digest=sha256:ae40c54ec5d74e96ae72e0a4005ee974228998888a99f1c5bc490a972b8ed254

Observation a93cc7b4-9312-4abb-bae2-be1feafcf37c · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Got-10k: A large high-diversity benchmark for generic object tracking in the wild,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.022165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.548657Z digest=sha256:26f27ab7d063983a0b95d372194cff2e7a8b3c1894f0a958979723301d48dc85

Observation 20dde008-6850-4ec5-8e0e-78b883a3ec5d · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Trackingnet: A large-scale dataset and benchmark for object tracking in the wild,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.012423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.551551Z digest=sha256:3c00b4c145b5c2ddaa2bfb35d887e778c0b2928b9d302a3348c0f28b2faf95d9

Observation fabd465d-7895-408a-a8f3-64c580da8891 · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Microsoft coco: Common objects in context,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:46.002594Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.554534Z digest=sha256:54b50f1912dac800174d8371266d0ab826f9d8203e465191d7e201754cbb8358

Observation 9a8152e0-66cb-4870-9447-841c7846999a · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Lasot: A high-quality benchmark for large-scale single object tracking,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.992729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.557637Z digest=sha256:a71c66570ab167d5c105b74408dca0c485f02e3441eb398d9f1b0bacab084dbc

Observation 0c998677-8d21-4256-8faf-2e10a0796100 · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Lasher: A large-scale high-diversity benchmark for rgbt tracking,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.982352Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.560467Z digest=sha256:c59cca9e73bc1b14b8c97332ac18f23ec2d8b717ab521f8ec5902d2220a818af

Observation 4c9f9456-81ed-45d4-b9b0-cece5158950d · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Visevent: Reliable object tracking via collaboration of frame and event flows,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.972313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.563568Z digest=sha256:4688ecd6905f317780686f5bc23420d481aaa999b592da3dc4633d889e686840

Observation 8d1bc65a-67f4-4dd3-912a-2c271df176e9 · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Depthtrack: Unveiling the power of rgbd tracking,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.963228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.567327Z digest=sha256:ac137d718158379d06cdd3ba91535ba1e4db20096eef994974e2db419c879b8b

Observation d2180809-1177-4bad-910e-52387ef08fa4 · outbound

This paper cites Rgbd1k: A large-scale dataset and benchmark for rgb-d object tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Rgbd1k: A large-scale dataset and benchmark for rgb-d object tracking,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.953438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.570535Z digest=sha256:e05d19826075c2335eb5874d11c94b4cd03dacc794d9c9c90704e05f2b978146

Observation 6bcbeb21-a9db-42c6-91a7-47b8a9534477 · outbound

This paper cites Correlation- aware deep tracking,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Correlation- aware deep tracking,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.942011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.574169Z digest=sha256:17d4d6555fbc20562f8e2fe971a8dff323cbecfd92fb748c2fd338d2abeef9b6

Observation 9004d9bc-2a79-447a-a5ce-f3a46dab6e61 · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning The tenth visual object tracking vot2022 challenge results,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.930704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.577885Z digest=sha256:dce57bab9dd1b53095727b1f9d31bdef4ab7a4ab8ea2132577c3636f23c6cff2

Observation 41b0b6c6-da42-4c8f-a945-913abe2204e2 · outbound

This paper cites The eighth visual object tracking VOT2020 challenge results,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning The eighth visual object tracking VOT2020 challenge results,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.919732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.580770Z digest=sha256:4b71041118a5589447d7114642fa7e995553f7c7c6a2880a5d726fa0368c3127

Observation 30e40a7b-fdde-4c20-8f0d-7cf66a4d4e37 · outbound

This paper cites Dal: A deep depth-aware long-term tracker,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Dal: A deep depth-aware long-term tracker,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.909738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.583500Z digest=sha256:1b2b2f78bbdb4f6b05f3328125b00bbfd62a1a8bb401b96061dd3441805861ea

Observation f1998aeb-2155-4c80-8b22-dc647c00b748 · outbound

This paper cites The seventh visual object tracking VOT2019 challenge results,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning The seventh visual object tracking VOT2019 challenge results,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.900796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.587062Z digest=sha256:dbc38855c06c1a63d4529a56de6c20c7f3cff0eec419f8ea2b7c129d5ba07d35

Observation 59ac86b9-14a2-4235-aedd-db458844e1b2 · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Context-aware three-dimensional mean-shift with occlusion handling for robust object tracking in RGB-D videos,

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.892407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.589843Z digest=sha256:a96279bbda6aa93d3c794fca0b666cd113859f21a82d4eeaf0191413a37ae77d

Observation 294601b8-82a8-4689-bbba-a2b39591d0bb · outbound

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

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Learning discrimi- native model prediction for tracking,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.882609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.592741Z digest=sha256:8a4c4e714096f6eb8051f22f3ec14d3b08cc2ec369ddd9eae2a40681023a2dc6

Observation aefcdcd9-707b-41d0-aa87-10fbe1e6713d · outbound

This paper cites Channel-wise knowledge distillation for dense prediction,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Channel-wise knowledge distillation for dense prediction,

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.872267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.595760Z digest=sha256:f496ff500dcd888c4d31a982cfb31009fa0ed25140b8c3d00786e074c12a4e76

Observation a8a382e4-2bf8-4cbb-a52b-f67722b8e486 · outbound

This paper cites FitNets: Hints for Thin Deep Nets.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning FitNets: Hints for Thin Deep Nets

Reference 69

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unresolved
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Observation 4e5fea43-c5b8-4fee-a932-c17191b56a7f · outbound

This paper cites Similarity-preserving knowledge distillation,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Similarity-preserving knowledge distillation,

Reference 70

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verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.862165Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation ae849a77-651f-4a6a-9a05-bdea66e2c9fc · outbound

This paper cites Customkd: Customizing large vision foundation for edge model improvement via knowledge distillation,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Customkd: Customizing large vision foundation for edge model improvement via knowledge distillation,

Reference 71

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verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.852508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 016d73eb-3986-4d8f-b800-2f0ec16e6331 · outbound

This paper cites Attention-guided Feature Distillation for Semantic Segmentation.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Attention-guided Feature Distillation for Semantic Segmentation

Reference 72

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verified exact
local_arxiv, observed 2026-08-06T00:09:45.783428Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation dc3f0682-4722-48bd-86ad-cdb508d155d0 · outbound

This paper cites Rethinking knowledge distillation with raw features for semantic segmentation,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Rethinking knowledge distillation with raw features for semantic segmentation,

Reference 73

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verified fuzzy
raw_fallback, observed 2026-08-06T00:09:45.842222Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T00:09:45.612443Z digest=sha256:a2d3602a10f4e496df245d9fe29d5423c3e51a83a4fc52517b14c156912634dc

Observation ea853971-8cb0-4f46-9d26-0a143d057e24 · outbound

This paper cites Simple semi-supervised knowledge distillation from vision-language models via dual-head optimization,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Simple semi-supervised knowledge distillation from vision-language models via dual-head optimization,

Reference 74

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unresolved
no resolver link, observed 2026-08-06T00:09:45.616325Z

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source=pdf_text observed=2026-08-06T00:09:45.616325Z digest=sha256:1389ba7c36be0535c725b1db839f59892a1306b5e88f4f8a586f7b87e6e73485

Observation 43f71132-027a-4c9a-8d3a-73bae4af8369 · outbound

This paper cites Generative adversarial networks,.

Towards Compact Unified Multimodal Tracking: Synergizing Knowledge Distillation with Structural Pruning Generative adversarial networks,

Reference 75

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unresolved
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Pith citing papers

No inbound Pith citation observations are available.