Paper Citation Record · LEDGER

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models

As of 7 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2506.03752.

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

pith.paper-citation-record.v1
2506.03752 v1

Coverage vector

measured 39 of 39 reference resolution

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measured 39 of 39 standing notices

One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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Reference resolution

39 of 39 outbound references displayed

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External citation measurements

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Outbound references

Observation f20d12c1-70d7-48d7-9727-290aa8653c1c · outbound

This paper cites Task-oriented training in rehabilitation after stroke: systematic re- view,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Task-oriented training in rehabilitation after stroke: systematic re- view,

Reference 1

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This paper cites Extra upper limb practice after stroke: a feasibility study,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Extra upper limb practice after stroke: a feasibility study,

Reference 2

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Observation 942a8864-5a37-428a-bac1-202a330c5ee9 · outbound

This paper cites Physical activity and exercise recommendations for stroke survivors: a statement for healthcare professionals from the american heart association/american stroke association,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Physical activity and exercise recommendations for stroke survivors: a statement for healthcare professionals from the american heart association/american stroke association,

Reference 3

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This paper cites What is current practice for upper limb rehabilitation in the acute hospital setting following stroke? a systematic review,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models What is current practice for upper limb rehabilitation in the acute hospital setting following stroke? a systematic review,

Reference 4

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Observation 80be9a05-8f65-463d-8dae-02120519783a · outbound

This paper cites Factors affecting rehabilitation and use of upper limb after stroke: views from healthcare professionals and stroke survivors,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Factors affecting rehabilitation and use of upper limb after stroke: views from healthcare professionals and stroke survivors,

Reference 5

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This paper cites Challenges in applying evidence-based practice in stroke rehabilita- tion: a qualitative description of health professional experience in low, middle, and high-income countries,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Challenges in applying evidence-based practice in stroke rehabilita- tion: a qualitative description of health professional experience in low, middle, and high-income countries,

Reference 6

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Observation 607ecf8f-392a-47b2-aef8-ef830e634f3e · outbound

This paper cites Interventions to aid patient adherence to physiotherapist prescribed self-management strategies: a systematic review,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Interventions to aid patient adherence to physiotherapist prescribed self-management strategies: a systematic review,

Reference 7

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This paper cites Qualitative analysis of stroke patients’ motivation for rehabilitation,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Qualitative analysis of stroke patients’ motivation for rehabilitation,

Reference 8

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This paper cites Architecture and applica- tions of virtual coaches,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Architecture and applica- tions of virtual coaches,

Reference 9

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This paper cites Virtual coaches: background, theories, and future research directions,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Virtual coaches: background, theories, and future research directions,

Reference 10

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Observation 61fcc4c7-9195-48fc-9236-6d42d3d69afe · outbound

This paper cites A clinically feasible kinematic assessment method of upper extremity motor function impairment after stroke,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models A clinically feasible kinematic assessment method of upper extremity motor function impairment after stroke,

Reference 11

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This paper cites Automated assessment of upper extremity movement impairment due to stroke,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Automated assessment of upper extremity movement impairment due to stroke,

Reference 12

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This paper cites Learning to assess the quality of stroke rehabilitation exercises,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Learning to assess the quality of stroke rehabilitation exercises,

Reference 13

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This paper cites Ai in rehabilitation medicine: Opportunities and challenges,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Ai in rehabilitation medicine: Opportunities and challenges,

Reference 14

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This paper cites Learning from Few Examples: A Summary of Approaches to Few-Shot Learning.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Learning from Few Examples: A Summary of Approaches to Few-Shot Learning

Reference 15

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This paper cites Towards personalized interaction and corrective feedback of a socially assistive robot for post-stroke rehabilitation therapy,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Towards personalized interaction and corrective feedback of a socially assistive robot for post-stroke rehabilitation therapy,

Reference 16

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This paper cites A low-cost virtual coach for 2d video-based compensation assessment of upper extremity reha- bilitation exercises,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models A low-cost virtual coach for 2d video-based compensation assessment of upper extremity reha- bilitation exercises,

Reference 17

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This paper cites A deep learning system to monitor and assess rehabilitation exercises in home- based remote and unsupervised conditions,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models A deep learning system to monitor and assess rehabilitation exercises in home- based remote and unsupervised conditions,

Reference 18

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Observation c54960db-98e1-4252-9d98-fdd49d06c33d · outbound

This paper cites Exploring a Gradient-based Explainable AI Technique for Time-Series Data: A Case Study of Assessing Stroke Rehabilitation Exercises.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Exploring a Gradient-based Explainable AI Technique for Time-Series Data: A Case Study of Assessing Stroke Rehabilitation Exercises

Reference 19

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Observation e14222c9-b590-46a1-9ef3-2e90cf679017 · outbound

This paper cites Learning frame-level classifiers for video-based real-time assessment of stroke rehabilitation exercises from weakly annotated datasets,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Learning frame-level classifiers for video-based real-time assessment of stroke rehabilitation exercises from weakly annotated datasets,

Reference 20

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This paper cites Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Segment Anything Model (SAM) Enhanced Pseudo Labels for Weakly Supervised Semantic Segmentation

Reference 21

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Frame-level label refinement for skeleton- based weakly-supervised action recognition,

Reference 22

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Cross-model pseudo-labeling for semi-supervised action recognition,

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This paper cites Transfer learning: a friendly introduction,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Transfer learning: a friendly introduction,

Reference 24

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Human action recognition based on transfer learning approach,

Reference 25

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Internal trans- fer learning for improving performance in human action recognition for small datasets,

Reference 26

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Skelresnet: Transfer learning approach for skeleton-based action recognition,

Reference 27

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Observation c890ae94-719c-4494-b20d-f1f38d553a13 · outbound

This paper cites Action transformer: A self-attention model for short-time pose-based human action recognition,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Action transformer: A self-attention model for short-time pose-based human action recognition,

Reference 28

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Skateformer: skeletal-temporal transformer for human action recognition,

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models MOMENT: A Family of Open Time-series Foundation Models

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models What do motor “recovery

Reference 31

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This paper cites Axiomatic attribution for deep networks,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Axiomatic attribution for deep networks,

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Skeleton tracking solutions for a low-cost stroke rehabilitation support system,

Reference 34

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Dosovitskiy, L

Reference 35

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This paper cites Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding,.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Ntu rgb+ d 120: A large-scale benchmark for 3d human activity understanding,

Reference 36

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Ntu rgb+ d: A large scale dataset for 3d human activity analysis,

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Cross-view action modeling, learning and recognition,

Reference 38

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This paper cites Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps.

Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Reference 39

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Frame-Level Real-Time Assessment of Stroke Rehabilitation Exercises from Video-Level Labeled Data: Task-Specific vs. Foundation Models Axiomatic Attribution for Deep Networks

Reference 40

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Pith citing papers

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