Paper Citation Record · LEDGER

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data

As of 14 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2607.01838.

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pith.paper-citation-record.v1
2607.01838 v1

Coverage vector

measured 39 of 39 reference resolution

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measured 39 of 39 standing notices

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Pith citing papers itemized under the disclosed page cap.

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

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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 1a794d08-a453-4ce8-a643-cd742a5e5363 · outbound

This paper cites Deep learning for predicting rehabilitation success: Advancing clinical and patient-reported outcome modeling,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Deep learning for predicting rehabilitation success: Advancing clinical and patient-reported outcome modeling,

Reference 1

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Observation cf9ae2d6-efbb-464a-b49c-06eeec5e448b · outbound

This paper cites Systematic review of ai/ml applications in multi-domain robotic rehabilitation: trends, gaps, and future directions,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Systematic review of ai/ml applications in multi-domain robotic rehabilitation: trends, gaps, and future directions,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T04:20:40.281216Z

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Observation d2621cf8-f3d5-48b4-a3e6-f5a90bef93dc · outbound

This paper cites Philosophy and clinical rea- soning in rehabilitation sciences: Bridging the gap,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Philosophy and clinical rea- soning in rehabilitation sciences: Bridging the gap,

Reference 3

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This paper cites A unified approach to interpreting model predictions,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data A unified approach to interpreting model predictions,

Reference 4

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Observation 676f30f4-b737-4d80-9268-f73839bac53b · outbound

This paper cites Counterfactual explanations without opening the black box: Automated decisions and the gdpr,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Counterfactual explanations without opening the black box: Automated decisions and the gdpr,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T04:20:40.285602Z

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Observation 6683d957-d08a-4aa4-bff3-51b1ef09c5c9 · outbound

This paper cites M-cels: Counter- factual explanation for multivariate time series data guided by learned saliency maps,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data M-cels: Counter- factual explanation for multivariate time series data guided by learned saliency maps,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T04:20:40.273382Z

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Observation 08c8e15c-f92a-4be5-a0ed-dbe0cfa07ebd · outbound

This paper cites TSEvo: Evolutionary Counter- factual Explanations for Time Series Classification,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data TSEvo: Evolutionary Counter- factual Explanations for Time Series Classification,

Reference 7

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Observation abc8140d-c2cd-4156-95c2-a93d8236691c · outbound

This paper cites Counterfactual explanations for multivariate time series,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Counterfactual explanations for multivariate time series,

Reference 8

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Observation fd19da49-dda8-45dc-8cc0-a836b372f53c · outbound

This paper cites Instance-based counterfactual explanations for time series classification,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Instance-based counterfactual explanations for time series classification,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T04:20:40.270669Z

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Observation 03567d03-2577-44ec-83b2-925c7034d95d · outbound

This paper cites Inertial measurement units (IMUs) for biomechanical analysis in sport: a review of applications, challenges and future directions,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Inertial measurement units (IMUs) for biomechanical analysis in sport: a review of applications, challenges and future directions,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T04:20:40.330598Z

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Observation 25d1f7b1-be3c-4102-9386-a76b0eef9881 · outbound

This paper cites Wearable movement sensors for rehabilitation: A focused review of technological and clinical advances,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Wearable movement sensors for rehabilitation: A focused review of technological and clinical advances,

Reference 11

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Observation c089694e-1d45-41dd-94ff-4200b4822c1d · outbound

This paper cites Clinicians’ perspectives on inertial measurement units in clinical practice,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Clinicians’ perspectives on inertial measurement units in clinical practice,

Reference 12

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Observation ea926dea-ad7c-4d79-bece-36b0c7281819 · outbound

This paper cites A knee rehabilitation exercises dataset for postural assessment using wearable devices,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data A knee rehabilitation exercises dataset for postural assessment using wearable devices,

Reference 13

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Observation a30c92d3-fdbf-4a25-b36a-9c99ef26d65e · outbound

This paper cites Optimization of imu sensor placement for the measurement of lower limb joint kinematics,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Optimization of imu sensor placement for the measurement of lower limb joint kinematics,

Reference 14

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Observation e5b581eb-d9ed-48dc-b807-dffe0ebf55cd · outbound

This paper cites Effects of imu sensor-to-segment calibration on clinical 3d elbow joint angles estimation,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Effects of imu sensor-to-segment calibration on clinical 3d elbow joint angles estimation,

Reference 15

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Observation afa30c1d-d3e2-4e9e-8618-752cae15aab4 · outbound

This paper cites Algorithmic recourse: from counterfactual explanations to interventions,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Algorithmic recourse: from counterfactual explanations to interventions,

Reference 16

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Observation 7b9989c3-e87e-4e75-930c-f70a32a2a8ad · outbound

This paper cites Preserving causal constraints in counterfactual explanations for machine learning classifiers,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Preserving causal constraints in counterfactual explanations for machine learning classifiers,

Reference 17

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This paper cites Learning model- agnostic counterfactual explanations for tabular data,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Learning model- agnostic counterfactual explanations for tabular data,

Reference 18

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Observation 14694b54-7bb6-41b0-b2b3-7c21385fa012 · outbound

This paper cites Data-driven discovery of feature groups in clinical time series,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Data-driven discovery of feature groups in clinical time series,

Reference 19

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Observation 397d1258-28aa-4e3e-8b08-f1ac152e0aa0 · outbound

This paper cites Multi-objective coun- terfactual explanations,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Multi-objective coun- terfactual explanations,

Reference 20

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Observation e7048020-51f5-4b07-ab91-42b9831610dd · outbound

This paper cites Explaining machine learning classifiers through diverse counterfactual explanations,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Explaining machine learning classifiers through diverse counterfactual explanations,

Reference 21

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Observation 8297b863-36ad-4d23-a244-1471aa69b50c · outbound

This paper cites SG-CF: Shapelet- Guided Counterfactual Explanation for Time Series Classification,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data SG-CF: Shapelet- Guided Counterfactual Explanation for Time Series Classification,

Reference 22

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Observation 08f15c82-156d-4aec-9edc-74ba63dd07a3 · outbound

This paper cites Shapelet-based Model-agnostic Counterfactual Local Explanations for Time Series Classification.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Shapelet-based Model-agnostic Counterfactual Local Explanations for Time Series Classification

Reference 23

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Observation aab864a2-80a5-4a10-940d-1014a2432af8 · outbound

This paper cites On the mining of time series data counterfactual explanations using barycenters,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data On the mining of time series data counterfactual explanations using barycenters,

Reference 24

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This paper cites Attention-based counterfactual explanation for multivariate time series,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Attention-based counterfactual explanation for multivariate time series,

Reference 25

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Observation 7e1b746e-a695-470e-a9c0-35d0dac6472d · outbound

This paper cites Learning Time Series Counterfactuals via Latent Space Representations,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Learning Time Series Counterfactuals via Latent Space Representations,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T04:20:40.304060Z

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Observation 60aed715-ba09-4ac0-a9d6-3366a5cfbb45 · outbound

This paper cites Conditional Generative Models for Counterfactual Explanations.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Conditional Generative Models for Counterfactual Explanations

Reference 27

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This paper cites Comparative assessment of an imu-based wearable device and a marker-based optoelectronic system in trunk motion analysis: A cross-sectional investigation,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Comparative assessment of an imu-based wearable device and a marker-based optoelectronic system in trunk motion analysis: A cross-sectional investigation,

Reference 28

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Observation 7b8dc9fe-786d-4a95-a0ae-63c415280702 · outbound

This paper cites Ambulatory measurement of shoulder and elbow kinematics through inertial and magnetic sensors,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Ambulatory measurement of shoulder and elbow kinematics through inertial and magnetic sensors,

Reference 29

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Observation 4b8de747-0461-405f-bb69-f2a3b945e980 · outbound

This paper cites LIMU-BERT: Unleashing the Potential of Unlabeled Data for IMU Sensing Applications,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data LIMU-BERT: Unleashing the Potential of Unlabeled Data for IMU Sensing Applications,

Reference 30

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Observation e2170c62-1514-4560-ad12-96974f50a83a · outbound

This paper cites Calib-net: Calibrating the low-cost imu via deep convolutional neural network,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Calib-net: Calibrating the low-cost imu via deep convolutional neural network,

Reference 31

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This paper cites Interpretable deep learning: interpretation, interpretability, trustworthi- ness, and beyond,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Interpretable deep learning: interpretation, interpretability, trustworthi- ness, and beyond,

Reference 32

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Observation adf8a7c2-62ec-4b1e-9390-892a95c23397 · outbound

This paper cites Model selection and estimation in regression with grouped variables.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Model selection and estimation in regression with grouped variables

Reference 33

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Observation ef98f7eb-8998-44d8-94c0-f7a4ab9c46d7 · outbound

This paper cites Structured variable selection with sparsity-inducing norms,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Structured variable selection with sparsity-inducing norms,

Reference 34

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Observation 2ddfd37a-d267-45dc-ada5-8a4983aac690 · outbound

This paper cites All models are wrong, but many are useful: Learning a variable’s importance by studying an entire class of prediction models simultaneously,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data All models are wrong, but many are useful: Learning a variable’s importance by studying an entire class of prediction models simultaneously,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T04:20:40.263794Z

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Observation 3755a14a-8c4b-4dea-bfba-92c57f63b386 · outbound

This paper cites The many shapley values for model explanation,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data The many shapley values for model explanation,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T04:20:40.293461Z

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Observation 4ffac58a-2f72-428c-a5a6-e896edbe1ef7 · outbound

This paper cites Explaining by removing: A unified framework for model explanation,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Explaining by removing: A unified framework for model explanation,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T04:20:40.328708Z

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Observation 4be48e2a-9a70-43ab-83b2-ef51d6ccc044 · outbound

This paper cites Counterfactual explanations and algorithmic recourses for machine learning: A review,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Counterfactual explanations and algorithmic recourses for machine learning: A review,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T04:20:40.331024Z

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Observation fe80129d-2094-45e8-a5f3-26eff5581740 · outbound

This paper cites Time series classification from scratch with deep neural networks: A strong baseline,.

Adaptive Group-Based Counterfactual Explanations for Time-Series Rehabilitation Data Time series classification from scratch with deep neural networks: A strong baseline,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-07-05T04:20:40.340208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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