Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:39:36.732828Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2506.21249.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T22:39:36.732828Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
64 of 64 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 88c911cb-57da-4b25-a449-7e380f22bd0a · outbound
Temporal Rate Reduction Clustering for Human Motion Segmentation A percep- tual prediction framework for self supervised event segmen- tation
Reference 1
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Temporal Rate Reduction Clustering for Human Motion Segmentation Unsu- pervised learning from narrated instruction videos
Reference 2
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Temporal Rate Reduction Clustering for Human Motion Segmentation Dual-side auto-encoder for high-dimensional time series seg- mentation
Reference 3
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Reference 4
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Temporal Rate Reduction Clustering for Human Motion Segmentation Image clustering via the principle of rate reduction in the age of pretrained models
Reference 5
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Temporal Rate Reduction Clustering for Human Motion Segmentation Learning event rep- resentations for temporal segmentation of image sequences by dynamic graph embedding
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Temporal Rate Reduction Clustering for Human Motion Segmentation Tempo- ral action segmentation: An analysis of modern techniques
Reference 10
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Temporal Rate Reduction Clustering for Human Motion Segmentation Haeffele
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Temporal Rate Reduction Clustering for Human Motion Segmentation Fast and unsupervised action boundary detection for action seg- mentation
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Reference 13
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Temporal Rate Reduction Clustering for Human Motion Segmentation Log- det heuristic for matrix rank minimization with applications to hankel and euclidean distance matrices
Reference 14
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Observation 48725c9d-e163-45ae-96fe-b89c01563ab2 · outbound
Temporal Rate Reduction Clustering for Human Motion Segmentation The visual analysis of human movement: A survey
Reference 15
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Temporal Rate Reduction Clustering for Human Motion Segmentation Probabilistic tem- poral subspace clustering
Reference 16
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Observation 92f27136-2363-4295-ba98-59f650333259 · outbound
Temporal Rate Reduction Clustering for Human Motion Segmentation Actions as space-time shapes.IEEE Trans- actions on Pattern Analysis and Machine Intelligence , 29 (12):2247–2253, 2007
Reference 17
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Observation 2ff83e08-8f01-414c-a5c7-86789dfb3c81 · outbound
Temporal Rate Reduction Clustering for Human Motion Segmentation A cri- tique of self-expressive deep subspace clustering
Reference 18
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Temporal Rate Reduction Clustering for Human Motion Segmentation Sequential max-margin event detectors
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Temporal Rate Reduction Clustering for Human Motion Segmentation Towards understanding action recognition
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Temporal Rate Reduction Clustering for Human Motion Segmentation Recognizing hu- man actions by learning and matching shape-motion proto- type trees
Reference 21
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Temporal Rate Reduction Clustering for Human Motion Segmentation The language of actions: Recovering the syntax and semantics of goal- directed human activities
Reference 22
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Observation cb8f5716-eb20-463b-9dc0-4c46810d4f8e · outbound
Temporal Rate Reduction Clustering for Human Motion Segmentation Unsupervised learning of action classes with contin- uous temporal embedding
Reference 23
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Temporal Rate Reduction Clustering for Human Motion Segmentation Learning realistic human actions from movies
Reference 24
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Temporal Rate Reduction Clustering for Human Motion Segmentation Structured sparse subspace clustering: A joint affinity learning and sub- space clustering framework
Reference 25
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Temporal Rate Reduction Clustering for Human Motion Segmentation Deeper insights into graph convolutional networks for semi-supervised learn- ing
Reference 26
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Temporal Rate Reduction Clustering for Human Motion Segmentation Temporal subspace clus- tering for human motion segmentation
Reference 27
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Observation dc8f245d-ff49-40ca-83e1-0975865a0203 · outbound
Temporal Rate Reduction Clustering for Human Motion Segmentation Robust subspace clustering with indepen- dent and piecewise identically distributed noise modeling
Reference 28
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Observation d0999bb5-32c9-4108-b56f-9bfd390cf694 · outbound
Temporal Rate Reduction Clustering for Human Motion Segmentation Neural Manifold Clustering and Embedding
Reference 29
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Temporal Rate Reduction Clustering for Human Motion Segmentation Robust sub- space segmentation by low-rank representation
Reference 30
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Reference 31
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Temporal Rate Reduction Clustering for Human Motion Segmentation Self-supervised learning via maximum entropy coding
Reference 32
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Temporal Rate Reduction Clustering for Human Motion Segmentation Robust and efficient subspace segmentation via least squares regression
Reference 33
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Observation daf86759-d44f-4f61-8871-f959e6f6f52c · outbound
Temporal Rate Reduction Clustering for Human Motion Segmentation Seg- mentation of multivariate mixed data via lossy coding and compression
Reference 34
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Reference 35
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Temporal Rate Reduction Clustering for Human Motion Segmentation A survey of advances in vision-based human motion capture and analysis
Reference 36
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Reference 37
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Reference 38
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Reference 47
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Reference 48
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Reference 49
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Reference 50
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Reference 51
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Reference 52
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Reference 53
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Reference 58
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Reference 59
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Reference 60
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Reference 61
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Reference 62
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Reference 63
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Reference 64
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No inbound Pith citation observations are available.