Pith. sign in

Paper Citation Record · LEDGER

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process

As of 18 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2507.10632.

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

pith.paper-citation-record.v1
2507.10632 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:46:01.666201Z

measured 24 of 24 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 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

24 of 24 outbound references displayed

  • verified exact4
  • verified fuzzy16
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e71e1a89-87a5-475d-a084-53900004baaf · outbound

This paper cites Joint modeling of multiple related time series via the beta process,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Joint modeling of multiple related time series via the beta process,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:04.576390Z

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=2026-08-06T17:45:59.617898Z digest=sha256:d4c7768dc4ada8eba62dff99df703f33db8387e12c346a436eb4658fc966ce1a

Observation 58063204-76dd-42dc-b34d-107e8a4f2a27 · outbound

This paper cites Autoplait: Automatic mining of co-evolving time sequences,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Autoplait: Automatic mining of co-evolving time sequences,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:04.477566Z

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=2026-08-06T17:45:59.696471Z digest=sha256:6977dea4e3b8c13bd0500795b6aab28ff8cdcc7841e3da8d579fc23dfa51d9dd

Observation c9f3b1ab-8b1c-46e5-a63e-b9e494778370 · outbound

This paper cites Unsupervised learning and segmentation of complex activities from video,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Unsupervised learning and segmentation of complex activities from video,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:04.361024Z

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=2026-08-06T17:45:59.825597Z digest=sha256:7928454b65bc491faf8a0e0e2f4b35c927f4933ac93f156d99fec6876ab8486f

Observation 62223f89-aa99-458e-9ed0-038858df03e3 · outbound

This paper cites Weakly supervised action labeling in videos under ordering constraints,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Weakly supervised action labeling in videos under ordering constraints,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:04.267445Z

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=2026-08-06T17:45:59.929070Z digest=sha256:da1dc524cca6310dc1b513e23d3b65e60111469fcfa9d9a8ae04b1a0fc711844

Observation 1d28bd33-39e6-439c-b4a8-9a9502fb88cd · outbound

This paper cites Connectionist temporal modeling for weakly supervised action labeling,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Connectionist temporal modeling for weakly supervised action labeling,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:04.081936Z

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=2026-08-06T17:46:00.054732Z digest=sha256:996e645c4044f66af8f02e7cdec2e6e15a249e4301f144e58e95b78d8f0d9412

Observation 8e4dc1ce-96ee-4bea-aa29-2812b6e925b8 · outbound

This paper cites Weakly supervised action learning with rnn based fine-to-coarse modeling,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Weakly supervised action learning with rnn based fine-to-coarse modeling,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:03.967216Z

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=2026-08-06T17:46:00.187905Z digest=sha256:2af99212c17ddb9c5632784bc3f9699c5d55f841b799772092142e1f6551101b

Observation f478e2fc-0a29-4a32-b441-d30b10350af9 · outbound

This paper cites Segmenting continuous motions with hidden semi-markov models and gaussian processes,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Segmenting continuous motions with hidden semi-markov models and gaussian processes,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:03.842805Z

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=2026-08-06T17:46:00.277291Z digest=sha256:e9ac0a58ea9a30f55865b356b200d150d5a7e003e7c4cce34d10d5c2df1bdbb0

Observation 9bec6024-8726-45b7-b9e5-4059d5a32f17 · outbound

This paper cites Unsupervised work behavior analysis using hierarchical probabilistic segmentation,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Unsupervised work behavior analysis using hierarchical probabilistic segmentation,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:03.671331Z

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=2026-08-06T17:46:00.336380Z digest=sha256:8d400b7c8dea8f75d9e48e23717a9fabcc63472dd6b703972f9c6352c87818b8

Observation 2ea73286-8621-4fb4-ae2d-9ad32f2273cd · outbound

This paper cites Unsupervised decom- position of natural monkey behavior into a sequence of motion motifs,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Unsupervised decom- position of natural monkey behavior into a sequence of motion motifs,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:03.260028Z

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=2026-08-06T17:46:00.430407Z digest=sha256:dc8011058babd6cc9917dc4274f1ab293546f25b2a83efb8814d1f07e8131d4f

Observation 0b068f89-44c6-43d8-affb-49426f58727d · outbound

This paper cites Emergence of continuous signals as shared symbols through emergent communication,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Emergence of continuous signals as shared symbols through emergent communication,

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:03.125184Z

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=2026-08-06T17:46:00.524967Z digest=sha256:52f1a2854153d4c8536daee81ad7c87cf06711f8035e71a11214808cbd4bdc25

Observation b27e5544-c244-47fe-b333-e2ab25063225 · outbound

This paper cites Multi-step motion learning by combining learning-from-demonstration and policy-search,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Multi-step motion learning by combining learning-from-demonstration and policy-search,

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T17:46:00.597181Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:46:00.597181Z digest=sha256:fbf520c907db7e4153e5931236c46128a45118bb9baba527ce7561576c3224c1

Observation 83a45e37-a113-4a3e-acfd-3de18daaabac · outbound

This paper cites Random features for large-scale kernel machines,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Random features for large-scale kernel machines,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:03.002084Z

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=2026-08-06T17:46:00.690731Z digest=sha256:6ce58f6fe708b77c4fa7a91e7b1516d890dc2d5cb75c268ab8315a18f74048b2

Observation 349d09d2-61cd-4870-b68f-da6edffd78e6 · outbound

This paper cites Fine- grained action recognition in assembly work scenes by drawing attention to the hands,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Fine- grained action recognition in assembly work scenes by drawing attention to the hands,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:02.880012Z

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=2026-08-06T17:46:00.752092Z digest=sha256:e3ba12f6d73c1a1f4689d21efdf94cfa2bf9177b515801e5205a7d93896cda0f

Observation c6d02dad-caea-4e3c-b6aa-2e2c0e9f215e · outbound

This paper cites Tempo- ral convolutional networks for action segmentation and detection,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Tempo- ral convolutional networks for action segmentation and detection,

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T17:46:00.827358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:46:00.827358Z digest=sha256:f41d59aaabca025f944c9872847c778783d93593fc3a7e6cfabf57373d8d9e71

Observation 57111155-64f1-4221-835e-4ee92d302ac0 · outbound

This paper cites End-to-end learning of action detection from frame glimpses in videos,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process End-to-end learning of action detection from frame glimpses in videos,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:02.772639Z

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=2026-08-06T17:46:00.906318Z digest=sha256:e0560f50e891e1f8aea26d411c1418cb0f9d2ffde7b251f2ad0298e25d2958d6

Observation 77782985-0a12-45f4-a680-b17dce5c6eab · outbound

This paper cites Spatio-temporal channel correlation networks for action classification,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Spatio-temporal channel correlation networks for action classification,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:02.660178Z

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=2026-08-06T17:46:00.977238Z digest=sha256:c6814679695b6063f84e869d2b7d544d82f5cba0b6bd3008df6cc56966e5c8dc

Observation 28ba5618-3826-4d9c-8477-a0d4c763f8a5 · outbound

This paper cites Temporal Segment Transformer for Action Segmentation.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Temporal Segment Transformer for Action Segmentation

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:46:02.197758Z

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=2026-08-06T17:46:01.062929Z digest=sha256:eea4116644f9bd056d6b646f3923197d1324cce0c34a53fb2de21dfbdac7add5

Observation b45d3fbe-d455-4043-8fe8-7e45e41c0aa3 · outbound

This paper cites Transformers in Time Series: A Survey.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Transformers in Time Series: A Survey

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T17:46:01.137428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:46:01.137428Z digest=sha256:58779ab10647d61caa690b28e601df45be5528b811d8ccdcae4af203b0255f48

Observation 1ce2bffb-043a-438f-b519-d2e066a6f176 · outbound

This paper cites Long-term Forecasting with TiDE: Time-series Dense Encoder.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Long-term Forecasting with TiDE: Time-series Dense Encoder

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T17:46:01.214106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:46:01.214106Z digest=sha256:141c38501d5583a62e95574b0e0991a6cdb3cd2471d5f4aca969aab2ed727179

Observation bb7df3c1-2163-4ef9-8c61-7b3f675fbc49 · outbound

This paper cites Sequence pattern extraction by segmenting time series data using gp-hsmm with hierarchical dirichlet process,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Sequence pattern extraction by segmenting time series data using gp-hsmm with hierarchical dirichlet process,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:02.517790Z

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=2026-08-06T17:46:01.311124Z digest=sha256:b070cba8d132957a2eaca05ab2df7f5fb6a364660bf9379f8e1b71351617dd01

Observation 4077ca5f-2fad-4b64-a01e-11a321ab7eb7 · outbound

This paper cites Bayesian Non-linear Latent Variable Modeling via Random Fourier Features.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Bayesian Non-linear Latent Variable Modeling via Random Fourier Features

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:46:02.073219Z

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=2026-08-06T17:46:01.398281Z digest=sha256:099299cf84435cba0f02cfa8143af622067335d9e9f9a86ef3b4452741dd51a2

Observation d7f35a14-4a48-42b7-94b6-9276d5cd05ce · outbound

This paper cites Preventing Model Collapse in Gaussian Process Latent Variable Models.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Preventing Model Collapse in Gaussian Process Latent Variable Models

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:46:01.955928Z

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=2026-08-06T17:46:01.493178Z digest=sha256:f084bd8bfa19097df58e86eb8b2c6d3d1ff3b64ab52207686c99db0cb422f8bf

Observation c77fe043-8e54-47da-9602-53139c907e28 · outbound

This paper cites Scalable Hybrid HMM with Gaussian Process Emission for Sequential Time-series Data Clustering.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process Scalable Hybrid HMM with Gaussian Process Emission for Sequential Time-series Data Clustering

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-06T17:46:01.814367Z

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=2026-08-06T17:46:01.589402Z digest=sha256:266748729376986de917a4eb6c7d0cabd9b2591c3f363ac1734635b4e427cae7

Observation 5c05feff-a567-4945-ab01-becf60cf5b5b · outbound

This paper cites A high-speed method of segmenting human body motions with regular time interval sensor data based on gaussian process hidden semi- markov model,.

Scalable Unsupervised Segmentation via Random Fourier Feature-based Gaussian Process A high-speed method of segmenting human body motions with regular time interval sensor data based on gaussian process hidden semi- markov model,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:46:02.380788Z

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=2026-08-06T17:46:01.666201Z digest=sha256:854f4b659d29231dc17876038d6b34bfd5e0beef4be83d12d864a3fd991cd569

Pith citing papers

No inbound Pith citation observations are available.