Pith. sign in

Paper Citation Record · LEDGER

T-Rep: Representation Learning for Time Series using Time-Embeddings

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2310.04486.

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

pith.paper-citation-record.v1
2310.04486 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:13:41.611073Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3c06a19f-62cb-40e6-9485-69073d65973d · inbound

Universal Time-Series Representation Learning: A Survey cites this paper.

Universal Time-Series Representation Learning: A Survey T-Rep: Representation Learning for Time Series using Time-Embeddings

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-24T04:28:53.441632Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-24T04:26:45.527625Z digest=sha256:f0459c9cad076247af39b831b4493213f1dad9a5d10d250b310ac79408faa9c0

Observation 65f7f3e7-ee3d-4699-8db3-143f603d98c1 · inbound

MFF-FTNet: Multi-scale Feature Fusion across Frequency and Temporal Domains for Time Series Forecasting cites this paper.

MFF-FTNet: Multi-scale Feature Fusion across Frequency and Temporal Domains for Time Series Forecasting T-Rep: Representation Learning for Time Series using Time-Embeddings

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T12:13:41.611073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:13:41.611073Z digest=sha256:b9cf764bc5ace40a668c238d72ef820f79cf75f89b64fb553ed95d18d588420d

Observation 0c0d4a4a-a125-4018-b1a3-f6338c47f2e9 · inbound

CORAL: Concept Drift Representation Learning for Co-evolving Time-series cites this paper.

CORAL: Concept Drift Representation Learning for Co-evolving Time-series T-Rep: Representation Learning for Time Series using Time-Embeddings

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-10T22:38:41.138671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T22:38:41.138671Z digest=sha256:8447fe182d637b03c4768df55b5ccbc4999c1f286580777ec7dbd9f869ea76a1

Observation a4a4b620-9cfe-4251-8df3-861cb80a66e9 · inbound

Enhancing Low-Cost Video Editing with Lightweight Adaptors and Temporal-Aware Inversion cites this paper.

Enhancing Low-Cost Video Editing with Lightweight Adaptors and Temporal-Aware Inversion T-Rep: Representation Learning for Time Series using Time-Embeddings

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T21:35:41.927342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:35:41.927342Z digest=sha256:071382f7311878a33e11db391604b632872c9c6b0564a417b0ee02cb06f41bb4

Observation b02d3140-f9f3-4665-afa1-af49f65848df · inbound

Path Generation and Evaluation in Video Games: A Nonparametric Statistical Approach cites this paper.

Path Generation and Evaluation in Video Games: A Nonparametric Statistical Approach T-Rep: Representation Learning for Time Series using Time-Embeddings

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T11:07:28.200387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:07:28.200387Z digest=sha256:88624b19cf040b2d4391ff3fcab9ba0474a87864d77d17c73a527553895ec983

Observation ba0e64b7-66ff-4e53-bb8b-3292630407be · inbound

Leveraging External Factors in Household-Level Electrical Consumption Forecasting using Hypernetworks cites this paper.

Leveraging External Factors in Household-Level Electrical Consumption Forecasting using Hypernetworks T-Rep: Representation Learning for Time Series using Time-Embeddings

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T00:23:46.230290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:23:46.230290Z digest=sha256:2d2212dbd6db7c479beb94367880b5e7593eea9b499db247e3c9cc95a1b3ffda

Observation adfeca4c-9989-47e4-9a39-10f575fac1e2 · inbound

Fed-REACT: Federated Representation Learning for Heterogeneous and Evolving Data cites this paper.

Fed-REACT: Federated Representation Learning for Heterogeneous and Evolving Data T-Rep: Representation Learning for Time Series using Time-Embeddings

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-04T22:44:39.809244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T22:44:39.809244Z digest=sha256:45500b4038c8e23664b77bf30ee85ed5e8e48fe0e36a670099dc8d95c3540eb5

Observation 3884efa7-9e30-4bea-a726-2325ff6ceb24 · inbound

Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection cites this paper.

Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection T-Rep: Representation Learning for Time Series using Time-Embeddings

Reference 197

Resolution
verified exact
arxiv_id, observed 2026-06-26T00:28:42.775402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-26T00:27:41.609691Z digest=sha256:39a899b75973e5270273f4ba43fa94ca7f0e876a529feaece6b84c20786bf416