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Paper Citation Record · LEDGER

MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2410.15997.

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

pith.paper-citation-record.v1
2410.15997 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T15:37:04.184361Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T18:32:37.368568Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d0f3a689-e232-44d4-8c17-09a9f2da9cc9 · inbound

DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting cites this paper.

DUET: Dual Clustering Enhanced Multivariate Time Series Forecasting MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-11T15:37:04.184361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:37:04.184361Z digest=sha256:ef6103102365906deb8e34c5890ed29faaa891fbf8547d974704a4b30a363525

Observation d8b19610-6f6b-4f10-bca1-5ca1feef3fec · inbound

EasyTime: Time Series Forecasting Made Easy cites this paper.

EasyTime: Time Series Forecasting Made Easy MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-11T05:24:50.707279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T05:24:50.707279Z digest=sha256:e23def4ffffafd320ec13f7bb381039694825762e2b583500c9b65961af3c1f7

Observation 11fff1c1-4332-4c1a-9215-3fa0401301b9 · inbound

IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning cites this paper.

IMDPrompter: Adapting SAM to Image Manipulation Detection by Cross-View Automated Prompt Learning MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast

Reference 2006

Resolution
unresolved
no resolver link, observed 2026-08-09T12:09:14.548357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T12:09:14.548357Z digest=sha256:aed9077aa4b1653eb7955e1e81c094b3ebdc5fe88e68e9b1220837dd2c027859

Observation 48d04535-821d-4314-9082-9356dca238a1 · inbound

$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting cites this paper.

$K^2$VAE: A Koopman-Kalman Enhanced Variational AutoEncoder for Probabilistic Time Series Forecasting MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-07T13:02:34.667512Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:02:34.667512Z digest=sha256:ff8b445bc7d8c063ec3fda56579afe964fb7ba6983e17f0c79934ec6af1f6707

Observation 6d8eb5a6-9a0a-4fc6-a493-2856fcf84648 · inbound

FADE: Adversarial Concept Erasure in Flow Models cites this paper.

FADE: Adversarial Concept Erasure in Flow Models MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-06T17:00:00.815879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:00:00.815879Z digest=sha256:e2984f5db942b8059e1a5e074bc326b73c047e9ceaa0a80f959723200a35ef76

Observation ab49a391-9378-4db2-9ed3-3b12c68b0991 · inbound

Artificial Intelligence-Based Multiscale Temporal Modeling for Anomaly Detection in Cloud Services cites this paper.

Artificial Intelligence-Based Multiscale Temporal Modeling for Anomaly Detection in Cloud Services MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-05T18:32:37.431199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T18:32:32.414106Z digest=sha256:69af2945a469d037d84018ad3250690a458961d08c812b57c12ecf46f53c1dcc

Observation 74217801-08e8-488e-997b-0d6a4df342ad · inbound

Enhancing Irregular Time Series Forecasting with Continuous-Time Modeling Framework cites this paper.

Enhancing Irregular Time Series Forecasting with Continuous-Time Modeling Framework MultiRC: Joint Learning for Time Series Anomaly Prediction and Detection with Multi-scale Reconstructive Contrast

Reference 97

Resolution
unresolved
no resolver link, observed 2026-07-31T19:49:55.895834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T19:49:55.895834Z digest=sha256:b7f649bea628d8a97bd804fcf5e3c68c0ec088db02d85c8b00fe7d18fff3885d