Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Neural network-based CUSUM for online change-point detection
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2210.17312.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T17:31:24.178821Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T08:57:47.821105Z
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 a32c5701-c192-4ea8-9e8f-ad0d09fc3965 · inbound
Detectability Thresholds for Network Attacks on Static Graphs and Temporal Networks: Information-Theoretic Limits and Nearly-Optimal Tests cites this paper.
Detectability Thresholds for Network Attacks on Static Graphs and Temporal Networks: Information-Theoretic Limits and Nearly-Optimal Tests Neural network-based CUSUM for online change-point detection
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T17:31:24.178821Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b5022f93-6a13-4b80-9bb8-949ec62094b4 · inbound
Resilience Characterization of AI-Native Wireless Receivers via Persistent Homology cites this paper.
Resilience Characterization of AI-Native Wireless Receivers via Persistent Homology Neural network-based CUSUM for online change-point detection
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-25T03:00:15.903458Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2f669cce-0cb2-412a-b130-1484ea14a167 · inbound
Bernoulli CUSUM and Bayes-Optimal Detection Ceilings for Trust Fraud in Sparse Rating Networks cites this paper.
Bernoulli CUSUM and Bayes-Optimal Detection Ceilings for Trust Fraud in Sparse Rating Networks Neural network-based CUSUM for online change-point detection
Reference 23
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T09:26:51.503248Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0355bbf7-ff5a-4fd7-a477-96986151e73f · inbound
Online change point detection under heavy-tailedness and contamination cites this paper.
Online change point detection under heavy-tailedness and contamination Neural network-based CUSUM for online change-point detection
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T03:47:35.945039Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0fabb309-f7ec-45c0-9253-1c2d1c5373c7 · inbound
Quickest Detection of Hallucination Onset: Delay Bounds and Learned CUSUM Statistics cites this paper.
Quickest Detection of Hallucination Onset: Delay Bounds and Learned CUSUM Statistics Neural network-based CUSUM for online change-point detection
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T08:57:47.822744Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.