Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.03140.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T22:56:10.526439Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T08:26:16.586538Z
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 c512a89d-2b36-455f-976c-116413f933ab · inbound
FIC-TSC: Learning Time Series Classification with Fisher Information Constraint cites this paper.
FIC-TSC: Learning Time Series Classification with Fisher Information Constraint TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T22:56:10.526439Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c2656ddd-b061-4465-aa1a-e55f77e14ef0 · inbound
Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series cites this paper.
Prototype-Guided Classification Sub-Task Decoupling Framework: Enhancing Generalization and Interpretability for Multivariate Time Series TimeMIL: Advancing Multivariate Time Series Classification via a Time-aware Multiple Instance Learning
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T08:26:16.592048Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.