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Paper Citation Record · LEDGER

Explaining Deep Classification of Time-Series Data with Learned Prototypes

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1904.08935.

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

pith.paper-citation-record.v1
1904.08935 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T18:48:44.191874Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T13:49:32.039961Z

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 06f911f7-5e26-4ac5-a438-4cf6ac7d8293 · inbound

Multi-Stage Prototype Learning for Interpretable Time Series Classification cites this paper.

Multi-Stage Prototype Learning for Interpretable Time Series Classification Explaining Deep Classification of Time-Series Data with Learned Prototypes

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-24T13:49:32.053519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-05-24T13:47:51.707080Z digest=sha256:f7686eb749d26028fa48b1c5327ee0758be5d345345f4e841b0e70f5c309312d

Observation f0684a9d-4eea-45b0-bcd5-6d00d1cff0ad · inbound

When, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregate cites this paper.

When, How Long and How Much? Interpretable Neural Networks for Time Series Regression by Learning to Mask and Aggregate Explaining Deep Classification of Time-Series Data with Learned Prototypes

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-03T18:48:44.191874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T18:48:44.191874Z digest=sha256:6336271b54c8ad355c0a7de1771521654c189a6cd81cf388371f164d393aae8c