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Paper Citation Record · LEDGER

Deep learning for time series classification

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2010.00567.

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

pith.paper-citation-record.v1
2010.00567 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T10:15:33.029952Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T06:25:07.717413Z

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 ed17d033-9252-4fc9-ba6f-e1fd72b958c0 · inbound

MoSSDA: A Semi-Supervised Domain Adaptation Framework for Multivariate Time-Series Classification using Momentum Encoder cites this paper.

MoSSDA: A Semi-Supervised Domain Adaptation Framework for Multivariate Time-Series Classification using Momentum Encoder Deep learning for time series classification

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T10:15:33.029952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T10:15:33.029952Z digest=sha256:ec225007468290a498639ea73b20910ab824bb661c0f5bf3be6c956fc8e30802

Observation 9c33853b-659e-4754-b548-1f28a0873bd0 · inbound

A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks cites this paper.

A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks Deep learning for time series classification

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-15T00:13:21.722692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T00:11:43.037956Z digest=sha256:8bcd25374b8c601c583c7d39abef09b911dfcb327c992cc2bc15c6a4f3078084

Observation 28f5b45e-eac8-4ab1-9945-3fe04575d5ab · inbound

A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks cites this paper.

A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks Deep learning for time series classification

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-15T06:25:07.720064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T06:21:42.394251Z digest=sha256:08ac9d1ba4543fcc913ae6fae21bd89fdf7459beb7d3b634ebc211fb63eab114