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Paper Citation Record · LEDGER

Incorporating Transformer and LSTM to Kalman Filter with EM algorithm for state estimation

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2105.00250.

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

pith.paper-citation-record.v1
2105.00250 v2

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 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:41:25.277165Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T21:16:14.097688Z

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 aeece236-c69e-40b5-bad1-406f4e76b0e9 · inbound

DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking cites this paper.

DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking Incorporating Transformer and LSTM to Kalman Filter with EM algorithm for state estimation

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-15T20:41:25.277165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:41:25.277165Z digest=sha256:6ea80815b3a51596984582c6817a8793428bfaab863769c76c63a4713ec07b3c

Observation 1997be2b-59b4-4a96-ac3e-030d955ca20b · inbound

ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection cites this paper.

ChronosAD: Leveraging Time Series Foundation Models for Accurate Anomaly Detection Incorporating Transformer and LSTM to Kalman Filter with EM algorithm for state estimation

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-07-01T21:16:14.099384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-28T17:15:38.257093Z digest=sha256:770ac88e2981ad4cb6a4596d648d32a37aec7955e0aaa174d3ff43915254d13b