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Paper Citation Record · LEDGER

A Unified Replay-based Continuous Learning Framework for Spatio-Temporal Prediction on Streaming Data

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.14999.

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

pith.paper-citation-record.v1
2404.14999 v1

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 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:52:22.341792Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T10:16:15.373445Z

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 e2d16ca6-e8e5-4b29-8c25-2597250a0f65 · inbound

Distribution-aware Online Continual Learning for Urban Spatio-Temporal Forecasting cites this paper.

Distribution-aware Online Continual Learning for Urban Spatio-Temporal Forecasting A Unified Replay-based Continuous Learning Framework for Spatio-Temporal Prediction on Streaming Data

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-12T13:52:22.341792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:52:22.341792Z digest=sha256:e4ee30eca4eabcf785e9e13d790b44145115c57bee5fd3a4151e74a6d94b725c

Observation cf79fa75-832e-4141-a400-f4521122e136 · inbound

Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction cites this paper.

Multi-grained spatial-temporal feature complementarity for accurate online cellular traffic prediction A Unified Replay-based Continuous Learning Framework for Spatio-Temporal Prediction on Streaming Data

Reference 23

Resolution
verified exact
local_arxiv, observed 2026-08-06T10:16:15.382631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-06T10:16:14.960783Z digest=sha256:399428893752a3e112c99f39099f193205e271bb750427c3476b60055960647a