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Paper Citation Record · LEDGER

Continual Learning Should Move Beyond Incremental Classification

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.11927.

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

pith.paper-citation-record.v1
2502.11927 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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:34:33.780147Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T23:24:01.940185Z

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 d061e6bb-ad99-42fa-9e0b-ab5df34f23b3 · inbound

Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study cites this paper.

Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study Continual Learning Should Move Beyond Incremental Classification

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-16T12:34:33.780147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:34:33.780147Z digest=sha256:4a7835ab66aab79b017bb9d2842f8de4aa763fad9b728608d279b392ea92449a

Observation 1d997292-9db9-4c9f-ba24-4236c4a73ddf · inbound

Forgetting in Language Models: Capacity, Optimization, and Self-Generated Replay cites this paper.

Forgetting in Language Models: Capacity, Optimization, and Self-Generated Replay Continual Learning Should Move Beyond Incremental Classification

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-06-29T23:24:01.941843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-29T23:15:45.174086Z digest=sha256:2a8d8c9f5ffea41ce231706c51012f562d18a85b8bd13e115661515a3c5bbc7c