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Paper Citation Record · LEDGER

Catastrophic Forgetting in Deep Learning: A Comprehensive Taxonomy

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2312.10549.

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

pith.paper-citation-record.v1
2312.10549 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 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T15:53:59.291965Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T00:13:39.398724Z

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 e78fa806-6cb6-462d-ae50-ff92476b0562 · inbound

Preserving Knowledge in Large Language Model with Model-Agnostic Self-Decompression cites this paper.

Preserving Knowledge in Large Language Model with Model-Agnostic Self-Decompression Catastrophic Forgetting in Deep Learning: A Comprehensive Taxonomy

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-24T00:13:39.401823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-24T00:09:52.093810Z digest=sha256:71d6aafa2a5be962236fb209e0afb8cb414aeeffdeb224085cd94a0d5b316603

Observation cc4a53db-0e7d-49c5-b0f9-f4d2945e8c09 · inbound

Efficient Unlearning through Maximizing Relearning Convergence Delay cites this paper.

Efficient Unlearning through Maximizing Relearning Convergence Delay Catastrophic Forgetting in Deep Learning: A Comprehensive Taxonomy

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:30:56.600414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T16:37:24.974659Z digest=sha256:e6e3d87267bf0e20a0c39872e03b11552dc17ca68ac84160fa87dc2dca76137a

Observation c6e62dc0-2ed3-4ca5-a3de-f7aa27c36797 · inbound

A Continual Validation, Updating, and Decision-Making Framework for Self-Adaptive Digital Twins via Robust Model Predictive Control: A Case Study in Additive Manufacturing cites this paper.

A Continual Validation, Updating, and Decision-Making Framework for Self-Adaptive Digital Twins via Robust Model Predictive Control: A Case Study in Additive Manufacturing Catastrophic Forgetting in Deep Learning: A Comprehensive Taxonomy

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-01T15:53:59.291965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T15:53:59.291965Z digest=sha256:6fdd5a4a6ae2da1cd1773b5c2b92ee91b9df65fa19c642a1e5d9b9e84ac0971b