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Paper Citation Record · LEDGER

Order parameters and phase transitions of continual learning in deep neural networks

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2407.10315.

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

pith.paper-citation-record.v1
2407.10315 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T11:19:07.009634Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T22:16:16.805614Z

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 1999f3c4-7eef-4eee-8d95-79d2ad4bc88e · inbound

Adaptive kernel predictors from feature-learning infinite limits of neural networks cites this paper.

Adaptive kernel predictors from feature-learning infinite limits of neural networks Order parameters and phase transitions of continual learning in deep neural networks

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-08T11:19:07.009634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T11:19:07.009634Z digest=sha256:f54cf2d6c644975a77a9e6d78ecbd7239faeb08c5a12a4efcd0f9806e8c37efa

Observation 1a395281-ea69-439a-831d-48ed3f1053fd · inbound

Replay Can Provably Increase Forgetting cites this paper.

Replay Can Provably Increase Forgetting Order parameters and phase transitions of continual learning in deep neural networks

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T10:52:42.115815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:52:42.115815Z digest=sha256:c90988e08b8976649556404fd2f2889542b742f249adf1aa1016b8c47c0241c4

Observation e6c319e7-50f3-4aa4-a436-b51d324a83ea · inbound

A statistical physics framework for optimal learning cites this paper.

A statistical physics framework for optimal learning Order parameters and phase transitions of continual learning in deep neural networks

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T18:39:39.875669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:39:39.875669Z digest=sha256:91200a8354db4f259d06067c76c382b438fcea73c49090b1a8b2275b3fffc97a

Observation 7fdf44c3-d3e9-409c-a058-565d49fcd570 · inbound

Microscopic and collective signatures of feature learning in neural networks cites this paper.

Microscopic and collective signatures of feature learning in neural networks Order parameters and phase transitions of continual learning in deep neural networks

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-05T14:46:58.319445Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:46:58.319445Z digest=sha256:1ae30aa7ba3d85c9b094dfef32fad4b34b95a57c71346bc1a05a4bfb4642bb09

Observation 810a9f18-6ece-4287-bcce-f7a8d7a790f5 · inbound

Continual Learning as a Multiphase Moving-Boundary Problem cites this paper.

Continual Learning as a Multiphase Moving-Boundary Problem Order parameters and phase transitions of continual learning in deep neural networks

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-07-01T22:16:16.807267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-06-28T15:31:19.971397Z digest=sha256:43430ce1b0118123e63858b7b4960d4e92bd7a7788746cec2689ce8e8c709944