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Paper Citation Record · LEDGER

Investigating Forgetting in Pre-Trained Representations Through Continual Learning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2305.05968.

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

pith.paper-citation-record.v1
2305.05968 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 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:55:27.119883Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:09:14.313441Z

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 ade0fdf9-3982-465e-ba09-76d49a61ad9c · inbound

Measuring Representational Shifts in Continual Learning: A Linear Transformation Perspective cites this paper.

Measuring Representational Shifts in Continual Learning: A Linear Transformation Perspective Investigating Forgetting in Pre-Trained Representations Through Continual Learning

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T13:55:27.119883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:55:27.119883Z digest=sha256:a835d87147e9fe92ca059145132002b9c008e6c1adbe1d059a58add4dd18f30b

Observation 3930e000-2abf-4fc2-9d7c-c52df28c125e · inbound

PEFT-MedSAM: Efficient Fine-Tuning of Medical Foundation Models for Explainable Skin Lesion Segmentation cites this paper.

PEFT-MedSAM: Efficient Fine-Tuning of Medical Foundation Models for Explainable Skin Lesion Segmentation Investigating Forgetting in Pre-Trained Representations Through Continual Learning

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-07-04T00:09:14.316012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T21:29:37.875402Z digest=sha256:cbc77d0c681f5d86c273ab4134ae0053278ac6de17d9aeb75407db44c5af21bf

Observation 8efed4fc-1766-4225-aa71-b62835889004 · inbound

Latent-LoRA: Compact Latent-Space Adapters with Gradient-Free Routing for Continual Learning cites this paper.

Latent-LoRA: Compact Latent-Space Adapters with Gradient-Free Routing for Continual Learning Investigating Forgetting in Pre-Trained Representations Through Continual Learning

Reference 3

Resolution
unresolved
no resolver link, observed 2026-07-30T10:55:15.291663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T10:55:15.291663Z digest=sha256:1eb286de0d22666683bd127650807b9b2e4608f50ab93a03f7a7aef9cd4a36e6