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Paper Citation Record · LEDGER

SVFit: Parameter-Efficient Fine-Tuning of Large Pre-Trained Models Using Singular Values

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.05926.

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

pith.paper-citation-record.v1
2409.05926 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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T06:48:16.041090Z

measured 0 of 1 external citation measurements

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

Source: cited_works

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 2b0eeedb-b04c-4eb3-b937-e97b915835b4 · inbound

Quantifying the Uncertainty of Foundation Models with Singular Value Ensembles cites this paper.

Quantifying the Uncertainty of Foundation Models with Singular Value Ensembles SVFit: Parameter-Efficient Fine-Tuning of Large Pre-Trained Models Using Singular Values

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-03T06:48:16.041090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T06:48:16.041090Z digest=sha256:a4654d8b8bfc2f7c77a28673d23b2bf2d606d215915b3f646d03135fb5cb7f0e

Observation 16364baa-ecb8-4c91-9946-be05fc7fd87b · inbound

Localized LoRA-MoE: Block-wise Low-Rank Experts With Adaptive Routing cites this paper.

Localized LoRA-MoE: Block-wise Low-Rank Experts With Adaptive Routing SVFit: Parameter-Efficient Fine-Tuning of Large Pre-Trained Models Using Singular Values

Reference 21

Resolution
unresolved
no resolver link, observed 2026-07-11T08:38:02.220727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T08:38:02.220727Z digest=sha256:f81c67b5d2c5288370864ea80284d5d11d53db5b0b5cafb6e1c288dd97b9f46a