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Paper Citation Record · LEDGER

Penalising the biases in norm regularisation enforces sparsity

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2303.01353.

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

pith.paper-citation-record.v1
2303.01353 v4

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T01:22:48.978471Z

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 d2232cc5-c5c9-4ecc-8351-1df45a1a1a78 · inbound

Elliptic Regularity Theory in Barron Spaces and Applications to the Deep Ritz Method cites this paper.

Elliptic Regularity Theory in Barron Spaces and Applications to the Deep Ritz Method Penalising the biases in norm regularisation enforces sparsity

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-07-31T01:28:49.704555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T01:28:49.704555Z digest=sha256:6126fe191258edfe5a840b8aa954042fd0cede7c083171de50f565104581fc46

Observation 458a7b25-9ef4-4af6-b1fc-5af5600c1866 · inbound

The Barron-Lipschitz Energy Gap and Depth Separation Phenomena in Scientific Machine Learning cites this paper.

The Barron-Lipschitz Energy Gap and Depth Separation Phenomena in Scientific Machine Learning Penalising the biases in norm regularisation enforces sparsity

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-01T01:22:48.978471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T01:22:48.978471Z digest=sha256:bf5e80c27ebcf8f39a8496874a7d9646eff788f5a7630b9171470fb16bd877a2