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Paper Citation Record · LEDGER

A Unified Algebraic Perspective on Lipschitz Neural Networks

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2303.03169.

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

pith.paper-citation-record.v1
2303.03169 v2

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 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:04:07.875868Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T05:56:26.931831Z

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 a74c43fa-bd85-4f8c-ad7a-3f3de546ec9e · inbound

Inference Privacy: Properties and Mechanisms cites this paper.

Inference Privacy: Properties and Mechanisms A Unified Algebraic Perspective on Lipschitz Neural Networks

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-12T11:04:07.875868Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T11:04:07.875868Z digest=sha256:5eb531bbb1139111ac9eff165e2006d975d36ee55194691b4d05ae63e77de819

Observation 29b57bf0-c1cd-4c80-9c41-3d74602c1dba · inbound

Hierarchical End-to-End Taylor Bounds for Complete Neural Network Verification cites this paper.

Hierarchical End-to-End Taylor Bounds for Complete Neural Network Verification A Unified Algebraic Perspective on Lipschitz Neural Networks

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:56:26.959037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-12T04:46:50.715051Z digest=sha256:ecfa51a22fbff1be3b9d83fa446550f37a0feb2aca0461564ace1735797f3799