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Paper Citation Record · LEDGER

Scalable Approximate Optimal Diagonal Preconditioning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.15594.

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

pith.paper-citation-record.v1
2312.15594 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:10:09.165212Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:38:00.445228Z

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 e3cc866c-4d62-4b8a-b00e-b6e99c6b6d3f · inbound

Gradient Methods with Online Scaling Part I. Theoretical Foundations cites this paper.

Gradient Methods with Online Scaling Part I. Theoretical Foundations Scalable Approximate Optimal Diagonal Preconditioning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-07T13:10:09.165212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:09.165212Z digest=sha256:99ecd1cb10ad4925844fe4f9676cc31ce922dee8affa85dd69fe92b0576771ed

Observation c6e8a0f4-c70b-40bd-91e2-c461c998438c · inbound

Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification cites this paper.

Interior-Point Vanishing Problem in Semidefinite Relaxations for Neural Network Verification Scalable Approximate Optimal Diagonal Preconditioning

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:38:00.452826Z

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=2026-08-07T04:38:00.039861Z digest=sha256:e840d594c7aab3ce9a6b07c4b96dede58bff56dee8bbab4b3e2c3e8c46ea1862