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Paper Citation Record · LEDGER

Deep Operator Network Approximation Rates for Lipschitz Operators

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2307.09835.

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

pith.paper-citation-record.v1
2307.09835 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:51:24.049918Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T02:38:53.896470Z

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 9eee41d8-9f11-4bb1-a071-8ff478b1c456 · inbound

Computational Math with Neural Networks is Hard cites this paper.

Computational Math with Neural Networks is Hard Deep Operator Network Approximation Rates for Lipschitz Operators

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T14:51:24.049918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:51:24.049918Z digest=sha256:22998ce46205e9838ac6cb6560dbfc09908203576a2fdab8b8d75b5f233de038

Observation bf03f9d8-9d00-4b7b-acc5-3dc0afc491dc · inbound

Upper Approximation Bounds for Neural Oscillators cites this paper.

Upper Approximation Bounds for Neural Oscillators Deep Operator Network Approximation Rates for Lipschitz Operators

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-17T02:38:53.898205Z

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=arxiv_source observed=2026-05-17T02:36:17.018873Z digest=sha256:994002dccc64650679495813b902f59344d250bf1a4e155458dbbabe7f98e817