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Paper Citation Record · LEDGER

Theory-to-Practice Gap for Neural Networks and Neural Operators

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2503.18219.

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

pith.paper-citation-record.v1
2503.18219 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:51:22.262827Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:19:49.700324Z

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 a9ca1ec1-0446-4bf7-939f-1c1c6c9d39aa · inbound

Computational Math with Neural Networks is Hard cites this paper.

Computational Math with Neural Networks is Hard Theory-to-Practice Gap for Neural Networks and Neural Operators

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T14:51:22.262827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:51:22.262827Z digest=sha256:935971fcbce23d312910024f91641f6930cbfe1a3c09048c1c37c39cc245a521

Observation 919b661d-c03b-4f7c-b2ee-7816d9aa21f7 · inbound

Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning cites this paper.

Principled Approaches for Extending Neural Architectures to Function Spaces for Operator Learning Theory-to-Practice Gap for Neural Networks and Neural Operators

Reference 30

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:19:49.779408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-08-07T04:19:39.494414Z digest=sha256:dc0d98bf8df6a478087eff4385a2872c631d134c5e6685234f9793c97efa7c6e

Observation a060983a-a647-46c2-849d-f1fa87b003ce · inbound

A short tour of operator learning theory: Convergence rates, statistical limits, and open questions cites this paper.

A short tour of operator learning theory: Convergence rates, statistical limits, and open questions Theory-to-Practice Gap for Neural Networks and Neural Operators

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-02T19:58:41.665697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T19:58:41.665697Z digest=sha256:1493b0eb240bb871e7533d5aa4c3e5aaaec5ef8a0a5b66809559c5207fbd522a