Paper Citation Record · LEDGER

Neural networks meet hyperelasticity: A monotonic approach

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2501.02670.

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

pith.paper-citation-record.v1
2501.02670 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:01:31.562671Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T05:56:40.790522Z

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 750dc67b-0ec1-41d9-b55c-a4af4c4e421e · inbound

Biaxial characterization of soft elastomers: experiments and data-adaptive configurational forces for fracture cites this paper.

Biaxial characterization of soft elastomers: experiments and data-adaptive configurational forces for fracture Neural networks meet hyperelasticity: A monotonic approach

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-07T14:01:31.562671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 270af796-c9d4-4294-9880-04354cb3d760 · inbound

Towards Rapid Constitutive Model Discovery from Multi-Modal Data: Physics Augmented Finite Element Model Updating (paFEMU) cites this paper.

Towards Rapid Constitutive Model Discovery from Multi-Modal Data: Physics Augmented Finite Element Model Updating (paFEMU) Neural networks meet hyperelasticity: A monotonic approach

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-11T06:15:56.661724Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f93bc3ef-1c33-4444-b0c0-b31dd3b40f19 · inbound

Data-adaptive spline surfaces for non-separable hyperelastic energy functions cites this paper.

Data-adaptive spline surfaces for non-separable hyperelastic energy functions Neural networks meet hyperelasticity: A monotonic approach

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:05:59.799188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation db25a99f-6dea-427c-a7a5-d3383033624f · inbound

Learning finite viscoelasticity with DAVIS: A supervised framework for generalized standard materials cites this paper.

Learning finite viscoelasticity with DAVIS: A supervised framework for generalized standard materials Neural networks meet hyperelasticity: A monotonic approach

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-07-02T05:56:40.792064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.