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Paper Citation Record · LEDGER

Generalized Lagrangian Neural Networks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2401.03728.

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

pith.paper-citation-record.v1
2401.03728 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 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:11:42.940900Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T18:56:05.805505Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
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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 5c4eea68-2252-4040-9663-668a8f97d536 · inbound

Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics cites this paper.

Learning mechanical systems from real-world data using discrete forced Lagrangian dynamics Generalized Lagrangian Neural Networks

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T14:11:42.940900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:11:42.940900Z digest=sha256:7a7a4986f985edd59f91fe40fae27a3ae520457a9cc56e4cf53cdad72d36b371

Observation 5ab3a160-7e78-4d14-a574-78da8350237e · inbound

Newtonian and Lagrangian Neural Networks: A Comparison Towards Efficient Inverse Dynamics Identification cites this paper.

Newtonian and Lagrangian Neural Networks: A Comparison Towards Efficient Inverse Dynamics Identification Generalized Lagrangian Neural Networks

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T23:28:35.515536Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:28:35.515536Z digest=sha256:90e4488d1afdc7c1bfac18d5956db509fc688f9c53595ce550abe7bf471c6a33

Observation ed6b3f76-a92b-4a09-8549-5de49415da82 · inbound

Structure-Preserving Gaussian Processes Via Discrete Euler-Lagrange Equations cites this paper.

Structure-Preserving Gaussian Processes Via Discrete Euler-Lagrange Equations Generalized Lagrangian Neural Networks

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:56:05.807528Z

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=2026-05-08T13:28:06.412955Z digest=sha256:2b690526c7194bd8cc8e3a02477e573876885235c2df1259a1ae9f3c52d3ea4b