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Paper Citation Record · LEDGER

Transfer Learning for Control Systems via Neural Simulation Relations

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.01783.

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

pith.paper-citation-record.v1
2412.01783 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 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T23:17:08.369342Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T10:16:28.336425Z

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 575032bd-9cdb-411e-acb4-f13d2a18fffb · inbound

Hierarchical Control for Continuous-time Systems via General Approximate Alternating Simulation Relations cites this paper.

Hierarchical Control for Continuous-time Systems via General Approximate Alternating Simulation Relations Transfer Learning for Control Systems via Neural Simulation Relations

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:16:28.337899Z

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.

source=arxiv_source observed=2026-05-07T06:45:33.765409Z digest=sha256:7903d9867fe209a0b749664d115d78539f0219526382545602698b0287825a35

Observation 9f96ce8c-4a39-44ce-bf7a-7776ba23b9f4 · inbound

Data-Driven Formal Methods for Complex Dynamical Systems: A Survey cites this paper.

Data-Driven Formal Methods for Complex Dynamical Systems: A Survey Transfer Learning for Control Systems via Neural Simulation Relations

Reference 8005

Resolution
unresolved
no resolver link, observed 2026-07-31T23:17:08.369342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T23:17:08.369342Z digest=sha256:1d89e77c39d2f058e6f4adb115bd31f5915416777f3f6b68735e4bcd884c3fc5