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Paper Citation Record · LEDGER

Verified Safe Reinforcement Learning for Neural Network Dynamic Models

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2405.15994.

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

pith.paper-citation-record.v1
2405.15994 v2

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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:56:55.303280Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T16:57:34.551392Z

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 2b3a95bd-7fa2-419c-82b0-5b05a16ed0b0 · inbound

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics cites this paper.

BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Verified Safe Reinforcement Learning for Neural Network Dynamic Models

Reference 63

Resolution
verified exact
local_arxiv, observed 2026-08-11T16:57:34.556522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T16:57:34.219440Z digest=sha256:283eccf14171fd04a7a1b405eebcca2269b3843019fae73c51935f5a55f88dbe

Observation 84f0bdaf-976c-4a8c-82f8-619f873a5b3f · inbound

Learning Verifiable Control Policies Using Relaxed Verification cites this paper.

Learning Verifiable Control Policies Using Relaxed Verification Verified Safe Reinforcement Learning for Neural Network Dynamic Models

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-16T10:56:55.303280Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:56:55.303280Z digest=sha256:d91cb0fba17174415cb1deb71d245be8db7d20789d8aa13f3e5a8e5395fa15d1