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Paper Citation Record · LEDGER

Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2301.04330.

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

pith.paper-citation-record.v1
2301.04330 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 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T19:49:35.434155Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T20:50:12.063429Z

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 ae054a7b-e5f1-41e0-a199-8450e500fc70 · inbound

BMP: Bridging the Gap between B-Spline and Movement Primitives cites this paper.

BMP: Bridging the Gap between B-Spline and Movement Primitives Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-12T19:49:35.434155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:49:35.434155Z digest=sha256:cca6612286ab3c5100e8699087b0252c5088e4051da9fddf42c5cc12215c1485

Observation 18a3a329-ca76-4c04-b7d4-04026e9ad2b1 · inbound

GASP: GPU-Accelerated Safe Planner for Real-Time Collision-Aware Motion Generation with Latent Trajectory Sampling cites this paper.

GASP: GPU-Accelerated Safe Planner for Real-Time Collision-Aware Motion Generation with Latent Trajectory Sampling Fast Kinodynamic Planning on the Constraint Manifold with Deep Neural Networks

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-06T20:50:12.113492Z

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=pdf_text observed=2026-08-06T20:50:10.975132Z digest=sha256:c52bdb14efef1b0104194a3dd32b086368ee110862c87047e37e23f313c21302