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Paper Citation Record · LEDGER

Learning Differentiable Tensegrity Dynamics using Graph Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.12216.

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

pith.paper-citation-record.v1
2410.12216 v1

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 2026-08-09T06:31:02.800959+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T21:09:31.783184Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T03:55:51.235328Z

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 1cefd6ef-989a-455a-a7d5-4cfdb0f3df84 · inbound

Morphology-Aware Graph Reinforcement Learning for Tensegrity Robot Locomotion cites this paper.

Morphology-Aware Graph Reinforcement Learning for Tensegrity Robot Locomotion Learning Differentiable Tensegrity Dynamics using Graph Neural Networks

Reference 27

Resolution
verified exact
arxiv_id, observed 2026-05-18T03:55:51.238085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T03:53:34.929607Z digest=sha256:38c9ed3a5ae62155b6b16d145eb212867f115077d0ae6510eda03e6bb8a47371

Observation 69153ec1-4e5b-44f8-bd6f-be39412ecbe9 · inbound

CableRobotGraphSim: A Graph Neural Network for Modeling Partially Observable Cable-Driven Robot Dynamics cites this paper.

CableRobotGraphSim: A Graph Neural Network for Modeling Partially Observable Cable-Driven Robot Dynamics Learning Differentiable Tensegrity Dynamics using Graph Neural Networks

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-02T21:09:31.783184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:09:31.783184Z digest=sha256:833f07c969a128a11eb6430981063f1200cde48ca78dcdd7ba3deb76834b4e82

Observation 6cb50178-7556-4738-89a1-fdc31d33ed87 · inbound

State and Trajectory Estimation of Tensegrity Robots via Factor Graphs and Chebyshev Polynomials cites this paper.

State and Trajectory Estimation of Tensegrity Robots via Factor Graphs and Chebyshev Polynomials Learning Differentiable Tensegrity Dynamics using Graph Neural Networks

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-11T07:35:58.203065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T17:06:09.601895Z digest=sha256:dbe2ed434bcad3a5d4ede7b41aea762a72a0cbec3577a89964e83ce15d5306bc