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Paper Citation Record · LEDGER

Koopman Operators in Robot Learning

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2408.04200.

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

pith.paper-citation-record.v1
2408.04200 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:24:30.497012Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

5
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3d0460ec-4019-4c64-a1a3-dd0c4dc1201b · inbound

Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots cites this paper.

Continual Learning and Lifting of Koopman Dynamics for Linear Control of Legged Robots Koopman Operators in Robot Learning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T15:24:30.497012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:24:30.497012Z digest=sha256:4c93e6f57ee9c08f74d91061fc5619f75beaed23f7583e0229d54e880cd0b3e0

Observation bae931a2-3f97-441f-85f7-62c164186fea · inbound

Data-Driven Contact-Aware Control Method for Real-Time Deformable Tool Manipulation: A Case Study in the Environmental Swabbing cites this paper.

Data-Driven Contact-Aware Control Method for Real-Time Deformable Tool Manipulation: A Case Study in the Environmental Swabbing Koopman Operators in Robot Learning

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-22T22:37:12.482938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-22T22:37:07.608847Z digest=sha256:e9075a41a63a22421f3596db03e94cf4b81f4a19f1e386162c4dc3232137bf2e

Observation 095ceb6a-d8c3-4544-b057-6a937379a6b3 · inbound

Extracting transient Koopman modes from short-term weather simulations with sparsity-promoting dynamic mode decomposition cites this paper.

Extracting transient Koopman modes from short-term weather simulations with sparsity-promoting dynamic mode decomposition Koopman Operators in Robot Learning

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-19T10:12:14.619481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-19T10:07:17.688238Z digest=sha256:05f36d301ab6afd8e20dfeb742cd65b92a8bde5e1a19717146a0a14867a13b8f

Observation 64e63271-d7f9-4331-85b9-11cf89e701e7 · inbound

Koopman Model Dimension Reduction via Variational Bayesian Inference and Graph Search cites this paper.

Koopman Model Dimension Reduction via Variational Bayesian Inference and Graph Search Koopman Operators in Robot Learning

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-03T11:32:56.537411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T11:32:56.537411Z digest=sha256:04c20f897a0c96781ede6d0dc1b3f5b30a685ea90f40f69a767e43d71379d1ae

Observation 1dea09d4-ffd1-4a6c-9eea-db079ae6b392 · inbound

KFTD: Koopman-Fourier Time-Differentiable Network for Continuous Ocean Spatiotemporal Forecasting cites this paper.

KFTD: Koopman-Fourier Time-Differentiable Network for Continuous Ocean Spatiotemporal Forecasting Koopman Operators in Robot Learning

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-07-02T22:07:26.429089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-27T19:11:15.490486Z digest=sha256:b7267744c349a87729c05a219dc3fc1496c04f1e033f6d346211c6a6023cb02e

Observation edaaf2c4-7f5a-4b77-b413-04f1e0498576 · inbound

Learning the Koopman Operator using Attention Free Transformers cites this paper.

Learning the Koopman Operator using Attention Free Transformers Koopman Operators in Robot Learning

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-06-26T08:59:15.437470Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-06-26T08:49:32.561520Z digest=sha256:90ebcad19345d36b0c695c342d82be2827a3e11ce9d04062edf85933ec19ecd9

Observation d13860ce-f2aa-4ce7-ae05-ed9377244438 · inbound

MetaKoopman: Bayesian Meta-Learning of Koopman Operators for Modeling Structured Dynamics under Distribution Shifts cites this paper.

MetaKoopman: Bayesian Meta-Learning of Koopman Operators for Modeling Structured Dynamics under Distribution Shifts Koopman Operators in Robot Learning

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-01T00:11:34.262197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:11:34.262197Z digest=sha256:9b6dbb8949dc26ccfab218ea5e47a00368b8586c5778d6ac469fc5839b4b2431

Observation 42b6694b-dabc-410c-b2bc-7e35dbbc8d0a · inbound

Self-Adaptive Learning and Model Predictive Control for Tracking Unknown Dynamics with No Regret cites this paper.

Self-Adaptive Learning and Model Predictive Control for Tracking Unknown Dynamics with No Regret Koopman Operators in Robot Learning

Reference 103

Resolution
unresolved
no resolver link, observed 2026-08-01T17:24:15.057398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T17:24:15.057398Z digest=sha256:c932678201a8e6d3ff9e5d848b226dfc7c93fe6421c51c5acd329aab9afef991