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Paper Citation Record · LEDGER

Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2208.06721.

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

pith.paper-citation-record.v1
2208.06721 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:06:51.347062Z

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

6
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 4ee89a59-0ce1-4cb1-b184-e3eb25baa977 · inbound

Physics-model-guided Worst-case Sampling for Safe Reinforcement Learning cites this paper.

Physics-model-guided Worst-case Sampling for Safe Reinforcement Learning Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-11T14:06:51.347062Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:06:51.347062Z digest=sha256:91a69f2e32dcf8218edec11fefe10f45a0d3f443f16858bfeb04a5bbe6e48f95

Observation 27ab88ee-2b3d-42f3-8844-7d79ac2833d4 · inbound

Rapidly Adapting Policies to the Real World via Simulation-Guided Fine-Tuning cites this paper.

Rapidly Adapting Policies to the Real World via Simulation-Guided Fine-Tuning Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-09T11:31:10.765781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:31:10.765781Z digest=sha256:ff365746bd1142e0e39930df5c003a72b586bb56646ef51dc4b4be59a0b0f2a1

Observation 3030c1f6-6e9a-445d-8e5e-86024e679d34 · inbound

A Review On Safe Reinforcement Learning Using Lyapunov and Barrier Functions cites this paper.

A Review On Safe Reinforcement Learning Using Lyapunov and Barrier Functions Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning

Reference 68

Resolution
verified exact
arxiv_id, observed 2026-05-18T22:41:53.784062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-18T22:37:32.388931Z digest=sha256:918a6ad4541eb2b1c17be02f13d265fba639309b8543e55ea4049a732cb7abc6

Observation 2385aec5-d5c6-48f6-8ec8-0f6ef28bc278 · inbound

Control Synthesis with Reinforcement Learning: A Modeling Perspective cites this paper.

Control Synthesis with Reinforcement Learning: A Modeling Perspective Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-04T07:37:46.494550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:37:46.494550Z digest=sha256:fbde3cef62a7d57d004be443371b326d37646f4ee5c28333616b73f3c1981584

Observation 50053440-0409-4e53-8976-98039b2a97c5 · inbound

Simulation Distillation: Pretraining World Models in Simulation for Rapid Real-World Adaptation cites this paper.

Simulation Distillation: Pretraining World Models in Simulation for Rapid Real-World Adaptation Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-15T09:49:54.492689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-15T09:49:03.333757Z digest=sha256:dd16281b7cc38a31109b2a093920c8431c0390db74ec86b24eff24729e7d1e93

Observation e6cfdbf9-b34f-47ad-983e-6670e4f1ef22 · inbound

OHP-RL: Online Human Preference as Guidance in Reinforcement Learning for Robot Manipulation cites this paper.

OHP-RL: Online Human Preference as Guidance in Reinforcement Learning for Robot Manipulation Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-20T17:38:48.195295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T17:38:15.672066Z digest=sha256:78c9dcc08a9ee76a156cd6c3cadaf498df6e11c3a73c66ee36903b384e3e4ba9

Observation 60d1a9fd-0605-4e4b-a1a0-10f57b2df28c · inbound

OHP-RL: Online Human Preference as Guidance in Reinforcement Learning for Robot Manipulation cites this paper.

OHP-RL: Online Human Preference as Guidance in Reinforcement Learning for Robot Manipulation Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-06-30T19:45:00.844455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T19:40:19.827541Z digest=sha256:4b2edccfe1cb571399a9ffd3ed2344ef0263bc1a6baeb9e59f7f996deb09dd80

Observation 7bb83e81-2663-4ccb-bccc-936aaca84f71 · inbound

Zero-shot Transfer of Reinforcement Learning Control Policies for the Swing-Up and Stabilization of a Cart-Pole System cites this paper.

Zero-shot Transfer of Reinforcement Learning Control Policies for the Swing-Up and Stabilization of a Cart-Pole System Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-06-26T11:39:24.466295Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-26T11:39:18.595140Z digest=sha256:e6f5f076ac3613c41f5e1e22ea33dfc91383d608830b66dddc5b67f1bf8781f0

Observation d22a29e8-4459-4ea7-bc63-e80ebe746f6b · inbound

MPC-Injection: Biasing Off-Policy Locomotion RL Toward Controller-Induced Behavior Basins cites this paper.

MPC-Injection: Biasing Off-Policy Locomotion RL Toward Controller-Induced Behavior Basins Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-06-26T02:18:55.808081Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-26T01:33:55.421520Z digest=sha256:70ae1ae2df2339b1778bcf662bc2922ad507deafa513eafbc09b16bb95c5f8cb