Paper Citation Record · LEDGER

Lyapunov Design for Robust and Efficient Robotic Reinforcement Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 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 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:31:10.765781Z

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 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.

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 2026-08-10T06:31:04.303077+00:00.

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.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.

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 2026-08-10T06:31:04.303077+00:00.