Paper Citation Record · LEDGER

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills

As of 10 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2502.01800.

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

pith.paper-citation-record.v1
2502.01800 v2

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T14:30:08.919449Z

measured 50 of 50 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

50 of 50 outbound references displayed

verified exact8
verified fuzzy9
unresolved32
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c4b9277c-f961-49d0-ae6b-0f1a9530ecd8 · outbound

This paper cites write newline.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills write newline

Reference 1

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Source-reported events for the cited work

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Observation 7eada38b-b4ef-4287-9204-d4069481dee9 · outbound

This paper cites Distributionally Adaptive Meta Reinforcement Learning.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Distributionally Adaptive Meta Reinforcement Learning

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-09T14:30:09.537171Z

Source-reported events for the cited work

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Observation a06e4884-7c11-4dfa-bd2f-a9e51970e50e · outbound

This paper cites Closing the sim-to-real loop: Adapting simulation randomization with real world experience.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Closing the sim-to-real loop: Adapting simulation randomization with real world experience

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:30:09.700464Z

Source-reported events for the cited work

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Observation 3d9c91d8-8be8-4684-a205-42a6b4d56cba · outbound

This paper cites Understanding Domain Randomization for Sim-to-real Transfer.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Understanding Domain Randomization for Sim-to-real Transfer

Reference 4

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Source-reported events for the cited work

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Observation ff0abada-2d3d-4aab-8837-a01828538b67 · outbound

This paper cites Task-Directed Exploration in Continuous POMDPs for Robotic Manipulation of Articulated Objects.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Task-Directed Exploration in Continuous POMDPs for Robotic Manipulation of Articulated Objects

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-09T14:30:09.508717Z

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.

Observation d253d8a5-a57c-42b3-bc0c-ef828b9849cb · outbound

This paper cites Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.736726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40d8c6a5-a402-4534-9b4e-26fa567b5e1a · outbound

This paper cites Sequential monte carlo samplers.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Sequential monte carlo samplers

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.741081Z

Source-reported events for the cited work

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Observation 64aabcd7-1d0c-40ed-9d60-8e8bdf32df87 · outbound

This paper cites Neural spline flows.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Neural spline flows

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:30:09.682095Z

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.

Observation 38612c4c-9512-461d-b48e-3fab13f59dd2 · outbound

This paper cites Bayes3D: fast learning and inference in structured generative models of 3D objects and scenes.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Bayes3D: fast learning and inference in structured generative models of 3D objects and scenes

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.749471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed2954b7-1256-451e-8348-517233ba7b30 · outbound

This paper cites Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.753657Z

Source-reported events for the cited work

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Observation 8821c16d-833f-4ac4-b795-4bf6821b8610 · outbound

This paper cites Vision-force-fused curriculum learning for robotic contact-rich assembly tasks.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Vision-force-fused curriculum learning for robotic contact-rich assembly tasks

Reference 11

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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.

Observation 2ea8dd68-fb6f-4923-8e0f-5f584fcfe32b · outbound

This paper cites L., Navarro-Guerrero, N., and Knoll, A.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills L., Navarro-Guerrero, N., and Knoll, A

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:30:09.663042Z

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.

Observation c7b0b4b2-29c2-4cb5-a82e-e5a5496e18a8 · outbound

This paper cites and Lozano-Perez, T.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills and Lozano-Perez, T

Reference 13

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Source-reported events for the cited work

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Observation 5e648201-28b2-46b4-907c-5dc894dec93e · outbound

This paper cites A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-09T14:30:09.366601Z

Source-reported events for the cited work

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Observation 6bf87250-9381-4945-9d40-7a7535f2fe05 · outbound

This paper cites A., and Peters, J.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills A., and Peters, J

Reference 15

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Source-reported events for the cited work

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Observation eeb6aad4-c643-4b36-9896-edb22acd373c · outbound

This paper cites RL for Latent MDPs: Regret Guarantees and a Lower Bound.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills RL for Latent MDPs: Regret Guarantees and a Lower Bound

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-08-09T14:30:09.348523Z

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.

Observation 941f4c2d-fa77-4940-a82f-81ecb889539d · outbound

This paper cites MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills MegaPose: 6D Pose Estimation of Novel Objects via Render & Compare

Reference 17

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Source-reported events for the cited work

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Observation 7a999e28-8ba9-43f1-b8f6-34a62d8c2731 · outbound

This paper cites Learning Active Task-Oriented Exploration Policies for Bridging the Sim-to-Real Gap.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Learning Active Task-Oriented Exploration Policies for Bridging the Sim-to-Real Gap

Reference 18

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Source-reported events for the cited work

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Observation ac295e5a-1437-47da-9256-3677371f2f54 · outbound

This paper cites and Li, H.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills and Li, H

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:30:09.644947Z

Source-reported events for the cited work

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Observation 33f8e990-c760-4160-a71f-02c4b85c3a84 · outbound

This paper cites J., and Paull, L.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills J., and Paull, L

Reference 20

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Source-reported events for the cited work

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Observation 347dc41c-e907-4e88-bc2a-0f5b15167b76 · outbound

This paper cites Generative Skill Chaining: Long-Horizon Skill Planning with Diffusion Models.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Generative Skill Chaining: Long-Horizon Skill Planning with Diffusion Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.798022Z

Source-reported events for the cited work

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Observation c5d8659f-0174-4ab2-a7a1-9e051c893c85 · outbound

This paper cites L., Singh, R., Guo, Y., Mazhar, H., Mandlekar, A., Babich, B., State, G., Hutter, M., and Garg, A.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills L., Singh, R., Guo, Y., Mazhar, H., Mandlekar, A., Babich, B., State, G., Hutter, M., and Garg, A

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.802098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20b38924-b9bc-4b94-ba55-ce14b8dc0140 · outbound

This paper cites Learning Domain Randomization Distributions for Training Robust Locomotion Policies.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Learning Domain Randomization Distributions for Training Robust Locomotion Policies

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.805934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64f9afcb-8b08-430d-9d22-2748e7ba301f · outbound

This paper cites Assessing transferability from simulation to reality for reinforcement learning.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Assessing transferability from simulation to reality for reinforcement learning

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:30:09.625989Z

Source-reported events for the cited work

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Observation 7e7163ce-9ffc-427c-9848-fbb99e7e816d · outbound

This paper cites Data-efficient Domain Randomization with Bayesian Optimization.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Data-efficient Domain Randomization with Bayesian Optimization

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-08-09T14:30:09.204258Z

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.

Observation 3e1d1c8e-4ceb-45e2-bda7-e47861f8b141 · outbound

This paper cites Neural posterior domain randomization.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Neural posterior domain randomization

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:30:09.614109Z

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.

Observation 25b28b81-9e1c-4f35-8b04-746d71789b3c · outbound

This paper cites Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks

Reference 27

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Source-reported events for the cited work

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Observation 0f514de6-63d8-4a17-8c6d-9d78fd7282bf · outbound

This paper cites FORGE: Force-Guided Exploration for Robust Contact-Rich Manipulation under Uncertainty.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills FORGE: Force-Guided Exploration for Robust Contact-Rich Manipulation under Uncertainty

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd1b090e-81d8-4205-be4b-69a65e3cfb9e · outbound

This paper cites Solving Rubik's Cube with a Robot Hand.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Solving Rubik's Cube with a Robot Hand

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.831104Z

Source-reported events for the cited work

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Observation f3f3fde0-5cdf-472f-bb90-0a538ee016c3 · outbound

This paper cites Assessing Generalization in Deep Reinforcement Learning.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Assessing Generalization in Deep Reinforcement Learning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.835935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f877928-3c75-4850-90f6-ba7a25e4854e · outbound

This paper cites Sim-to-Real Transfer of Robotic Control with Dynamics Randomization.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Sim-to-Real Transfer of Robotic Control with Dynamics Randomization

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.840520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 672a6315-a9ea-4c8e-bc7b-b7b03e54526e · outbound

This paper cites Asymmetric Actor Critic for Image-Based Robot Learning.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Asymmetric Actor Critic for Image-Based Robot Learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.844939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fbd9b0a-0026-4330-a9f4-6eabde436482 · outbound

This paper cites BayesSim: adaptive domain randomization via probabilistic inference for robotics simulators.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills BayesSim: adaptive domain randomization via probabilistic inference for robotics simulators

Reference 33

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Source-reported events for the cited work

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Observation 8a9717c0-16f3-4c44-a64c-e78ee47966f1 · outbound

This paper cites AdaptSim: Task-Driven Simulation Adaptation for Sim-to-Real Transfer.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills AdaptSim: Task-Driven Simulation Adaptation for Sim-to-Real Transfer

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.854536Z

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Observation cdad007d-2bdd-42d1-80a0-0ced8fe7e9f8 · outbound

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Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Unresolved cited work

Reference 35

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

Observation 12610908-bce0-4bd2-afaf-2a829ff4b396 · outbound

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Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Unresolved cited work

Reference 36

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Observation db67cc20-24d8-4055-88de-8d24c47f1775 · outbound

This paper cites Gradual Domain Adaptation via Normalizing Flows.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Gradual Domain Adaptation via Normalizing Flows

Reference 37

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This paper cites A., Solowjow, E., and Levine, S.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills A., Solowjow, E., and Levine, S

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:30:09.578732Z

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Observation 6fcdeb8c-58cd-48a0-94a7-7ef317a82231 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Proximal Policy Optimization Algorithms

Reference 39

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Observation 5ceb2925-ab27-4282-af50-9d0c7a43c900 · outbound

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Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Unresolved cited work

Reference 40

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Observation e340ef0e-0c1c-41a2-a673-fe5cd4637781 · outbound

This paper cites IndustReal: Transferring Contact-Rich Assembly Tasks from Simulation to Reality.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills IndustReal: Transferring Contact-Rich Assembly Tasks from Simulation to Reality

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.881969Z

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Flow-based Domain Randomization for Learning and Sequencing Robotic Skills A., Akinola, I., Handa, A., Sukhatme, G

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:30:09.559725Z

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Observation a7b2837b-8dbb-4975-97a6-29faca3685bb · outbound

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Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Domain Randomization via Entropy Maximization

Reference 43

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eaf26459-ef0a-478b-8a8f-820c86f24530 · outbound

This paper cites Crossing the gap: A deep dive into zero-shot sim-to-real transfer for dynamics.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Crossing the gap: A deep dive into zero-shot sim-to-real transfer for dynamics

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T14:30:09.548446Z

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Observation 67928117-128f-4d94-9b85-5e2e39dbf74f · outbound

This paper cites Robust Fast Adaptation from Adversarially Explicit Task Distribution Generation.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Robust Fast Adaptation from Adversarially Explicit Task Distribution Generation

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-08-09T14:30:09.055398Z

Source-reported events for the cited work

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Observation c0350be2-fd82-47c8-ba9e-d2e497b8ac29 · outbound

This paper cites FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects

Reference 46

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Observation e4fa8920-ef5d-480c-8c67-0dae9dfbeee5 · outbound

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Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Policy Transfer with Strategy Optimization

Reference 47

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Source-reported events for the cited work

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Observation 914fd601-6b27-4a9b-8b00-2a8126e0b105 · outbound

This paper cites A Modular Robotic Arm Control Stack for Research: Franka-Interface and FrankaPy.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills A Modular Robotic Arm Control Stack for Research: Franka-Interface and FrankaPy

Reference 48

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Observation 62a951dc-15ee-4b30-a51d-2552e00d11de · outbound

This paper cites Bridging the Sim-to-Real Gap with Dynamic Compliance Tuning for Industrial Insertion.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills Bridging the Sim-to-Real Gap with Dynamic Compliance Tuning for Industrial Insertion

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-08-09T14:30:08.999247Z

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Observation 1fc3d64b-cddb-42dd-8f93-1b7d4114c1fb · outbound

This paper cites The Ingredients of Real-World Robotic Reinforcement Learning.

Flow-based Domain Randomization for Learning and Sequencing Robotic Skills The Ingredients of Real-World Robotic Reinforcement Learning

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-09T14:30:08.919449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.