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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 2026-08-10T06:31:04.303077+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
  • metadata mismatch1

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.714926Z digest=sha256:7043571512ffb7eee45a3a5c85cfe6a7294973201891a687858a04964c32c78e

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

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local_arxiv, observed 2026-08-09T14:30:09.537171Z

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.

source=arxiv_source observed=2026-08-09T14:30:08.719926Z digest=sha256:a5d611a826157e7566073eb0c86cbbe4bff81b0460d305c3bf8f2636ad7e9deb

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

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raw_fallback, observed 2026-08-09T14:30:09.700464Z

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.

source=arxiv_source observed=2026-08-09T14:30:08.724371Z digest=sha256:be64aed26f9f460f4e6447976edf4b42b8bad3a6731bef708d7ccb6e1926e152

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=arxiv_source observed=2026-08-09T14:30:08.728361Z digest=sha256:b56d12ce2ff07a35f644d9cb56e8c14dec2ae29dd671339d2ce2dc259bdfe671

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

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

source=arxiv_source observed=2026-08-09T14:30:08.732498Z digest=sha256:9e98192080b5af2702e4a0eeba66de9f0d0b5110dd5314b3afbbebf27afac4dc

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

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source=arxiv_source observed=2026-08-09T14:30:08.736726Z digest=sha256:6a0522847cab899ec47d27740721b4b9839039ea6c64a26407c4f08de63b0d72

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

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source=arxiv_source observed=2026-08-09T14:30:08.741081Z digest=sha256:c54bf687440d891137a02670465025c453476923bc71ced2ef71db36360ba99f

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

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

source=arxiv_source observed=2026-08-09T14:30:08.745488Z digest=sha256:f44139e8592bd5e4166bb18ea6ec66ab528bf910f974b5b360af24c130a1a73a

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

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source=arxiv_source observed=2026-08-09T14:30:08.749471Z digest=sha256:922275d1e10537af55e1d267abc2ef5d2c31ab2ee37aff984a70cd1770e3aed3

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

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source=arxiv_source observed=2026-08-09T14:30:08.753657Z digest=sha256:bb6c328a6262b9d9b9a1d7c0233e060bbf578296211aaf9159573bc7deba95d8

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=arxiv_source observed=2026-08-09T14:30:08.757952Z digest=sha256:36bd837a5eb618e086b6f66683156d8f147f8ecc085af7348f6334adcfb45960

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

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

source=arxiv_source observed=2026-08-09T14:30:08.761843Z digest=sha256:d9038bf07c13857cc017ca1342d79d306705f2c8b062c0ab2b42ca5056fd318f

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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doi, observed 2026-08-09T14:30:08.961834Z

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.

source=arxiv_source observed=2026-08-09T14:30:08.765924Z digest=sha256:2d6bc00596cd519265678434bf57dd5bb1f801ed74b93c6fa8463a9527626c40

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

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local_arxiv, observed 2026-08-09T14:30:09.366601Z

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.

source=arxiv_source observed=2026-08-09T14:30:08.770172Z digest=sha256:15afeb0e1db71300dc0cc861ec31fab3a94c5b79b19013a8dd9c65cda8f91cb8

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=arxiv_source observed=2026-08-09T14:30:08.774654Z digest=sha256:d335ecd81e22c744d697e239f31f0eb94f5f03b28192ce4d3899008afb76cdc3

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

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

source=arxiv_source observed=2026-08-09T14:30:08.778562Z digest=sha256:2fd9d6182ab93a933af27f291d55aedf000f73e1104deefbf2825d0acd9629c4

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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no resolver link, observed 2026-08-09T14:30:08.782693Z

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source=arxiv_source observed=2026-08-09T14:30:08.782693Z digest=sha256:85cfdbfd92e35aa48130eb601769652c81900a02df9e0eb35df73bab50d4faab

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=arxiv_source observed=2026-08-09T14:30:08.786791Z digest=sha256:2c2b0e947cf195dc517f91e7405a9737ae190e313db9e71e1b2cb0815888d0c8

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

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raw_fallback, observed 2026-08-09T14:30:09.644947Z

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.

source=arxiv_source observed=2026-08-09T14:30:08.791151Z digest=sha256:01b6d1a8ce677f47611b68699c33c50b665c1aec2f7bab09929dbefb05b3c9fc

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=arxiv_source observed=2026-08-09T14:30:08.794753Z digest=sha256:c35926d37b686ac75626e60ad74548ce928ebd991b1499caf8edc70416474c55

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

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source=arxiv_source observed=2026-08-09T14:30:08.798022Z digest=sha256:b6aa4457b871e8b9d909378864470653f0db782cb2a378c32db5f2c73bd87fbe

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

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source=arxiv_source observed=2026-08-09T14:30:08.802098Z digest=sha256:50c9d8bef398f88b17fc747fd8e54d17dd2aed9e85c142d3503b6c2ba476a416

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

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source=arxiv_source observed=2026-08-09T14:30:08.805934Z digest=sha256:4525de5206b6f984f571e3a955ba5dca54b2921ffa245ecd6bbc2018f3876054

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

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raw_fallback, observed 2026-08-09T14:30:09.625989Z

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.

source=arxiv_source observed=2026-08-09T14:30:08.809871Z digest=sha256:1c1cafbb18380811e918ee1e3e87896c51c56181cec6a45c38dbdb0068ab9ac4

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

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

source=arxiv_source observed=2026-08-09T14:30:08.813250Z digest=sha256:8123b61ffb9a169284a22885cdc30065367ade5bf7e214696a8220210fac2eea

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

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

source=arxiv_source observed=2026-08-09T14:30:08.817148Z digest=sha256:864c2631c90e0af14d3951de6e65d9e85dd4e99db582e6957d70f1951cd3b3d1

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=arxiv_source observed=2026-08-09T14:30:08.821159Z digest=sha256:8b67e79960e949c7114b074564abbc2b2a8e32750f33f8db3a646b921d6a504b

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=arxiv_source observed=2026-08-09T14:30:08.826834Z digest=sha256:742026ca5b8e98f9e4fb782f5d38c4d7997c8ae4d4f6b2f8e3d3b8e7225907e1

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.831104Z digest=sha256:f4be79433a161e83ea22adedbe909b66377d9f25ea8a4c973f225770a7cd9f57

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

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.835935Z digest=sha256:13090a67a51938a7a4d5808c9d749deaa591ada5c811fdb5f8355340017135a2

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

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source=arxiv_source observed=2026-08-09T14:30:08.840520Z digest=sha256:dbad8292a4067725ecb98254084f171f3d3a3f930332f73bedb08554fd7a0163

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

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.844939Z digest=sha256:5367e99aa24369ce1cd8c99e8a6fb7effaa4fdfb405dc831d26384d976aff25f

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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no resolver link, observed 2026-08-09T14:30:08.850211Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.850211Z digest=sha256:cec4924ee5466b04ca3c1ca494bc1f686faed8ce21bb89a060a129ccabb9921d

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

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source=arxiv_source observed=2026-08-09T14:30:08.854536Z digest=sha256:b79c5d1bf57ff15ca428cb085009fefb9e98745861c7bc9166b418efa3aa552b

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

This paper cites an unresolved cited work.

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

Reference 35

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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.

source=arxiv_source observed=2026-08-09T14:30:08.859178Z digest=sha256:892456a039dcbce45150beee195df2c9f2e3847fcceb6c04a3098c73270a5e84

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

This paper cites an unresolved cited work.

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

Reference 36

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raw_fallback, observed 2026-08-09T14:30:09.589922Z

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.

source=arxiv_source observed=2026-08-09T14:30:08.862925Z digest=sha256:ae6bc8cf4c19f16cc9b68e8959c3f5ded3187f2b4d7947417995724469cb4455

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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unresolved
no resolver link, observed 2026-08-09T14:30:08.866818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.866818Z digest=sha256:cdfd5d4ab714d0444921384f55b702d0523246f95cf326097ab92906a86b4486

Observation 2bed6187-1085-404c-acbe-807178ef2738 · outbound

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

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.

source=arxiv_source observed=2026-08-09T14:30:08.870641Z digest=sha256:fe8bf8f30b106c04be94ea16a3f17981e9da7d048bab4d6ecac9d783966f1ddf

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

Resolution
unresolved
no resolver link, observed 2026-08-09T14:30:08.874451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.874451Z digest=sha256:dfaf2edb81313d27d4822cd779edd9ffaa25d21a63dc2c97d6bdaee3c3346aa7

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

This paper cites an unresolved cited work.

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

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-09T14:30:08.878322Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.878322Z digest=sha256:159d81ff4fc4d2666ef0b9abe1597be0ce4e355e32a2163034b53bd2524ecab1

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.881969Z digest=sha256:1d9f9236fb3ed339b0be229e72cc15ed57ce3fb906c6c3fcba3e9d7fa50a5e7f

Observation 025381d1-2c75-4d8a-af57-2a9d56dfa9a3 · outbound

This paper cites A., Akinola, I., Handa, A., Sukhatme, G.

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

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.

source=arxiv_source observed=2026-08-09T14:30:08.886149Z digest=sha256:c2ee1d16c0f82b7dae3cebc6c4e86f0b055300af22732eb3780e79688e4f533b

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

This paper cites Domain Randomization via Entropy Maximization.

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

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-09T14:30:08.890438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.890438Z digest=sha256:c1f25a1ad9f5fb55027adc70b4293505f468b3c33b0d1929c721ee690d9c0c39

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

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.

source=arxiv_source observed=2026-08-09T14:30:08.894612Z digest=sha256:5972bb3d5bcd6f58df4a208818d9155a83a61a38d036267bc6561613f2eae397

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

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-09T14:30:08.898442Z digest=sha256:2a1aff94b915c0bd7970b0f0fd26359e44a06a05fecaff397debe089b884a998

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

Resolution
unresolved
no resolver link, observed 2026-08-09T14:30:08.902867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.902867Z digest=sha256:d44350c3e6a9ac634e4898466c07d2dfc83d6698f50eea1eb89dd3f66042f770

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

This paper cites Policy Transfer with Strategy Optimization.

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

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-09T14:30:08.907639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.907639Z digest=sha256:55aec718fc7d27b1365d87a17bb6859dc096327d061a1581efae997d4e5b9cdc

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

Resolution
unresolved
no resolver link, observed 2026-08-09T14:30:08.912120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T14:30:08.912120Z digest=sha256:172ddecbf03bbad555c252d85f173ba80fb05a70e5db38a945fcecc952ca2ca9

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

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.

source=arxiv_source observed=2026-08-09T14:30:08.915837Z digest=sha256:9c15f0868008dcb8844b4e18e2cf5d47c397c7b019ad4f589c15d2cb26686272

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.

source=arxiv_source observed=2026-08-09T14:30:08.919449Z digest=sha256:d0a7ca6da13f37d5bd47a52ffd66b859a3499adaf5f800bb1def6a25fd020dec

Pith citing papers

No inbound Pith citation observations are available.