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Paper Citation Record · LEDGER

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation

As of 7 August 2026, this Paper Citation Record lists 94 of 94 outbound references and 2 inbound Pith citation observations for arXiv:2507.06111.

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

pith.paper-citation-record.v1
2507.06111 v1

Coverage vector

measured 94 of 94 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:19:29.466784Z

measured 96 of 96 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T22:51:20.005562Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T22:52:44.957699Z

Reference resolution

94 of 94 outbound references displayed

  • verified exact0
  • verified fuzzy54
  • unresolved39
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1526371c-a675-4c97-814b-746330775ae9 · outbound

This paper cites MIT press, 2018.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation MIT press, 2018

Reference 1

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Observation 4bf1724f-2714-4f22-86e8-f3e3a134e07f · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 2

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source=pdf_text observed=2026-08-06T19:19:29.270830Z digest=sha256:88f63cb0c508358a8cf7dc54b7d793cecc01ad3b1ca8ab32f53586c497359b10

Observation ba244a59-48ea-448b-a35c-4ea07b740dff · outbound

This paper cites Reinforcement learning in robotics: A survey.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Reinforcement learning in robotics: A survey

Reference 3

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source=pdf_text observed=2026-08-06T19:19:29.273775Z digest=sha256:9abfa23021430c76db783d27de72b57c1e50f8ed7069c17668c981a8baf9a792

Observation 56859d3c-2cd0-4236-95af-df70614d7519 · outbound

This paper cites Toward self-driving processes: A deep reinforcement learning approach to control.AIChE journal, 65(10):e16689, 2019.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Toward self-driving processes: A deep reinforcement learning approach to control.AIChE journal, 65(10):e16689, 2019

Reference 4

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source=pdf_text observed=2026-08-06T19:19:29.276094Z digest=sha256:d227dba5c209905f3bc7082adf951f82f9784a560c6824da4e8f387ce4ab7a43

Observation 5073135a-bf34-45ec-9085-8493b5d7d39f · outbound

This paper cites Sim-to-real transfer in deep reinforcement learning for robotics: a survey.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Sim-to-real transfer in deep reinforcement learning for robotics: a survey

Reference 5

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source=pdf_text observed=2026-08-06T19:19:29.278337Z digest=sha256:4e6ea60b3b7801734252a506c25806fd8fa67083dae7f51f3be16b3df1d5ebcf

Observation 15a92a1b-465b-48e0-bb1d-e67a041c145d · outbound

This paper cites Out-of-Distribution Dynamics Detection: RL-Relevant Benchmarks and Results.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Out-of-Distribution Dynamics Detection: RL-Relevant Benchmarks and Results

Reference 6

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source=pdf_text observed=2026-08-06T19:19:29.280573Z digest=sha256:cf11dc8eac4976b2f06eb631a782d8576c64ed9e78981dd24547f975448cb123

Observation 21553616-b72f-42f5-9ff6-d9b1a9d7554f · outbound

This paper cites Off-dynamics reinforcement learning: Training for transfer with domain classifiers.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Off-dynamics reinforcement learning: Training for transfer with domain classifiers

Reference 7

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source=pdf_text observed=2026-08-06T19:19:29.283011Z digest=sha256:ebfe2678ba8e6b280c9865787b9dac8b56dddf474bf3d929445ca989e1c8a493

Observation dbbeceac-cdb8-4aa8-9620-a67d693c4e8a · outbound

This paper cites Robust dynamic programming.Mathematics of Operations Research, 30(2):257–280, 2005.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Robust dynamic programming.Mathematics of Operations Research, 30(2):257–280, 2005

Reference 8

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source=pdf_text observed=2026-08-06T19:19:29.285338Z digest=sha256:a1de76162dbaee3f7e7c5031b16fe1c72f99bdabfe0f669fb1b67e1f0110d170

Observation 028831bd-968d-4d86-babd-2a5893be2385 · outbound

This paper cites Offline-to-online reinforcement learning via balanced replay and pessimistic q-ensemble.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Offline-to-online reinforcement learning via balanced replay and pessimistic q-ensemble

Reference 9

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source=pdf_text observed=2026-08-06T19:19:29.287354Z digest=sha256:b134bb50379eaa58571bb01e3ef8ac7db54be8496d64397a3ca4174bf95a6048

Observation 2da0939b-9d49-4471-b2dc-9fccee67e3ac · outbound

This paper cites Adaptive policy learning for offline-to-online reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Adaptive policy learning for offline-to-online reinforcement learning

Reference 10

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source=pdf_text observed=2026-08-06T19:19:29.289344Z digest=sha256:4c05882d15d0484a4abad1aebc1733a913afbc80880d43b4bd75dbf06337ccfd

Observation 22ed0b8b-7e03-4621-a290-1cf07f5008e1 · outbound

This paper cites Domain randomization for transferring deep neural networks from simulation to the real world.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Domain randomization for transferring deep neural networks from simulation to the real world

Reference 11

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source=pdf_text observed=2026-08-06T19:19:29.291520Z digest=sha256:916f638eac6f6df452ef789fbc6f9790c841f4960440d9170cba7e8b279fc2f8

Observation 0b98c3b2-914a-4c4f-a18a-98557b79b8e0 · outbound

This paper cites Pal, and Liam Paull.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Pal, and Liam Paull

Reference 12

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source=pdf_text observed=2026-08-06T19:19:29.293612Z digest=sha256:f4fbd0614df6fb143a1e34c4c7a452bdb4056d095e34f394cbcf8d51a7f47ae9

Observation 52067f97-ed3b-4a8f-9b0a-32e2eed5252f · outbound

This paper cites Mujoco: A physics engine for model-based control.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Mujoco: A physics engine for model-based control

Reference 13

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source=pdf_text observed=2026-08-06T19:19:29.296109Z digest=sha256:22c10765099179c2d5280c9ee4fe09bd7464248fac650f28d1f2871a8b8d855d

Observation 2db63577-4955-4e25-b994-5b2c2564a860 · outbound

This paper cites Towards a generic solution for inspection of industrial sites.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Towards a generic solution for inspection of industrial sites

Reference 14

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source=pdf_text observed=2026-08-06T19:19:29.298094Z digest=sha256:fc0670c0c3364faae211edbfaa062d5bf6f00fbd06395eaccd63866d60e03269

Observation bc1b65b0-5a98-4c53-8587-fff94163a914 · outbound

This paper cites Offline reinforcement learning with implicit q-learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Offline reinforcement learning with implicit q-learning

Reference 15

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source=pdf_text observed=2026-08-06T19:19:29.300018Z digest=sha256:de0c364c55a0ac0845b594c5a1ea188e8fa43d43aa9c2ec36c6cc94c3c85dc45

Observation 5bb02de6-6422-450c-8a4b-b8bf88b0c20b · outbound

This paper cites Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog

Reference 16

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source=pdf_text observed=2026-08-06T19:19:29.301981Z digest=sha256:9e6c15c3b878ca5669215381dbdfe4993c3f3fda3a255dd1d7e3df3fc7d4a3a1

Observation ee08bffa-b9a0-4338-8422-6d1c195222ae · outbound

This paper cites A minimalist approach to offline reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation A minimalist approach to offline reinforcement learning

Reference 17

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source=pdf_text observed=2026-08-06T19:19:29.304679Z digest=sha256:2265bfb022b5b457f5ab253bb11c7181f3bc31f6aec0301a1209abe7b5b0482b

Observation bee2bd30-27bc-4279-ae5d-b52113dc3e41 · outbound

This paper cites Conservative q-learning for offline reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Conservative q-learning for offline reinforcement learning

Reference 18

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source=pdf_text observed=2026-08-06T19:19:29.306599Z digest=sha256:c33d2f2d4d18673bb9521c64d7bcf59fc3766377e5a28b3158f558990ed84073

Observation 20eb6e39-95f7-43eb-a934-3d10f6fbe10b · outbound

This paper cites Uncertainty-based of- fline reinforcement learning with diversified q-ensemble.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Uncertainty-based of- fline reinforcement learning with diversified q-ensemble

Reference 19

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source=pdf_text observed=2026-08-06T19:19:29.308508Z digest=sha256:856624cb4ffbf065c04d8af48792ec56b7cce6d53ab5bebf4300587073c17495

Observation c53f3ea2-6348-499e-a952-2eb398ca4f21 · outbound

This paper cites Iteratively refined behavior regularization for offline reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Iteratively refined behavior regularization for offline reinforcement learning

Reference 20

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source=pdf_text observed=2026-08-06T19:19:29.310529Z digest=sha256:363c81fb16acace0b031a1c48ec7eb2f48a0b14e299ca7274ab4a1eab3b48b90

Observation ee8242d5-9d9d-4fff-a90a-9e4cc5f1d450 · outbound

This paper cites Offline reinforcement learning with OOD state correction and OOD action suppression.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Offline reinforcement learning with OOD state correction and OOD action suppression

Reference 21

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source=pdf_text observed=2026-08-06T19:19:29.312460Z digest=sha256:82fc325478dd8eb085294e4b73f0687957810696739f68472cf2faee4a959d82

Observation 0a9c719c-02dd-45dd-879a-57eafe701b56 · outbound

This paper cites Model-Bellman inconsistency for model-based offline reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Model-Bellman inconsistency for model-based offline reinforcement learning

Reference 22

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source=pdf_text observed=2026-08-06T19:19:29.314345Z digest=sha256:f1a522351836774733929f4f3a3a3d445bdf125c7cb99f925c3913924d697493

Observation 8048c12b-3fb2-4016-9c99-9a59bc06f200 · outbound

This paper cites Pessimistic bootstrapping for uncertainty-driven offline reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Pessimistic bootstrapping for uncertainty-driven offline reinforcement learning

Reference 23

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source=pdf_text observed=2026-08-06T19:19:29.316417Z digest=sha256:04e401842a7014a49571f502399c051e35110c785814929eab9738570d17dd12

Observation 6d05255c-a63e-4185-8418-3899e31904ee · outbound

This paper cites Rorl: Ro- bust offline reinforcement learning via conservative smoothing.Advances in neural information processing systems, 35:23851–23866, 2022.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Rorl: Ro- bust offline reinforcement learning via conservative smoothing.Advances in neural information processing systems, 35:23851–23866, 2022

Reference 24

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source=pdf_text observed=2026-08-06T19:19:29.318638Z digest=sha256:9987481154eaae731cc9440e0ffd30216daec29f1758a5ed827b8fb21d237c84

Observation 0021822e-187f-4dc2-aa2a-15414400336e · outbound

This paper cites When to trust your simulator: Dynamics-aware hybrid offline-and-online reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation When to trust your simulator: Dynamics-aware hybrid offline-and-online reinforcement learning

Reference 25

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source=pdf_text observed=2026-08-06T19:19:29.320703Z digest=sha256:5eaf23bfa0987ee77030df47ce3096663f9061989dc6438d68a7cedcd2acccc0

Observation 1648d827-69cd-4abd-866e-707f3e859cda · outbound

This paper cites Cross-domain policy adaptation via value-guided data filtering.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Cross-domain policy adaptation via value-guided data filtering

Reference 26

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source=pdf_text observed=2026-08-06T19:19:29.322700Z digest=sha256:6bd932c24f8cc3dc883b4a1ab31adfb12fd0788a657e841c0bb3f594d421d002

Observation 5cad286d-7c02-4cb0-a929-756ec34e37be · outbound

This paper cites Cross-domain policy adaptation by capturing representation mismatch.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Cross-domain policy adaptation by capturing representation mismatch

Reference 27

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source=pdf_text observed=2026-08-06T19:19:29.324779Z digest=sha256:298150217c6f6542129520ef85a6e80f5855fd718cbfa60bd406d5b79b698895

Observation b8338a00-9f6c-41d4-b8ef-7e2fa00fc332 · outbound

This paper cites Unsolved Problems in ML Safety.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Unsolved Problems in ML Safety

Reference 28

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source=pdf_text observed=2026-08-06T19:19:29.326782Z digest=sha256:14525d8bb4858f78eedd30060397711261106e12bb818d7512d2b8960a3e38d0

Observation 20628592-55e8-4951-a6f7-9e72589de342 · outbound

This paper cites Learning dexterous in-hand manipulation.The International Journal of Robotics Research, 39(1):3–20, 2020.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Learning dexterous in-hand manipulation.The International Journal of Robotics Research, 39(1):3–20, 2020

Reference 29

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source=pdf_text observed=2026-08-06T19:19:29.329102Z digest=sha256:34c8ba00c75fdc1a288e0122eb36f7a88f8cd628ff4812e9a1278ed13a48c110

Observation ff54dac0-ddf8-4970-a069-6a11f9a2fc24 · outbound

This paper cites Network randomization: A simple technique for generalization in deep reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Network randomization: A simple technique for generalization in deep reinforcement learning

Reference 30

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source=pdf_text observed=2026-08-06T19:19:29.331474Z digest=sha256:7ee7000d161be5f3b692b83406fd700a25738810fc9aecdde19af813b9fae602

Observation 135a6683-631b-424c-98a9-34fcc6649337 · outbound

This paper cites Learning domain randomization distributions for training robust locomotion policies.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Learning domain randomization distributions for training robust locomotion policies

Reference 31

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source=pdf_text observed=2026-08-06T19:19:29.333446Z digest=sha256:bd6a7def3b130813231bab3ca0704180ea20c216a15fbcda4ac206ab00261391

Observation a7568781-4dda-4914-a03b-96015ec8da77 · outbound

This paper cites A Markovian Decision Process.Indiana University Mathematics Journal, 6(4):679–684, 1957.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation A Markovian Decision Process.Indiana University Mathematics Journal, 6(4):679–684, 1957

Reference 32

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source=pdf_text observed=2026-08-06T19:19:29.335350Z digest=sha256:a0e076b5187d45d4a76afa7f92eac6948630e377094df6f93a2bd63582462fed

Observation 6ea5ee09-e2c6-453c-abae-4c239af013f0 · outbound

This paper cites Handling black swan events in deep learning with diversely extrapolated neural networks.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Handling black swan events in deep learning with diversely extrapolated neural networks

Reference 33

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source=pdf_text observed=2026-08-06T19:19:29.337048Z digest=sha256:9855df3454d82a609be20835bc6bad14a34330c622fe1dc3dbcfc53c0c9a1b88

Observation 3d72acdb-e36d-42a2-ab81-a9edbd72c976 · outbound

This paper cites Cal-QL: Calibrated offline RL pre-training for efficient online fine-tuning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Cal-QL: Calibrated offline RL pre-training for efficient online fine-tuning

Reference 34

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source=pdf_text observed=2026-08-06T19:19:29.338908Z digest=sha256:a751ef290e69b9c026fee38aa783ab10ab7239f5fcf3211ce623dffb85dbe43d

Observation 89de8493-1f4e-4a75-a416-b3beae587f0d · outbound

This paper cites AWAC: Accelerating Online Reinforcement Learning with Offline Datasets.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

Reference 35

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source=pdf_text observed=2026-08-06T19:19:29.341183Z digest=sha256:1a32ace10524ca739e2ff261a7beaa4797c2dcf4ba890eed89485609ffdf35dd

Observation 465d13c9-be27-4ae0-88e8-a76087b78458 · outbound

This paper cites D4RL: Datasets for Deep Data-Driven Reinforcement Learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation D4RL: Datasets for Deep Data-Driven Reinforcement Learning

Reference 36

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T19:19:29.343626Z digest=sha256:b365a618b966fa1d266036b80064e278e29970577c4347933d2787f50899d05b

Observation 9b219c75-4ffa-4510-a637-a87ed8da06a3 · outbound

This paper cites Terry, Ariel Kwiatkowski, John U.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Terry, Ariel Kwiatkowski, John U

Reference 37

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raw_fallback, observed 2026-08-06T19:19:29.910184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.346020Z digest=sha256:b6934390c79fe2238618ba9b64f24a2d8ddcfd7b382e5e0292663be4e4b0b584

Observation e0d11664-5751-476a-9d5d-27ba11d0f71b · outbound

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

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Soft actor-critic: Off- policy maximum entropy deep reinforcement learning with a stochastic actor

Reference 38

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raw_fallback, observed 2026-08-06T19:19:29.903281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.347835Z digest=sha256:e18d5c7bdca495c6540929d1fc9952e5ba8345c123e2d453d26d2ef455b7acef

Observation d9b9f682-7946-44a3-9028-18bc64fda4c4 · outbound

This paper cites Addressing function approximation error in actor-critic methods.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Addressing function approximation error in actor-critic methods

Reference 39

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:19:29.349772Z digest=sha256:8606f5626ab33d62a5ab76a2011a0328e8ad3807f08cd64bc3730363f6ad1427

Observation b1d777a0-3c31-41ae-9faa-2890d9c51f4f · outbound

This paper cites Corl: Research-oriented deep offline reinforcement learning library.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Corl: Research-oriented deep offline reinforcement learning library

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.890616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.352078Z digest=sha256:9742fb135170a6281b40980dee2f72600e2cc39015c20599a42572d4c309ae0c

Observation 752d14ce-4484-46ae-bca1-90b40391f100 · outbound

This paper cites Efficient online reinforcement learning with offline data.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Efficient online reinforcement learning with offline data

Reference 41

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no resolver link, observed 2026-08-06T19:19:29.354009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:19:29.354009Z digest=sha256:6cbdf9e645781cf4eaebb0f6b8f75e4fb8791fc4a0e0049d432eb6a999467387

Observation 7a3f1e80-44d1-4aec-bad1-b6334b7b664a · outbound

This paper cites Odrl: A benchmark for off-dynamics reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Odrl: A benchmark for off-dynamics reinforcement learning

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.877656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.356302Z digest=sha256:346696d263581440acbb28e421873c82511b01abec75373109f9357fb802efc9

Observation cb7d1f36-c7fa-42cf-87d0-45e79e5fbf57 · outbound

This paper cites Darl: distance-aware uncertainty estimation for offline reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Darl: distance-aware uncertainty estimation for offline reinforcement learning

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.870256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.358703Z digest=sha256:e575bb34a42172239d56febeb60f423bbf1859b1c757a365ede35f776107c52d

Observation f625135f-81d6-4579-9c72-d976d15e5d46 · outbound

This paper cites Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning

Reference 44

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no resolver link, observed 2026-08-06T19:19:29.360678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:19:29.360678Z digest=sha256:e08f021a2d3b73282411b83bff92cff1f553fd0066002f1f5ab2880bf980ccc0

Observation c4ce109d-cc73-4469-8485-8f5f7a86c5a1 · outbound

This paper cites Dario Bellicoso, Vassilios Tsounis, Jemin Hwangbo, Karen Bodie, Peter Fankhauser, Michael Bloesch, Remo Diethelm, Samuel Bachmann, Amir Melzer, and Mark Hoepflinger.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Dario Bellicoso, Vassilios Tsounis, Jemin Hwangbo, Karen Bodie, Peter Fankhauser, Michael Bloesch, Remo Diethelm, Samuel Bachmann, Amir Melzer, and Mark Hoepflinger

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.862493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.362912Z digest=sha256:279bc31665ac66e8471b027c5989dd4fdf5b07bdd8909261521c6ab6594cf36b

Observation 50084dd9-436a-4881-bbcc-a0a01590d0ff · outbound

This paper cites Learning to walk in minutes using massively parallel deep reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Learning to walk in minutes using massively parallel deep reinforcement learning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.854150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.364973Z digest=sha256:8c3ffc75ef8e92d113a4374d7a0ec383cc79e0f82e0e530e4e148c4c4f30903a

Observation d4297451-6beb-4138-ba31-b904e8cbec12 · outbound

This paper cites Learning agile and dynamic motor skills for legged robots.Science Robotics, 4(26):eaau5872, 2019.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Learning agile and dynamic motor skills for legged robots.Science Robotics, 4(26):eaau5872, 2019

Reference 47

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unresolved
no resolver link, observed 2026-08-06T19:19:29.366871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:19:29.366871Z digest=sha256:4ab363a37fabbb4e7623275dec1099e76e076fd40e6685b492f49ce02d0cba50

Observation 9aaf98a9-3769-4d8f-abf7-4fa1ce272a68 · outbound

This paper cites REvolveR: Continuous evolutionary models for robot-to-robot policy transfer.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation REvolveR: Continuous evolutionary models for robot-to-robot policy transfer

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.841571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.368958Z digest=sha256:9b4d9bc06b5e4c2daa3e02120f4ccbb102439c41f4802e9f52a0006e776a509d

Observation a8f851a0-5087-40e1-879a-1118306b0361 · outbound

This paper cites PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement Learning

Reference 49

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no resolver link, observed 2026-08-06T19:19:29.370866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:19:29.370866Z digest=sha256:cef1866dc5763fe04d3814ca2da4f88a2543d11b6a30744010323ea69918f6d6

Observation 819b9590-101f-4542-b17c-1bcf0a29a9bd · outbound

This paper cites Off-policy deep reinforcement learning without exploration.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Off-policy deep reinforcement learning without exploration

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.835110Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.373327Z digest=sha256:f2b0a906a8978754add3d9a821c1270f938ac0cd3297d795b3b36c5a27b45302

Observation f0f42879-8418-4202-aa5e-d81b0f110029 · outbound

This paper cites An optimistic perspective on offline reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation An optimistic perspective on offline reinforcement learning

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.827539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.375266Z digest=sha256:63f14d56a371ffe8721fa4a6d0bc2899f7120d9d5c9d8c99a45de47702515c3e

Observation 29ac67b7-ce28-40b4-8b7b-21d4cd3a7124 · outbound

This paper cites Tree-based batch mode reinforcement learning.Journal of Machine Learning Research, 6, 2005.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Tree-based batch mode reinforcement learning.Journal of Machine Learning Research, 6, 2005

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.820340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.377557Z digest=sha256:e11c7465ff66e14f9c0d617e170f094ca10b17325cc7fac1cad8251cec9e1c12

Observation 8dfcd02c-6f0d-40ba-add7-c9cfdb0124d1 · outbound

This paper cites Stabilizing off-policy q-learning via bootstrapping error reduction.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Stabilizing off-policy q-learning via bootstrapping error reduction

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.813522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.379882Z digest=sha256:230e63b19db1f44729e3fb40adbfa46c26041d57ae92e0461543cde68550479f

Observation 55874838-495d-4e38-bb63-cfb272151dc6 · outbound

This paper cites Batch reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Batch reinforcement learning

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.806240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.382002Z digest=sha256:27a445cc35d37ad25efb4cd3ebccab57a37d43898f4fd72f3a991696b14f4b97

Observation e0640f26-8c90-42d9-bbf1-2ffbe8ff7bd0 · outbound

This paper cites Critic regularized regression.Advances in Neural Information Processing Systems, 33:7768–7778, 2020.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Critic regularized regression.Advances in Neural Information Processing Systems, 33:7768–7778, 2020

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.799074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.384096Z digest=sha256:db82834d7bf131cc6500482c06ca0ea31f440403f249ed8039caa308a0713b27

Observation f78f2176-cf11-4722-8aea-42ac0e26f1ad · outbound

This paper cites Revisiting the minimalist approach to offline reinforcement learning.Advances in Neural Information Processing Systems, 36, 2024.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Revisiting the minimalist approach to offline reinforcement learning.Advances in Neural Information Processing Systems, 36, 2024

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.791474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.386007Z digest=sha256:2504a704e8ea8634e3154a3d063435a52b8b4dc8bae80d7c51ede6f62e94ab50

Observation f2b04cf0-7311-4c3e-92b0-5e76903e2726 · outbound

This paper cites Behavior Regularized Offline Reinforcement Learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Behavior Regularized Offline Reinforcement Learning

Reference 57

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no resolver link, observed 2026-08-06T19:19:29.387854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:19:29.387854Z digest=sha256:b21500b17e2b6207df5aa49ed31e2f8cdd353c79db865aef6ffa65da44e0f98d

Observation 1b2f9574-4016-42a6-bb3e-120b67be6ac6 · outbound

This paper cites Keep doing what worked: Behavior modelling priors for offline reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Keep doing what worked: Behavior modelling priors for offline reinforcement learning

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.783948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.390019Z digest=sha256:a1766771e6f6dd40973f678b80f41564db2441af316510d2c548dc5db306dfdf

Observation bd2927dd-016b-4e78-aed0-376aab5293fa · outbound

This paper cites Offline reinforcement learning with fisher divergence critic regularization.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Offline reinforcement learning with fisher divergence critic regularization

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.776341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.392283Z digest=sha256:f481b0de4037af7acabc69ce1d2e8b3d8a29685978f9f58efc223929001ec4dc

Observation ccdaffb5-16a9-467c-9476-671ed0365b51 · outbound

This paper cites Uncertainty weighted actor-critic for offline reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Uncertainty weighted actor-critic for offline reinforcement learning

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.768826Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.394549Z digest=sha256:6884fd9c687c15d4cd69f40db15a2881af3ce2d567142cf28cee655151fc348f

Observation 89e1fb23-82cc-48ab-8963-ad7587a9de85 · outbound

This paper cites Uni-o4: Unifying online and offline deep reinforcement learning with multi-step on-policy optimization.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Uni-o4: Unifying online and offline deep reinforcement learning with multi-step on-policy optimization

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.760539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.396578Z digest=sha256:bbc269b7d8b162687b40c75f1c99646edbac3094949c5fdd2e7eab63535084d7

Observation 963958b2-a71a-488e-8987-d9889d18be8f · outbound

This paper cites Enoto: Improving offline-to-online reinforcement learning with q-ensembles.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Enoto: Improving offline-to-online reinforcement learning with q-ensembles

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.753191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.398569Z digest=sha256:b3a1d220353468ab2a392dec583acd859bac5916833822a5c0a9f339c13fe4ec

Observation ab3132ae-9778-49a4-84b9-319bea955ec4 · outbound

This paper cites Online decision transformer.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Online decision transformer

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.744916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.400451Z digest=sha256:71ed005a4923cf09ba75f82961be4b2bf60b4b7e4e748d5b8a1a8d62d225d165

Observation fb53cca9-2672-4a72-bd95-01c21239d0cb · outbound

This paper cites Actor-critic alignment for offline-to-online reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Actor-critic alignment for offline-to-online reinforcement learning

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.737615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.402324Z digest=sha256:6c5e2f8efa2dec54236c16855419ca47054e42a7e2c7aa08a68b95cfb2007901

Observation 1df1ff13-ab37-47fc-b576-1c1c66aaeb7e · outbound

This paper cites Train once, get a family: State-adaptive balances for offline-to-online reinforcement learning.Advances in Neural Information Processing Systems, 36, 2024.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Train once, get a family: State-adaptive balances for offline-to-online reinforcement learning.Advances in Neural Information Processing Systems, 36, 2024

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.730169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.404627Z digest=sha256:7e3f4e922d57459970c14a7486d304bba9cf8484d642ceca2cbba6d8e88f62dc

Observation 6e2dcd07-f1b7-45e6-b59d-b4f3974fbdbc · outbound

This paper cites Policy expansion for bridging offline-to-online reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Policy expansion for bridging offline-to-online reinforcement learning

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.722584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.406945Z digest=sha256:f2f1a2ae8a85f7213000629a39b007fef950bd4c37eaaea4227b6d2a3c830f57

Observation 9faaf102-b410-4ae3-bf10-5977dcb8ff12 · outbound

This paper cites Albrecht, and Amos Storkey.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Albrecht, and Amos Storkey

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.715340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.409073Z digest=sha256:0f84ff85083565f52e189d68f93e8e16a14b8dd4f736075f389a923e3fdddf39

Observation aeff3033-7800-4f74-a7f8-cfbab583a70e · outbound

This paper cites A comprehensive survey on safe reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation A comprehensive survey on safe reinforcement learning

Reference 68

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unresolved
no resolver link, observed 2026-08-06T19:19:29.410801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:19:29.410801Z digest=sha256:d4e40d90a857749cd9aceaa4e56cdb4b9e2678ac25029a394c3049e4af08e2b2

Observation 866b0f2c-0144-4aa1-857d-504538951ec7 · outbound

This paper cites Consideration of risk in reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Consideration of risk in reinforcement learning

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T19:19:29.703434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T19:19:29.412546Z digest=sha256:c9e275343c53f5da694b0a16c8fc111c9490c1e7568aadf773cc6d1b5ba3c6b3

Observation ad5a7b7e-cd11-4111-a7a1-b6e87ac55b02 · outbound

This paper cites Robust control of markov decision processes with uncertain transition matrices.Operations Research, 53(5):780–798, 2005.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Robust control of markov decision processes with uncertain transition matrices.Operations Research, 53(5):780–798, 2005

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source=pdf_text observed=2026-08-06T19:19:29.414793Z digest=sha256:37c8e8d797455bf0cf81ea294d8bd85cdd55b519a7a4db23be763e67fdf0e58c

Observation b541c8e6-7200-49c9-8b4e-0ae5f1afcb13 · outbound

This paper cites Safe offline reinforcement learning with feasibility-guided diffusion model.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Safe offline reinforcement learning with feasibility-guided diffusion model

Reference 71

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source=pdf_text observed=2026-08-06T19:19:29.416648Z digest=sha256:2b4588a33598b616e1cb7b0c4a03d66b8f2d4422f93c621cf16175cfae4ec10a

Observation c5de7a59-d088-434c-bc24-6fa26922873b · outbound

This paper cites Enhancing efficiency of safe reinforcement learning via sample manipulation.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Enhancing efficiency of safe reinforcement learning via sample manipulation

Reference 72

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source=pdf_text observed=2026-08-06T19:19:29.418498Z digest=sha256:d68ef722994202c5dca873c5e50dfa29e37e3cff2f3777a43a41a7e88c706b7b

Observation 46eeeb28-8e94-4f3c-80ea-c5952b29cf04 · outbound

This paper cites Curriculum learning for reinforcement learning domains: A framework and survey.Journal of Machine Learning Research, 21(181):1–50, 2020.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Curriculum learning for reinforcement learning domains: A framework and survey.Journal of Machine Learning Research, 21(181):1–50, 2020

Reference 73

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source=pdf_text observed=2026-08-06T19:19:29.420529Z digest=sha256:196a61ca9f46c2f4379dfcefea50bd19ecdb7f01f89ef76d5cb1caa1b80d90fa

Observation 26abd769-ff08-447c-97a1-4a6cacf296d7 · outbound

This paper cites Causally aligned curriculum learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Causally aligned curriculum learning

Reference 74

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source=pdf_text observed=2026-08-06T19:19:29.422499Z digest=sha256:4ceebe92d58627ef62d93839cd13cc7d83c62d407b496e9b31b0b9a0c923423c

Observation 44dea0fa-db63-40bf-b85a-0142e4bb4af6 · outbound

This paper cites Au- tomated curriculum learning for neural networks.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Au- tomated curriculum learning for neural networks

Reference 75

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source=pdf_text observed=2026-08-06T19:19:29.424889Z digest=sha256:dd89bb8dc9ce7f37e0868182f3a2b25d35798a62039c70ab055590f8feb5f1d4

Observation 7f211236-c2b5-42f5-a24d-baed0cfe0a8c · outbound

This paper cites MIT press, 2016.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation MIT press, 2016

Reference 76

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source=pdf_text observed=2026-08-06T19:19:29.426837Z digest=sha256:10c6b47befa0f8e61f22eee1a6a10a068a6f4866d6898d14b47de055ef91074d

Observation 0b4402a7-9aa9-4766-b59a-a16ba0b5de03 · outbound

This paper cites Robust training with ensemble consensus.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Robust training with ensemble consensus

Reference 77

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source=pdf_text observed=2026-08-06T19:19:29.429055Z digest=sha256:e412e251789ad737efbfdc384776b22f0c461e597e38c3706c7f7d8c65038a48

Observation 3cb9dd47-d8f6-4661-b75f-d620146f0dda · outbound

This paper cites Simple and scalable predictive uncertainty estimation using deep ensembles.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Simple and scalable predictive uncertainty estimation using deep ensembles

Reference 78

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source=pdf_text observed=2026-08-06T19:19:29.430924Z digest=sha256:a88718312cb299cd0bc81e2761969e1120e820033610307fe55c91e24c9bb3bc

Observation 08ad4517-5379-48f5-a9bb-e9a489d45773 · outbound

This paper cites Improving robustness and calibration in ensembles with diversity regularization.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Improving robustness and calibration in ensembles with diversity regularization

Reference 79

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source=pdf_text observed=2026-08-06T19:19:29.432775Z digest=sha256:e58f1a829bbc9288f6ecb454cfb0d9674038d08d59098d5a75238e37511742da

Observation 8e4c9760-98c5-4ea7-bce9-973c718bbc77 · outbound

This paper cites Maximizing overall diversity for improved uncertainty estimates in deep ensembles.Proceedings of the AAAI Conference on Artificial Intelligence, 34(04):4264–4271, Apr.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Maximizing overall diversity for improved uncertainty estimates in deep ensembles.Proceedings of the AAAI Conference on Artificial Intelligence, 34(04):4264–4271, Apr

Reference 80

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source=pdf_text observed=2026-08-06T19:19:29.434936Z digest=sha256:c3b7f13657968cb0c2b88bc6bb5b206b49d1822d65990b8b854c7ebc48296325

Observation 497e7924-326b-42e8-856f-d687b10c2d4b · outbound

This paper cites Improving adversarial robustness via promoting ensemble diversity.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Improving adversarial robustness via promoting ensemble diversity

Reference 81

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source=pdf_text observed=2026-08-06T19:19:29.437314Z digest=sha256:beb702e641f3feb44780972ff12cb456f252e08e6190dda47b78bbfa5aab8a1c

Observation 98359dcb-0d9c-4d54-9794-f517139dcc7e · outbound

This paper cites Webb, Henry W.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Webb, Henry W

Reference 82

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source=pdf_text observed=2026-08-06T19:19:29.439174Z digest=sha256:7ef61cde096c71bc5a12accf428b3cbe4c86a71a163f14b8cbabc7afae3ff458

Observation 710834d2-13ba-415a-b6bd-246eb2e3a249 · outbound

This paper cites Ensemble of averages: Improv- ing model selection and boosting performance in domain generalization.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Ensemble of averages: Improv- ing model selection and boosting performance in domain generalization

Reference 83

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source=pdf_text observed=2026-08-06T19:19:29.441207Z digest=sha256:dcd009541dc7dcd78224e86547f7c1d189394ac3f0c69f9a520b1ec1260a24ce

Observation e261abd3-e9c6-43c6-ac43-171884808c09 · outbound

This paper cites Noise contrastive priors for functional uncertainty.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Noise contrastive priors for functional uncertainty

Reference 84

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source=pdf_text observed=2026-08-06T19:19:29.443024Z digest=sha256:836e3c17cf722641f390c50f03fd83557f27916d91e22fe857591f4a8ce9704e

Observation 7818270d-e5f4-46ad-8d86-1c2645b3c400 · outbound

This paper cites Deep exploration via bootstrapped dqn.Advances in neural information processing systems, 29, 2016.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Deep exploration via bootstrapped dqn.Advances in neural information processing systems, 29, 2016

Reference 85

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source=pdf_text observed=2026-08-06T19:19:29.445060Z digest=sha256:1a06cdfcbf12bee58d5f85edc47bd8b536ff3e6f46a1214e7331063d93c64778

Observation 684f6ff6-8c3c-4228-81b9-26cf183d0e63 · outbound

This paper cites Sunrise: A simple unified framework for ensemble learning in deep reinforcement learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Sunrise: A simple unified framework for ensemble learning in deep reinforcement learning

Reference 86

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source=pdf_text observed=2026-08-06T19:19:29.447135Z digest=sha256:f24e0ece786a357fa000cad76a8595802aa3684c814da99c786630158f48e5da

Observation 80a9eb5b-5761-4b2e-85d1-a21f6b0d1547 · outbound

This paper cites Accurate uncertainty estimation and decomposition in ensemble learning.Advances in Neural Information Processing Systems, 32, 2019.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Accurate uncertainty estimation and decomposition in ensemble learning.Advances in Neural Information Processing Systems, 32, 2019

Reference 87

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source=pdf_text observed=2026-08-06T19:19:29.449288Z digest=sha256:f11f0355fe23ccb3f0b4105fa6e94b077dd4676e30daec1ebe8db298bdd6a442

Observation 941e3176-5522-4b1d-aa8a-c91731d50bd6 · outbound

This paper cites Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Disentangling Epistemic and Aleatoric Uncertainty in Reinforcement Learning

Reference 88

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source=pdf_text observed=2026-08-06T19:19:29.451527Z digest=sha256:97bb5fe59fc838c344ede01ca4fa728a9526d7eab86010f554babaef1b1a037b

Observation 42e34f71-1de2-4658-8ed3-6accdde04c70 · outbound

This paper cites Kingma and Jimmy Ba.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Kingma and Jimmy Ba

Reference 89

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source=pdf_text observed=2026-08-06T19:19:29.453605Z digest=sha256:f64f238ba0f25129fe3e1076b5df8c123d57bcb4fdee075557f39fb86eb8c24c

Observation 8901a11e-c7fc-4d12-85bd-d8f69a797d87 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation Proximal Policy Optimization Algorithms

Reference 90

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source=pdf_text observed=2026-08-06T19:19:29.455963Z digest=sha256:4948d5a61c553aa6ad9366665abd3c52a8bb0ad1052a3b433553e8e4f43ff233

Observation 1b431425-3d5f-451c-b414-ff3fe25fd0c5 · outbound

This paper cites |R(s, a)−R(s′, a′)| ≤LR (s, a)−(s′, a′) ,∀(s, a),(s ′, a′)∈S×A,(19) and satisfies|R(s, a)| ≤Rmax.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation |R(s, a)−R(s′, a′)| ≤LR (s, a)−(s′, a′) ,∀(s, a),(s ′, a′)∈S×A,(19) and satisfies|R(s, a)| ≤Rmax

Reference 91

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source=pdf_text observed=2026-08-06T19:19:29.458862Z digest=sha256:5e67397c7e730c118f7fb6d258ff837d6be88438f6d0727c4451d39cda8622d8

Observation e0c46e7f-3d9e-44d3-a648-8c53cd3bca6c · outbound

This paper cites We acknowledge that real-world contact dynamics can violate global Lipschitz continuity.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation We acknowledge that real-world contact dynamics can violate global Lipschitz continuity

Reference 92

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source=pdf_text observed=2026-08-06T19:19:29.461201Z digest=sha256:b0df6f5d302ff78e10e681502061ef6c19d09ed6ae118c9745747cf3b9516a78

Observation dd71c4ac-e2c6-459b-bc1e-a08fa2317c59 · outbound

This paper cites distance.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation distance

Reference 93

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source=pdf_text observed=2026-08-06T19:19:29.463669Z digest=sha256:f97b77ca2297ef138e395923c5cb0828ef93a8c40b98fb6544be0b3e5cb1e213

Observation b8dd2bd5-6ccc-44d8-8534-bf3960160fc3 · outbound

This paper cites • Depending on the country in which research is conducted, IRB approval (or equivalent) may be required for any human subjects research.

Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation • Depending on the country in which research is conducted, IRB approval (or equivalent) may be required for any human subjects research

Reference 94

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source=pdf_text observed=2026-08-06T19:19:29.466784Z digest=sha256:a58b801d1bb58c664bc11c92b623f143a8fb330216b0ac0df3056bf2fe9b85d6

Pith citing papers

Observation 574d3609-1717-4005-9922-f229e73f6ee2 · inbound

Toward Hardware-Agnostic Quadrupedal World Models via Morphology Conditioning cites this paper.

Toward Hardware-Agnostic Quadrupedal World Models via Morphology Conditioning Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation

Reference 15

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arxiv_id, observed 2026-05-11T07:56:00.604939Z

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source=pdf_text observed=2026-05-10T16:53:48.187942Z digest=sha256:9b9c7aa3563f5fabfcfa714a8dd63c1768a2d55f4708660b7c42916aaec524d2

Observation 3d2a5ce3-47b7-41ea-91ad-ee34b05327d8 · inbound

Drift Q-Learning cites this paper.

Drift Q-Learning Safe Domain Randomization via Uncertainty-Aware Out-of-Distribution Detection and Policy Adaptation

Reference 39

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source=arxiv_source observed=2026-06-28T22:51:20.005562Z digest=sha256:d4ab330729fb0d402de81e21e4a94d6d4b664b77a086177d4ac01a9863f6c9c1