Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T04:03:57.872787Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2602.06219.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T04:03:57.872787Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
39 of 39 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation cebd7c78-9047-44b0-9a55-8ac96f97ff2d · outbound
Coupled Local and Global World Models for Efficient First Order RL Diffusion for world modeling: Visual details matter in atari.Advances in Neural Information Processing Sys- tems, 37, 2024
Reference 1
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Observation 608d48c3-97b4-4f94-8ae1-54d81e4ced4d · outbound
Coupled Local and Global World Models for Efficient First Order RL First order model-based rl through decoupled backpropagation
Reference 2
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Observation 13d19bea-9c3f-43f0-b51c-5409a67823db · outbound
Coupled Local and Global World Models for Efficient First Order RL Sample-efficient reinforce- ment learning with stochastic ensemble value expansion
Reference 3
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Observation 717707db-0e74-4b12-a98f-c20e760d5999 · outbound
Coupled Local and Global World Models for Efficient First Order RL Soloparkour: Constrained reinforcement learning for visual locomotion from privileged experience
Reference 4
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Observation fd44f585-4173-4798-89dd-648e29713ef3 · outbound
Coupled Local and Global World Models for Efficient First Order RL Cat: Constraints as terminations for legged locomotion reinforcement learning
Reference 5
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Observation 91e11f48-61b2-4a08-b27a-11f79d867a3b · outbound
Coupled Local and Global World Models for Efficient First Order RL Diffu- sion forcing: Next-token prediction meets full-sequence diffusion.Advances in Neural Information Processing Systems, 37, 2024
Reference 6
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Observation 1cd695da-a2e2-4c94-bcd5-8f8e359f0244 · outbound
Coupled Local and Global World Models for Efficient First Order RL Extreme parkour with legged robots
Reference 7
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Observation 4c4436d8-b8f3-4ee6-9ea7-e28d8d8a0941 · outbound
Coupled Local and Global World Models for Efficient First Order RL Deep reinforcement learning in a handful of trials using probabilistic dynamics models
Reference 8
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Observation 274f3b92-1545-4ad3-be73-a0b1fd2ec2c9 · outbound
Coupled Local and Global World Models for Efficient First Order RL Model- augmented actor-critic: Backpropagating through paths
Reference 9
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Observation 2efb367e-e2e2-4b4c-98d6-c0745027ebd8 · outbound
Coupled Local and Global World Models for Efficient First Order RL One Step Diffusion via Shortcut Models
Reference 10
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Observation c724f07f-d680-4eaa-8913-584157685fc4 · outbound
Coupled Local and Global World Models for Efficient First Order RL PWM: Policy Learning with Multi-Task World Models
Reference 11
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Observation 3bdc782b-677e-4961-995e-aa2203481aee · outbound
Coupled Local and Global World Models for Efficient First Order RL Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor
Reference 12
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Observation f273cae3-e53d-4d1c-8099-b10c5b7bf316 · outbound
Coupled Local and Global World Models for Efficient First Order RL Soft Actor-Critic Algorithms and Applications
Reference 13
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Observation 8ed3ffc5-301e-433f-ad70-63d8859bbd60 · outbound
Coupled Local and Global World Models for Efficient First Order RL Mastering atari with discrete world models
Reference 14
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Observation 1797ab77-6b56-453b-9833-8cf4aadf30b5 · outbound
Coupled Local and Global World Models for Efficient First Order RL Mastering diverse control tasks through world models.Nature, 640(8059):647–653, 2025
Reference 15
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Observation 1dae7f2e-5e52-447f-ad6b-0dc8b684048c · outbound
Coupled Local and Global World Models for Efficient First Order RL Training Agents Inside of Scalable World Models
Reference 17
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Observation 8bd46494-f7ad-4d65-843d-ebdc11dad254 · outbound
Coupled Local and Global World Models for Efficient First Order RL Temporal difference learning for model predictive control
Reference 18
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Observation b294454d-15bb-4b10-908a-2439cc741e2a · outbound
Coupled Local and Global World Models for Efficient First Order RL Td-mpc2: Scalable, robust world models for continuous control
Reference 19
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Unavailable: canonical work link unavailable.
Observation f2d99499-4fa2-432b-abe9-c8419db54712 · outbound
Coupled Local and Global World Models for Efficient First Order RL Axial attention in multidimensional transformers
Reference 20
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Observation 7894fed2-e8ea-468b-ab6a-011544c9e6a7 · outbound
Coupled Local and Global World Models for Efficient First Order RL Anymal parkour: Learning agile navigation for quadrupedal robots.Science Robotics, 9(88), 2024
Reference 21
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Observation 3a485370-5fbd-4fd7-9c99-f655702be553 · outbound
Coupled Local and Global World Models for Efficient First Order RL When to trust your model: Model-based policy optimization.Advances in neural information processing systems, 32, 2019
Reference 22
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Observation 2ef21bb8-960e-4aaa-ae35-38e21a5bd598 · outbound
Coupled Local and Global World Models for Efficient First Order RL An introduction to zero-order op- timization techniques for robotics.arXiv preprint arXiv:2506.22087, 2025
Reference 23
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Observation ccabee6a-3e02-44cf-9d84-af06f7ee6482 · outbound
Coupled Local and Global World Models for Efficient First Order RL Elucidating the design space of diffusion-based genera- tive models.Advances in neural information processing systems, 35, 2022
Reference 24
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Observation df6bf141-15b5-44d8-9223-40f48002be56 · outbound
Coupled Local and Global World Models for Efficient First Order RL Worldplanner: Monte carlo tree search and mpc with action-conditioned visual world models, 2025
Reference 25
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Observation 7492b502-ac9d-46c7-8e19-84a0a6989370 · outbound
Coupled Local and Global World Models for Efficient First Order RL Auto-encoding variational bayes
Reference 26
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Observation e0761d95-cec3-4e75-ac75-d3b31b234931 · outbound
Coupled Local and Global World Models for Efficient First Order RL Model-ensemble trust-region policy optimization
Reference 27
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Observation 7fc70c44-37dd-40bb-921f-be63a0b09f29 · outbound
Coupled Local and Global World Models for Efficient First Order RL Investigating Compounding Prediction Errors in Learned Dynamics Models
Reference 28
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Observation b6976a91-c4cc-45fc-8d59-41aaaccc3f66 · outbound
Coupled Local and Global World Models for Efficient First Order RL Uncertainty-aware robotic world model makes offline model-based reinforcement learning work on real robots, 2025
Reference 29
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Unavailable: canonical work link unavailable.
Observation 05e9cd88-4604-4802-b826-dc9ca8633bd0 · outbound
Coupled Local and Global World Models for Efficient First Order RL Lightzero: A unified benchmark for monte carlo tree search in general sequential decision scenarios.Advances in Neural Information Processing Systems, 36, 2024
Reference 30
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Observation 0386dd37-9f4a-4a13-a693-4c3b69f845db · outbound
Coupled Local and Global World Models for Efficient First Order RL UniZero: Generalized and Efficient Planning with Scalable Latent World Models
Reference 31
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Unavailable: canonical work link unavailable.
Observation 405f2d97-f906-405a-87e0-74cc059c0235 · outbound
Coupled Local and Global World Models for Efficient First Order RL Mastering atari, go, chess and shogi by planning with a learned model.Nature, 588(7839):604– 609, 2020
Reference 32
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Observation 6356dc6a-a18e-4fb4-9367-af66dd7ac47b · outbound
Coupled Local and Global World Models for Efficient First Order RL Proximal Policy Optimization Algorithms
Reference 33
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Observation 9a25fdc2-75bd-4c72-a838-842dd2ab67b2 · outbound
Coupled Local and Global World Models for Efficient First Order RL Daydreamer: World models for physical robot learning
Reference 34
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Observation ffeffede-261d-4132-aaac-cf171f13466e · outbound
Coupled Local and Global World Models for Efficient First Order RL Learning to combat compounding- error in model-based reinforcement learning, 2019
Reference 35
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Observation d091cfb9-1912-45bc-a529-f29e813084e4 · outbound
Coupled Local and Global World Models for Efficient First Order RL Stabilizing rein- forcement learning in differentiable multiphysics simula- tion.International Conference on Learning Representa- tions (ICLR), 2025
Reference 36
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Observation 4445579d-62d0-436d-8a35-942cc6bcfa18 · outbound
Coupled Local and Global World Models for Efficient First Order RL Rank2reward: Learning shaped reward functions from passive video
Reference 37
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Observation 306fc9f4-dff9-4422-a5e2-76d025c93d45 · outbound
Coupled Local and Global World Models for Efficient First Order RL Zhao, Vikash Kumar, Sergey Levine, and Chelsea Finn
Reference 38
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Observation 087ca447-38d7-4023-9947-fc8b91fecbf6 · outbound
Coupled Local and Global World Models for Efficient First Order RL Sim-to-real transfer in deep reinforcement learning for robotics: a survey
Reference 39
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Observation 6799c458-a3c1-45b7-a582-e722a8acc9be · outbound
Coupled Local and Global World Models for Efficient First Order RL Robot Parkour Learning
Reference 40
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No inbound Pith citation observations are available.