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Paper Citation Record · LEDGER

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

As of 16 August 2026, this Paper Citation Record lists 100 of 299 outbound references and 28 inbound Pith citation observations for arXiv:2507.00917.

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

pith.paper-citation-record.v1
2507.00917 v3

Coverage vector

measured 100 of 299 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:08:58.007269Z

measured 128 of 128 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T04:17:35.717037Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T13:14:53.255674Z

Reference resolution

100 of 299 outbound references displayed

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  • verified fuzzy0
  • unresolved100
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 4108ae77-c57d-497c-b9c4-3f319949c8a5 · outbound

This paper cites GPT-4 Technical Report.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models GPT-4 Technical Report

Reference 1

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Observation 58afac07-b523-4298-9b66-cde8e9ef728f · outbound

This paper cites DeepSeek-V3 Technical Report.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models DeepSeek-V3 Technical Report

Reference 2

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Observation d845da8c-e09a-45b3-afba-a406bdd7ddea · outbound

This paper cites Diffusion policy: Visuomotor policy learning via action diffusion,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Diffusion policy: Visuomotor policy learning via action diffusion,

Reference 3

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Observation c07ac234-8988-4dcd-a1b5-3179ef4bcfbc · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models OpenVLA: An Open-Source Vision-Language-Action Model

Reference 4

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Observation 2d662618-8d24-42b1-ba5b-d5061590909c · outbound

This paper cites Advancements in hu- manoid robots: A comprehensive review and future prospects,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Advancements in hu- manoid robots: A comprehensive review and future prospects,

Reference 5

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Observation 917af46e-51a3-4a47-8952-7cf343adf1b6 · outbound

This paper cites HumanPlus: Humanoid Shadowing and Imitation from Humans.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models HumanPlus: Humanoid Shadowing and Imitation from Humans

Reference 6

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Observation 7da3a572-63e7-4277-ba6d-bd222ed6090e · outbound

This paper cites Assistive social robots in elderly care: a review,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Assistive social robots in elderly care: a review,

Reference 7

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Observation bf485ec7-a036-4a20-a7c2-35c0fb2d2976 · outbound

This paper cites A decade retrospective of medical robotics research from 2010 to 2020,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models A decade retrospective of medical robotics research from 2010 to 2020,

Reference 8

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source=pdf_text observed=2026-08-06T21:08:46.582146Z digest=sha256:2086d708d710feaa211ca0d39324c9fcdc5413c20c4d0fa0cc0b056bf74e737c

Observation ce5243f4-f72d-407f-ab27-f036d585b239 · outbound

This paper cites Disaster robotics,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Disaster robotics,

Reference 9

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source=pdf_text observed=2026-08-06T21:08:46.720087Z digest=sha256:09a213cd5b2f8c4d0a854bc95ab188eead6ae231028112b942a10406c9027f6c

Observation ccee311a-471d-49f2-8ce5-f05515aad5cd · outbound

This paper cites Social robots for education: A review,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Social robots for education: A review,

Reference 10

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Observation 9fd44ee9-43a2-4cb0-a4a9-8e537619b00b · outbound

This paper cites The darpa robotics chal- lenge finals: Results and perspectives,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models The darpa robotics chal- lenge finals: Results and perspectives,

Reference 11

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source=pdf_text observed=2026-08-06T21:08:46.922712Z digest=sha256:72929a82463a9c97a30b7571f9ea97f22f7ab42d0229633b673e9a41ec14e894

Observation 2ac72f74-ccd7-40e4-a1b4-ff703854270b · outbound

This paper cites 13 482, 2014.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models 13 482, 2014

Reference 12

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source=pdf_text observed=2026-08-06T21:08:47.070724Z digest=sha256:f4796e1b035171069d802f7615fa9f058672a83ef1f32458470e386050915da7

Observation 781a6fac-c0c4-4eee-a0ba-7bc12867479f · outbound

This paper cites A framework for autonomy levels for unmanned systems (alfus),.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models A framework for autonomy levels for unmanned systems (alfus),

Reference 13

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Observation 2319edeb-0826-4fe2-a0fe-2285bfe9028b · outbound

This paper cites Toward a framework for levels of robot autonomy in human-robot interaction,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Toward a framework for levels of robot autonomy in human-robot interaction,

Reference 14

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Observation 08db78aa-9e30-40a4-ac90-5a6455a9dd3d · outbound

This paper cites Design and use paradigms for gazebo, an open-source multi-robot simulator,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Design and use paradigms for gazebo, an open-source multi-robot simulator,

Reference 15

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source=pdf_text observed=2026-08-06T21:08:47.455585Z digest=sha256:b64fee300b19f4a1382fce3a4a73a563bd4f96d1ebeecc1c09d53aac20ae3e82

Observation bbb5f6e1-4f52-4a54-8069-0f240ab35cc8 · outbound

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

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Mujoco: A physics engine for model-based control,

Reference 16

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Observation 798ad0c5-bde0-408e-9a5a-600361a2b4b5 · outbound

This paper cites (n.d.) World models.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models (n.d.) World models

Reference 17

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source=pdf_text observed=2026-08-06T21:08:47.582199Z digest=sha256:81103077d51d38ea8a893578953ecc6eb60effb162abffc9867c01b5ad532e21

Observation 7bf1802e-aef3-4642-b0ad-de263850b711 · outbound

This paper cites World Models.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models World Models

Reference 18

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source=pdf_text observed=2026-08-06T21:08:47.629666Z digest=sha256:2c9353abd6a40652004fa1f5c64c40d8bc2946f3968fce82a85e5782e871589b

Observation 11f0afbc-f912-43ac-ac5e-827b22c802c1 · outbound

This paper cites A survey of em- bodied ai: From simulators to research tasks,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models A survey of em- bodied ai: From simulators to research tasks,

Reference 19

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source=pdf_text observed=2026-08-06T21:08:47.675092Z digest=sha256:2ed44d369f60f2f8ae952f7a0360a775b2daf9862dca04625634f38923ab95d1

Observation fe6a7804-f867-46ad-818d-fd61a67fd152 · outbound

This paper cites Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Aligning Cyber Space with Physical World: A Comprehensive Survey on Embodied AI

Reference 20

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Observation fc015907-c051-4655-9331-5c2a25074a95 · outbound

This paper cites A review of physics simulators for robotic applications,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models A review of physics simulators for robotic applications,

Reference 21

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Observation cdb5060f-539d-49df-9f67-5004b8dcd90c · outbound

This paper cites Is sora a world simulator? a comprehensive survey on general world models and beyond,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Is sora a world simulator? a comprehensive survey on general world models and beyond,

Reference 22

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Observation fd12e0e5-11a7-4f15-9693-e8281f7034ae · outbound

This paper cites Understanding world or predicting future? a comprehensive survey of world models,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Understanding world or predicting future? a comprehensive survey of world models,

Reference 23

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Observation 0ee651f0-2aae-4000-b5ae-024cdab8b444 · outbound

This paper cites From Efficient Multimodal Models to World Models: A Survey.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models From Efficient Multimodal Models to World Models: A Survey

Reference 24

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source=pdf_text observed=2026-08-06T21:08:48.013615Z digest=sha256:7e77186dabf473c05c3c86e21aa8c5b9edcfbe31291ef52dbde0c1b8a8dee597

Observation cd15ab2e-252e-4133-8a79-d0f6fe5bcb7d · outbound

This paper cites Siciliano and O.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Siciliano and O

Reference 25

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source=pdf_text observed=2026-08-06T21:08:48.100545Z digest=sha256:33a9cff43792e2fcef47c51d5caebe3164eee1e1926435fa03d2ceb63de11ae6

Observation 2ae2ce92-fabc-4ae7-83a4-9fbd42d0c51d · outbound

This paper cites an unresolved cited work.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Unresolved cited work

Reference 26

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source=pdf_text observed=2026-08-06T21:08:48.290296Z digest=sha256:31d6172ffc1e99be7a6ec3d321154f912663927fa42bb350d0a2c7de44972f9b

Observation da63efe3-ae9d-445e-8395-eec18a4da6f4 · outbound

This paper cites Behavior Trees in Robotics and AI: An Introduction.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Behavior Trees in Robotics and AI: An Introduction

Reference 27

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source=pdf_text observed=2026-08-06T21:08:48.441500Z digest=sha256:c72b3331a339dfb751d3b3cdd0685aeb37177ac762f4d640f3845f219c70ed41

Observation 847db5f6-8ee7-4157-a393-d30547525ba3 · outbound

This paper cites an unresolved cited work.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Unresolved cited work

Reference 28

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source=pdf_text observed=2026-08-06T21:08:48.578182Z digest=sha256:ed2a615c3f328d96e5e4d1d136281730b1c51644208d3501704758b6a08a47c6

Observation c4df7c97-95e2-4129-b204-be580ef1d187 · outbound

This paper cites Model predictive control of legged and humanoid robots: models and algorithms,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Model predictive control of legged and humanoid robots: models and algorithms,

Reference 29

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source=pdf_text observed=2026-08-06T21:08:48.704338Z digest=sha256:7a7912066f18ac09475e546cdad5b2f245245dc1b3f73ebdb7e83f66f851f005

Observation cc8b3477-2315-4a7b-8554-d630aa8ffaff · outbound

This paper cites An integrated system for real-time model predictive control of humanoid robots,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models An integrated system for real-time model predictive control of humanoid robots,

Reference 30

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Observation 31892b44-31ae-446e-aace-31739c4536e6 · outbound

This paper cites Whole-body model-predictive control applied to the hrp-2 humanoid,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Whole-body model-predictive control applied to the hrp-2 humanoid,

Reference 31

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source=pdf_text observed=2026-08-06T21:08:48.955925Z digest=sha256:8f0b343d581d911fcf2ec0699831c06fe28c3ee017ded6a3e5070d6869134d4f

Observation 30154771-51db-430a-ab69-36158adc32aa · outbound

This paper cites Goswami and P.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Goswami and P

Reference 32

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source=pdf_text observed=2026-08-06T21:08:49.130420Z digest=sha256:0673fcbf5196c1c6592616a8486616002a1704822a0410367be2e2a98390d067

Observation c6d82550-0826-46e9-8623-3f679232ba47 · outbound

This paper cites A whole-body control framework for humanoids operating in human environments,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models A whole-body control framework for humanoids operating in human environments,

Reference 33

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source=pdf_text observed=2026-08-06T21:08:49.353530Z digest=sha256:c2de808c7efb35ec1d4e4aeab995db69125a9b138937b7e84f0b1bee84ae2b6f

Observation eca63aff-4c9e-4db0-a14e-160647e1ed46 · outbound

This paper cites Hierarchical quadratic programming: Fast online humanoid-robot motion generation,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Hierarchical quadratic programming: Fast online humanoid-robot motion generation,

Reference 34

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source=pdf_text observed=2026-08-06T21:08:49.595627Z digest=sha256:b812845b0dfcaff62c1371ef267ab7f36c1e0e998a4690d081b9eab68d91c350

Observation e516c511-6b35-4fd9-871c-236b560eb618 · outbound

This paper cites Optimization- based locomotion planning, estimation, and control design for the atlas humanoid robot,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Optimization- based locomotion planning, estimation, and control design for the atlas humanoid robot,

Reference 35

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source=pdf_text observed=2026-08-06T21:08:49.763155Z digest=sha256:2b2e34d7fdb0d1f18589ccf2138e51fdd31d66e51c6f1ad674007bb88e481ed6

Observation 02bec01a-7076-4e13-8074-866d8f223ca5 · outbound

This paper cites Compliant lo- comotion using whole-body control and divergent component of motion tracking,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Compliant lo- comotion using whole-body control and divergent component of motion tracking,

Reference 36

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source=pdf_text observed=2026-08-06T21:08:49.882367Z digest=sha256:73467cff920c8bf7ee5052830524d4c5e0c1d6c7ff7307ef1d3b4b1b25190514

Observation 8e6e1fd5-86b0-44c2-8305-96061180b29a · outbound

This paper cites ExBody2: Advanced Expressive Humanoid Whole-Body Control.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models ExBody2: Advanced Expressive Humanoid Whole-Body Control

Reference 37

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source=pdf_text observed=2026-08-06T21:08:50.081130Z digest=sha256:fc8a44699e0ef82c7f3ef6ad5c566ec99dae360518ed8d4a5b9139e3cc71db59

Observation ea3fcc9e-9875-4c12-8f0d-600cf16d2126 · outbound

This paper cites A Unified and General Humanoid Whole-Body Controller for Versatile Locomotion.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models A Unified and General Humanoid Whole-Body Controller for Versatile Locomotion

Reference 38

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source=pdf_text observed=2026-08-06T21:08:50.219048Z digest=sha256:8424e4c59aad915caf20d5ad3931de832958b1539f8a2b0ca2c44d1dfb58aadc

Observation 08f6c58f-2da8-4a57-bbf1-946aa83a8d9e · outbound

This paper cites Reinforcement learning in robotics: A survey,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Reinforcement learning in robotics: A survey,

Reference 39

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source=pdf_text observed=2026-08-06T21:08:50.315790Z digest=sha256:71730dcad6f91e2e86be9ae4cf24b1468db3093d82ab8b13f5391e7fdf5978b5

Observation e80564ca-5c9c-4b67-9a79-d40d77afad45 · outbound

This paper cites Model learning for robot con- trol: a survey,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Model learning for robot con- trol: a survey,

Reference 40

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source=pdf_text observed=2026-08-06T21:08:50.380856Z digest=sha256:bdefd8f8e9c51356832a0047a4003be79edac01601de052256f660058c9e9aae

Observation d1274318-13aa-49d5-b9bf-7409d306fc17 · outbound

This paper cites Develop- ment of a bipedal humanoid robot-control method of whole body cooperative dynamic biped walking,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Develop- ment of a bipedal humanoid robot-control method of whole body cooperative dynamic biped walking,

Reference 41

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source=pdf_text observed=2026-08-06T21:08:50.554738Z digest=sha256:385c95a3a4ef681263e5054b0d2acd3be4eda4daa335e7adfbc1fb71ce0c868e

Observation 63bc61ea-1934-4ef9-9883-4aa2843fe1be · outbound

This paper cites Learning-based legged locomotion: State of the art and future perspectives,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Learning-based legged locomotion: State of the art and future perspectives,

Reference 42

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Observation 1cd6e4ba-a71b-4296-95d0-5eb446cb288f · outbound

This paper cites Reinforcement learning of dynamic motor sequence: Learning to stand up,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Reinforcement learning of dynamic motor sequence: Learning to stand up,

Reference 43

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source=pdf_text observed=2026-08-06T21:08:50.851544Z digest=sha256:7af45b175c7d9df15acc2f111b3368e2a2fb7145183392100df15735eb95c8c8

Observation 025c26fc-1f63-49ed-9c04-55273d2876d6 · outbound

This paper cites Deeploco: Dynamic locomotion skills using hierarchical deep reinforcement learning,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Deeploco: Dynamic locomotion skills using hierarchical deep reinforcement learning,

Reference 44

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source=pdf_text observed=2026-08-06T21:08:50.953637Z digest=sha256:f4fb020834ec872352233094c9b2bbbccf361b847a53b4c10fb451c8bebe01c3

Observation d1dd0cd0-bae5-4003-8bd1-bdcba029426b · outbound

This paper cites Learning symmetric and low- energy locomotion,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Learning symmetric and low- energy locomotion,

Reference 45

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source=pdf_text observed=2026-08-06T21:08:51.136667Z digest=sha256:699bba86b3c6664985eec69694d446b4b69d1c1b186cef692ae1ad3befcd0d8e

Observation 6d1d8f6a-be14-4d7d-82ec-c45a0076437f · outbound

This paper cites Emergence of Locomotion Behaviours in Rich Environments.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Emergence of Locomotion Behaviours in Rich Environments

Reference 46

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source=pdf_text observed=2026-08-06T21:08:51.273499Z digest=sha256:99c9fe5e7f2a94056ea91eeca8c5b379d5491ba9b721a97ca9df8b3d93ccc814

Observation 230d3b0e-6708-489c-94a9-98c281bb0b21 · outbound

This paper cites Iterative Reinforcement Learning Based Design of Dynamic Locomotion Skills for Cassie.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Iterative Reinforcement Learning Based Design of Dynamic Locomotion Skills for Cassie

Reference 47

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source=pdf_text observed=2026-08-06T21:08:51.356775Z digest=sha256:029e5683534077f3cedffa59849ad6e202f90fdf7f2f7ed6a3bd8276d8c5d424

Observation 48319211-7fff-4bdb-bd4d-7394a3b916e0 · outbound

This paper cites 3d diffusion policy,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models 3d diffusion policy,

Reference 48

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source=pdf_text observed=2026-08-06T21:08:51.487320Z digest=sha256:6f4a1ceb378a6b15092799129f1b2c5681f75bee547fce3d19507e54a894f25f

Observation 4d52e92e-8ffc-49fc-a3a6-10c84e2c785d · outbound

This paper cites Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

Reference 49

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source=pdf_text observed=2026-08-06T21:08:51.573828Z digest=sha256:2ec895b7b2a22c6e7097c679a71f00298ede7197c2f73d43dc51cd1c35c74d10

Observation 7935683b-880f-4964-9c3f-841fbde44f68 · outbound

This paper cites RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation

Reference 50

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source=pdf_text observed=2026-08-06T21:08:51.689112Z digest=sha256:984e99358e639eccdfbc314a1bd38b30f3b8d3612f4233164719870d249471d6

Observation d60b0c15-0491-4b63-b238-73d16bb7ee93 · outbound

This paper cites DiffuseLoco: Real-Time Legged Locomotion Control with Diffusion from Offline Datasets.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models DiffuseLoco: Real-Time Legged Locomotion Control with Diffusion from Offline Datasets

Reference 51

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source=pdf_text observed=2026-08-06T21:08:51.786466Z digest=sha256:af793ec03e5fbdeb2dc304c02c919ca4a094ef6ee75bd94f57ae4ee99cfd1945

Observation be4a39d7-5372-4367-b409-4425f272a1d4 · outbound

This paper cites Amp: Adversarial motion priors for stylized physics-based character control,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Amp: Adversarial motion priors for stylized physics-based character control,

Reference 52

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source=pdf_text observed=2026-08-06T21:08:51.875025Z digest=sha256:84f9ee5910754ad76c48867c5032849e421b3b0f794ad3a23efa34da91ce0536

Observation b6f6fe28-c1d2-42b5-99b7-53e776fc12d3 · outbound

This paper cites Whole-body humanoid robot locomotion with human reference,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Whole-body humanoid robot locomotion with human reference,

Reference 53

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source=pdf_text observed=2026-08-06T21:08:51.955267Z digest=sha256:3a04d2d0bdbff4840848617f2a8aba3d7afb09d3d217b68cad28133962f8961c

Observation 4a4c7382-ebca-4112-a818-f19c7831a18b · outbound

This paper cites DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models DexCap: Scalable and Portable Mocap Data Collection System for Dexterous Manipulation

Reference 54

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source=pdf_text observed=2026-08-06T21:08:52.081916Z digest=sha256:e7fba4779662291d08b8a13282f1ba87f236fd19783ae7ad6cb1cde8c4333561

Observation d9ed0028-56a4-42b8-9b12-4e633be7e783 · outbound

This paper cites Open-TeleVision: Teleoperation with Immersive Active Visual Feedback.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Open-TeleVision: Teleoperation with Immersive Active Visual Feedback

Reference 55

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source=pdf_text observed=2026-08-06T21:08:52.213372Z digest=sha256:15c38a88cb0945cb604c61780f62c0320a6d18d8131e2b57d4c9a72e50aee1be

Observation aa1cd01d-0375-472e-9bb1-feb1f80108c6 · outbound

This paper cites Visual Imitation Enables Contextual Humanoid Control.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Visual Imitation Enables Contextual Humanoid Control

Reference 56

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source=pdf_text observed=2026-08-06T21:08:52.326582Z digest=sha256:3bea50fe13b88efc79ed5c1c64260c436c368c84c96fe0c35681f263ce489b45

Observation 2a7e93cc-47f5-428a-97fd-285b051b3b58 · outbound

This paper cites Compliant terrain adaptation for biped humanoids without measuring ground surface and contact forces,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Compliant terrain adaptation for biped humanoids without measuring ground surface and contact forces,

Reference 57

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source=pdf_text observed=2026-08-06T21:08:52.456650Z digest=sha256:ac5313753542c7f18e960463802310646ea0999c677f75dc4ad90bc5c6a4e403

Observation 52b5a7b4-d149-41c4-902b-95a8fbc41327 · outbound

This paper cites Practical bipedal walking control on uneven terrain using surface learning and push recovery,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Practical bipedal walking control on uneven terrain using surface learning and push recovery,

Reference 58

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source=pdf_text observed=2026-08-06T21:08:52.586466Z digest=sha256:ea7c70b4c0f616c68337cba5b832a7ea3b1c71ed51ac6efc015c6d25bf5cc099

Observation f4d1c328-36b8-4e76-aabc-859d72f4b555 · outbound

This paper cites Dynamic walking with compliance on a cassie bipedal robot,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Dynamic walking with compliance on a cassie bipedal robot,

Reference 59

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source=pdf_text observed=2026-08-06T21:08:52.707601Z digest=sha256:c50d3d7fe2489b09c83f92b475992aa28950c8cc0da601f24b8268697208bdb5

Observation ae75da7f-e178-4c69-b81d-1002fd75f096 · outbound

This paper cites Dynamic walking on compliant and uneven terrain us- ing dcm and passivity-based whole-body control,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Dynamic walking on compliant and uneven terrain us- ing dcm and passivity-based whole-body control,

Reference 60

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source=pdf_text observed=2026-08-06T21:08:52.811170Z digest=sha256:491ef8af546d1736a512ce45ab9cca1fc763696fb6a25cd97b17e65724d1538f

Observation 12979010-6fee-4fda-b9c2-8397b11b6214 · outbound

This paper cites Blind bipedal stair traversal via sim-to-real reinforcement learning,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Blind bipedal stair traversal via sim-to-real reinforcement learning,

Reference 61

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source=pdf_text observed=2026-08-06T21:08:52.956980Z digest=sha256:fe8d419666e3ccc96c305fd19b0a1d89f44377b56ee5fa616fa8dbed96b7eaaf

Observation b0cef45f-43ad-43c7-8239-bcd7b44b0634 · outbound

This paper cites Efficient anytime clf reactive planning system for a bipedal robot on undulating terrain,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Efficient anytime clf reactive planning system for a bipedal robot on undulating terrain,

Reference 62

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source=pdf_text observed=2026-08-06T21:08:53.086407Z digest=sha256:0434ea326d4b709ad34d1b9ee91fad458cbc0ae52f6777ef8dcdb67584341feb

Observation 975c1ecb-8da8-4ea7-badb-8c65bc484f66 · outbound

This paper cites Learning vision-based bipedal locomotion for chal- lenging terrain,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Learning vision-based bipedal locomotion for chal- lenging terrain,

Reference 63

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source=pdf_text observed=2026-08-06T21:08:53.217326Z digest=sha256:2470d0a8162888df27c63608158813e59ba97ce512f52b7bea88baeeef493f9b

Observation 6bfdca88-2ce2-4c2d-8ab4-b4a8d8138f9b · outbound

This paper cites Humanoid Parkour Learning.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Humanoid Parkour Learning

Reference 64

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source=pdf_text observed=2026-08-06T21:08:53.337106Z digest=sha256:78c25e11ad53aa9d02813b39cab04d5664c94a959b5e181b5af8d6755b225388

Observation eda7565f-aa49-47f0-ace1-bf2b45cdf9bd · outbound

This paper cites Rt-2: Vision-language-action models transfer web knowledge to robotic control,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Rt-2: Vision-language-action models transfer web knowledge to robotic control,

Reference 65

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source=pdf_text observed=2026-08-06T21:08:53.457017Z digest=sha256:cd7b61f6e2a3c1227c610e79f2dfc0e282a05d6343de58221d1611bbd62d7ce4

Observation 21d4acac-a0e5-447a-8c71-a4e49754acb8 · outbound

This paper cites 3D-VLA: A 3D Vision-Language-Action Generative World Model.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models 3D-VLA: A 3D Vision-Language-Action Generative World Model

Reference 66

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source=pdf_text observed=2026-08-06T21:08:53.614836Z digest=sha256:3983166e252c8180b0c1d4815d62ca4b8c7c37ed3a05821b23dd25921bdf016e

Observation edf2b406-3e00-4a10-9121-748f755e6b54 · outbound

This paper cites Magma: A Foundation Model for Multimodal AI Agents.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Magma: A Foundation Model for Multimodal AI Agents

Reference 67

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source=pdf_text observed=2026-08-06T21:08:53.705343Z digest=sha256:4ea99b1d04dc87e039196bfddcdea5e57c88d8daf3b8da46fcc22b12e603e3de

Observation 837eedda-0a74-4cfc-8ca7-d0f3016901a8 · outbound

This paper cites FAST: Efficient Action Tokenization for Vision-Language-Action Models.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models FAST: Efficient Action Tokenization for Vision-Language-Action Models

Reference 69

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source=pdf_text observed=2026-08-06T21:08:53.920323Z digest=sha256:5ab0ff4a6c1b220870a0cb2b2134631da158ebcb5852229a2693dbb0bfe86ce5

Observation a44cbd05-75c9-452f-83f6-6b4abc9566fc · outbound

This paper cites Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models

Reference 70

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source=pdf_text observed=2026-08-06T21:08:54.058239Z digest=sha256:3a54a77b2122392d762ea681eb94d5c3b00e14055126af4fb2c4860d93e4831e

Observation c4c9404c-31e1-4818-871a-d00e6105a78d · outbound

This paper cites TinyVLA: Towards Fast, Data-Efficient Vision-Language-Action Models for Robotic Manipulation.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models TinyVLA: Towards Fast, Data-Efficient Vision-Language-Action Models for Robotic Manipulation

Reference 71

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source=pdf_text observed=2026-08-06T21:08:54.216140Z digest=sha256:299b7b8026b8e318b7b2074a716ca128cbc8f4d81a4e77a8d63cd8b50353ee35

Observation 8ca05710-5b10-4a4b-96bc-3ef9f7fbe8af · outbound

This paper cites Vision- language-action models: Concepts, progress, applications and challenges,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Vision- language-action models: Concepts, progress, applications and challenges,

Reference 72

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source=pdf_text observed=2026-08-06T21:08:54.359357Z digest=sha256:35be3c3e0e02b54cebce3ed3c80639b024ddd79c8cedf6600980e5e49c1faefd

Observation 34043bbf-1c8f-4728-acab-c4670236c76c · outbound

This paper cites Optimizing human motion for the control of a humanoid robot,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Optimizing human motion for the control of a humanoid robot,

Reference 73

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source=pdf_text observed=2026-08-06T21:08:54.530183Z digest=sha256:d2cb74f270b4665a0f0cf7b48d158c91d63ea4b170dbdcf1df9b02b016a86162

Observation 70456b00-3558-4c29-b02d-9a0e05ede20d · outbound

This paper cites Online learning of uneven terrain for humanoid bipedal walking,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Online learning of uneven terrain for humanoid bipedal walking,

Reference 74

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source=pdf_text observed=2026-08-06T21:08:54.610079Z digest=sha256:2a2784859504236d816fa16618257d8949820b28cb92df0a8564885d6845c851

Observation f91dda5a-90ed-487b-b8e5-d91699df61df · outbound

This paper cites Biped walking stabi- lization based on linear inverted pendulum tracking,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Biped walking stabi- lization based on linear inverted pendulum tracking,

Reference 75

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source=pdf_text observed=2026-08-06T21:08:54.746153Z digest=sha256:e6e83f412902d3008093f8e5e0c71f91c3e6eb2b38d4b6a67394d2d839b82720

Observation 0a03eec1-ef0a-4354-af6b-b6709879e913 · outbound

This paper cites Dynamic balance force control for compliant humanoid robots,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Dynamic balance force control for compliant humanoid robots,

Reference 76

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source=pdf_text observed=2026-08-06T21:08:54.860755Z digest=sha256:4b29ea01d3804983587713bd03f40b1730f87e1fb46be15bb0812ae4ad284495

Observation 822c5b70-1ad2-4d3f-95ea-3ae6bd5f0e30 · outbound

This paper cites Adaptive force- based control for legged robots,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Adaptive force- based control for legged robots,

Reference 77

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source=pdf_text observed=2026-08-06T21:08:54.972967Z digest=sha256:7cdc53d18f8f1513d6f70c7a39e96f40a5e5776719304ad137dbcc77cf9916f7

Observation a4913f7b-68f5-4863-9db3-0f15cc125f0f · outbound

This paper cites Passivity-based whole-body balancing for torque-controlled humanoid robots in multi-contact scenarios,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Passivity-based whole-body balancing for torque-controlled humanoid robots in multi-contact scenarios,

Reference 78

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Observation ef91dd32-593a-4f4e-89e9-3f8ca424c529 · outbound

This paper cites Bipedal hopping: Reduced-order model embedding via optimization-based control,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Bipedal hopping: Reduced-order model embedding via optimization-based control,

Reference 79

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Observation 5c67b8de-d210-4f22-aaf2-8ddcf9b1d893 · outbound

This paper cites Vertical jump of a humanoid robot with cop-guided angular momentum control and impact absorption,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Vertical jump of a humanoid robot with cop-guided angular momentum control and impact absorption,

Reference 80

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Observation 67389545-27de-4d33-a393-fa736b637053 · outbound

This paper cites Optimizing bipedal locomotion for the 100m dash with com- parison to human running,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Optimizing bipedal locomotion for the 100m dash with com- parison to human running,

Reference 81

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Observation 019f556f-216e-43f3-afcb-c68a9923f5ea · outbound

This paper cites Reinforcement learning for versatile, dynamic, and robust bipedal locomotion control,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Reinforcement learning for versatile, dynamic, and robust bipedal locomotion control,

Reference 82

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Observation 2dbb141c-a0a8-46a0-8681-6d4ab755006e · outbound

This paper cites Cdm-mpc: An integrated dynamic planning and control framework for bipedal robots jumping,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Cdm-mpc: An integrated dynamic planning and control framework for bipedal robots jumping,

Reference 83

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Observation cb198c78-8f09-42a9-addc-462ac43c789a · outbound

This paper cites ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models ASAP: Aligning Simulation and Real-World Physics for Learning Agile Humanoid Whole-Body Skills

Reference 84

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Observation c16d97dc-ae41-447e-8e1a-010f419a7efb · outbound

This paper cites Fast contact-implicit model predictive control,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Fast contact-implicit model predictive control,

Reference 85

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Observation 7d56e9f1-9084-4baf-97fa-7de0b3b13fb6 · outbound

This paper cites Learning quadrupedal locomotion over challenging terrain,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Learning quadrupedal locomotion over challenging terrain,

Reference 86

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Observation e34d277a-2258-4e82-9b69-67e5d52caa04 · outbound

This paper cites Recent progress in legged robots locomotion control,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Recent progress in legged robots locomotion control,

Reference 87

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source=pdf_text observed=2026-08-06T21:08:56.230455Z digest=sha256:f0853f5545413ae02e1c40f17033180f8c088a1bc3202070a58fae43766c17ab

Observation 0ddc8873-1d51-438b-9395-348eb13f75cc · outbound

This paper cites Learning Humanoid Locomotion with Perceptive Internal Model.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Learning Humanoid Locomotion with Perceptive Internal Model

Reference 88

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source=pdf_text observed=2026-08-06T21:08:56.329953Z digest=sha256:ed1ab1c81bfb417a1d0d92abe6fe814f3b2774a03b87a159c735412142fcbe20

Observation 7e689a19-3c58-410e-a587-3b06a7649670 · outbound

This paper cites Unified modeling and control of walking and running on the spring-loaded in- verted pendulum,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Unified modeling and control of walking and running on the spring-loaded in- verted pendulum,

Reference 89

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source=pdf_text observed=2026-08-06T21:08:56.475126Z digest=sha256:63e329cb111273852f1d0146792cc9b34da991368b7948157bbf316957f60b25

Observation 0a0864c8-256b-46d9-beb9-1df787619d67 · outbound

This paper cites Capturability-based analysis and control of legged locomotion, part 2: Application to m2v2, a lower-body humanoid,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Capturability-based analysis and control of legged locomotion, part 2: Application to m2v2, a lower-body humanoid,

Reference 90

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source=pdf_text observed=2026-08-06T21:08:56.631502Z digest=sha256:ea5ebecfb67ba48d5d7742b989a384fb5d0ac014df20aa5cc472fae969f13add

Observation 8ea0386d-fedd-4506-99fa-f25030854d85 · outbound

This paper cites Convex model predictive control of single rigid body model on so (3) for versatile dynamic legged mo- 41 tions,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Convex model predictive control of single rigid body model on so (3) for versatile dynamic legged mo- 41 tions,

Reference 91

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source=pdf_text observed=2026-08-06T21:08:56.774224Z digest=sha256:85c71d1f079a58846fbff994df423a3048fc36d367ad58c57ed3532ba6d27920

Observation c6b8c44c-d460-4b8f-bcbf-4595e5f040bb · outbound

This paper cites Humanoid parkour learning,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Humanoid parkour learning,

Reference 92

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source=pdf_text observed=2026-08-06T21:08:56.890971Z digest=sha256:6ec0e4095db56bf42ea0d77c2b98e917ab2119644138ee765875a255e0f5e1d0

Observation 534eb0ca-c735-4dbd-929b-d7856b6d7d80 · outbound

This paper cites AMASS: Archive of motion capture as surface shapes,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models AMASS: Archive of motion capture as surface shapes,

Reference 93

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source=pdf_text observed=2026-08-06T21:08:56.989623Z digest=sha256:f36d7fb05be385fd910920fc44b578771d0f1db3f77b51f702e8529f29fde34b

Observation 8bd10830-826d-4709-bb79-59df07354674 · outbound

This paper cites Adversarial motion priors make good substitutes for complex reward functions,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Adversarial motion priors make good substitutes for complex reward functions,

Reference 94

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source=pdf_text observed=2026-08-06T21:08:57.111357Z digest=sha256:f311c1a73fa14285f8c38efd9d267ed736f2b3a97c0bf1976c1f6491a50994bd

Observation a9650d08-cda8-4096-b430-7bb6aadebb4c · outbound

This paper cites Expres- sive Whole-Body Control for Humanoid Robots,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Expres- sive Whole-Body Control for Humanoid Robots,

Reference 95

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source=pdf_text observed=2026-08-06T21:08:57.264243Z digest=sha256:10d407143e57d68dbf3fc378c51aa9cffb749e496bf729968388b67f3b8a47e4

Observation bbd734c6-741a-4c90-aaf4-a107a8f60dc0 · outbound

This paper cites Omnih2o: Universal and dexterous human-to-humanoid whole-body teleoperation and learning,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Omnih2o: Universal and dexterous human-to-humanoid whole-body teleoperation and learning,

Reference 96

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source=pdf_text observed=2026-08-06T21:08:57.381232Z digest=sha256:c77107f8e69439052b1a4d5e0d5d9ffdfa7539a2493acc046628ae93db8b94bf

Observation df8f7772-940e-4b4c-babf-d3df8d924b77 · outbound

This paper cites Ukemi: Falling motion control to minimize dam- age to biped humanoid robot,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Ukemi: Falling motion control to minimize dam- age to biped humanoid robot,

Reference 97

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Observation e03ed0ae-2b0d-4510-a786-0cecb1dc397a · outbound

This paper cites The first human-size humanoid that can fall over safely and stand-up again,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models The first human-size humanoid that can fall over safely and stand-up again,

Reference 98

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Observation 711eb589-6a52-4889-a50b-91f351cdc24b · outbound

This paper cites A falling motion control of humanoid robots based on biomechanical evaluation of falling down of humans,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models A falling motion control of humanoid robots based on biomechanical evaluation of falling down of humans,

Reference 99

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source=pdf_text observed=2026-08-06T21:08:57.793035Z digest=sha256:32a8bc6da8db7f3c4dee22266b06a41a88000dfdaf2c3d20882f6d4f28c43cf0

Observation bc414d9d-56a2-4218-a0f5-ea7b6fd65338 · outbound

This paper cites Resistant compliance control for biped robot inspired by humanlike behavior,.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Resistant compliance control for biped robot inspired by humanlike behavior,

Reference 100

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source=pdf_text observed=2026-08-06T21:08:57.908363Z digest=sha256:b17602e932e3de6a437776ea8f8a5572f77e950e93a878ef9a6a9facbeea299a

Observation 93e582fe-d247-422f-8791-3634a901849c · outbound

This paper cites Learning Humanoid Standing-up Control across Diverse Postures.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models Learning Humanoid Standing-up Control across Diverse Postures

Reference 101

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source=pdf_text observed=2026-08-06T21:08:58.007269Z digest=sha256:960d57285b56db70cc843c2c3363167cfa2ee21102e5415ee7d9d8c01fe3003a

Pith citing papers

Observation cfd961f4-492e-4b3e-b703-a898514bda01 · inbound

3D and 4D World Modeling: A Survey cites this paper.

3D and 4D World Modeling: A Survey A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 152

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source=pdf_text observed=2026-08-05T06:04:25.684741Z digest=sha256:bf3806f9d1253920d3ac47d73c041faa096797beb3acac302c795ee6d93eec41

Observation 4ade6fc4-4ee5-4d0a-9052-c014f71b5246 · inbound

Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI cites this paper.

Aligning Perception, Reasoning, Modeling and Interaction: A Survey on Physical AI A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 64

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation ac6a3000-994e-48ad-a416-f3e6d447c620 · inbound

Target-Bench: Can Video World Models Achieve Mapless Path Planning with Semantic Targets? cites this paper.

Target-Bench: Can Video World Models Achieve Mapless Path Planning with Semantic Targets? A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 55c60386-2765-4b86-90e7-f31b1c1380fa · inbound

ToG-Bench: Task-Oriented Spatio-Temporal Grounding in Egocentric Videos cites this paper.

ToG-Bench: Task-Oriented Spatio-Temporal Grounding in Egocentric Videos A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 23

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Observation c203b8be-e100-4017-8b35-2b591e340ad6 · inbound

Advancing Open-source World Models cites this paper.

Advancing Open-source World Models A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 41

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Observation 3ce26333-21db-476c-ab7a-baa797fe5882 · inbound

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RU4D-SLAM: Reweighting Uncertainty in Gaussian Splatting SLAM for 4D Scene Reconstruction A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 30

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Observation 3e693d99-fb49-423e-b20a-2974f363e1b4 · inbound

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WestWorld: A Knowledge-Encoded Scalable Trajectory World Model for Diverse Robotic Systems A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 26

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Observation b86160d3-8517-482d-a201-6f80b8f6afcc · inbound

OpenWorldLib: A Unified Codebase and Definition of Advanced World Models cites this paper.

OpenWorldLib: A Unified Codebase and Definition of Advanced World Models A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 91

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Observation 1190f747-45c9-48f5-b667-f33ff7c7d85e · inbound

OpenWorldLib: A Unified Codebase and Definition of Advanced World Models cites this paper.

OpenWorldLib: A Unified Codebase and Definition of Advanced World Models A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 91

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Observation 3b619996-cb68-4052-b2bf-44997997cf3b · inbound

Evaluation as Evolution: Transforming Adversarial Diffusion into Closed-Loop Curricula for Autonomous Vehicles cites this paper.

Evaluation as Evolution: Transforming Adversarial Diffusion into Closed-Loop Curricula for Autonomous Vehicles A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 12

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Observation 38255993-d25f-4573-b575-c56c357c1cc0 · inbound

PhyMix: Towards Physically Consistent Single-Image 3D Indoor Scene Generation with Implicit--Explicit Optimization cites this paper.

PhyMix: Towards Physically Consistent Single-Image 3D Indoor Scene Generation with Implicit--Explicit Optimization A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 23

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arxiv_id, observed 2026-05-11T09:50:58.238197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 87512676-4e39-4a56-ba39-3e3936ddb703 · inbound

Human Cognition in Machines: A Unified Perspective of World Models cites this paper.

Human Cognition in Machines: A Unified Perspective of World Models A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 113

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Observation 16e0f10e-693d-4f69-b6a0-f819c4b653ba · inbound

3D Generation for Embodied AI and Robotic Simulation: A Survey cites this paper.

3D Generation for Embodied AI and Robotic Simulation: A Survey A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 2

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arxiv_id, observed 2026-05-12T09:01:25.481935Z

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Observation b1f999e1-2ec9-4edb-90ff-39e09691fbcd · inbound

3D Generation for Embodied AI and Robotic Simulation: A Survey cites this paper.

3D Generation for Embodied AI and Robotic Simulation: A Survey A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 2

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arxiv_id, observed 2026-05-11T22:06:13.108283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-08T03:31:05.311070Z digest=sha256:99c65c894321caa3b3399dfd49fd8045e9b4b6ac6ce9035029306417376544a4

Observation 289a96b4-1509-4896-9640-47e815a02b4d · inbound

3D Generation for Embodied AI and Robotic Simulation: A Survey cites this paper.

3D Generation for Embodied AI and Robotic Simulation: A Survey A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 2

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verified exact
arxiv_id, observed 2026-05-11T04:05:58.646057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-11T01:56:24.510913Z digest=sha256:3740d3b5a5ef7b53d1e860e7eda24af9251f6ef93a7ccc33658e4234f4c59c2a

Observation 37dd6339-bf55-4ec2-a1fd-d7a8575b33a4 · inbound

GEM: Generating LiDAR World Model via Deformable Mamba cites this paper.

GEM: Generating LiDAR World Model via Deformable Mamba A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 24

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verified exact
arxiv_id, observed 2026-05-11T01:45:51.313105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-11T01:31:09.604703Z digest=sha256:5e261a7d9e1f6ebeb56763ea459c5e42df51934154fafa18c67a7f55e832afdb

Observation b1e668eb-eaf3-4460-bdfc-95ef9b91983c · inbound

WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform cites this paper.

WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 3

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verified exact
arxiv_id, observed 2026-05-20T11:03:13.682453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T10:59:54.879907Z digest=sha256:a4fa04fbb881345536c341248fd5041039d37ce18f1eeedd1ef993cbd7cf0fd4

Observation a340c223-4457-43c5-a39f-e3988046924e · inbound

WorldString: Actionable World Representation cites this paper.

WorldString: Actionable World Representation A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 35

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verified exact
arxiv_id, observed 2026-05-20T09:48:11.336345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T09:47:08.828067Z digest=sha256:0bac81a98bb239731ef102cf741cbf45a2836b64f933a0827e832d168c28f8c6

Observation 333260eb-88c3-4acd-b0a2-58786f6073db · inbound

WorldString: Actionable World Representation cites this paper.

WorldString: Actionable World Representation A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 35

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verified exact
arxiv_id, observed 2026-05-21T07:49:50.039860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-21T07:47:37.283455Z digest=sha256:288e3c401f952983a7b895af97bc78fac991dc4129eee4b55f3792c1e539ad6f

Observation dace664c-aa55-47b6-b0a2-dd75fa405e78 · inbound

PhyWorld: Physics-Faithful World Model for Video Generation cites this paper.

PhyWorld: Physics-Faithful World Model for Video Generation A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-20T07:33:07.610198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-20T07:28:20.248452Z digest=sha256:976e580640393d67f1d5a042517769bafcea9c8106107cee98f891baf35b4a43

Observation 32f4407a-c8d6-4b2d-a7b8-f7486d5de9d1 · inbound

NVIDIA Isaac Sim: Enabling Scalable, GPU-Accelerated Simulation for Robotics cites this paper.

NVIDIA Isaac Sim: Enabling Scalable, GPU-Accelerated Simulation for Robotics A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 32

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verified exact
arxiv_id, observed 2026-07-02T03:26:29.312301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-28T10:03:54.419845Z digest=sha256:9b3f17ac45302fb06d7f3b5cb72355f79f10d97fd5b144bd89485f6dd16f29b4

Observation 05324041-c7d2-4957-9383-5c8524e82b6c · inbound

Echo-Memory: A Controlled Study of Memory in Action World Models cites this paper.

Echo-Memory: A Controlled Study of Memory in Action World Models A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:57:29.741283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-27T16:58:37.552036Z digest=sha256:1376dd680dfb785e326cf3ac6f7b578806c7da74f97fc7cfce3681700b42ea90

Observation 218cd74d-0a6a-4bbe-b03e-c13c914b6c1e · inbound

Empowering Embodied AI in 6G Networks: Architecture, Enablers, and Open Challenges cites this paper.

Empowering Embodied AI in 6G Networks: Architecture, Enablers, and Open Challenges A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-06-30T19:45:00.748322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-30T19:42:35.149663Z digest=sha256:83f42147f1156cda7b5c32c46b05e55e79881efa6b26556447dee533f3f94eec

Observation 8239fc9d-9f77-4870-a8a7-c19cedee53b9 · inbound

MoWorld: A Flash World Model cites this paper.

MoWorld: A Flash World Model A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 37

Resolution
verified exact
local_arxiv, observed 2026-07-08T13:14:53.257007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-07-08T13:10:31.940263Z digest=sha256:9a0df2d153abe69825bd9ffdc7bb5543f0abc1a2ddf02fef9dafb4ca8f731c47

Observation 8a4cd1a6-e2fa-480d-b34c-1f3cdc5291b8 · inbound

MoWorld: A Flash World Model cites this paper.

MoWorld: A Flash World Model A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 37

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unresolved
no resolver link, observed 2026-08-04T04:32:04.084465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T04:32:04.084465Z digest=sha256:cb1f798fbfc473a5001d8c91de5ed5125e1ec76dfc68d074f6b78af13cf14310

Observation ca8f010c-7c01-4108-b8b2-330e2babfa19 · inbound

Xiaomi-Robotics-U0: Unified Embodied Synthesis with World Foundation Model cites this paper.

Xiaomi-Robotics-U0: Unified Embodied Synthesis with World Foundation Model A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-07-14T04:10:14.360463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T04:10:14.360463Z digest=sha256:cb7c6c90aa6f56eccb5d852017f3be459668d5570d488a55ac52da7f7fe5ebc3

Observation 25c096fd-1a4d-4766-864f-71c26351fea6 · inbound

Physical AI Governance: From Theory to Practice Across Life Cycle cites this paper.

Physical AI Governance: From Theory to Practice Across Life Cycle A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 105

Resolution
unresolved
no resolver link, observed 2026-08-01T04:17:53.715165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T04:17:53.715165Z digest=sha256:6a867510b02a1d1ed09a26db88ebbabc25e20adb7ceb0a03329e5fb1bfaeda8c

Observation eb3cc003-06d0-4b06-8f09-a2590aa15ca8 · inbound

AndroidReality: How Far Are Mobile Agents from the Real World? cites this paper.

AndroidReality: How Far Are Mobile Agents from the Real World? A Survey: Learning Embodied Intelligence from Physical Simulators and World Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-11T04:17:35.717037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T04:17:35.717037Z digest=sha256:779e84ba56a27f3f4ecb12352fe815999dfee9bd65c174f83a858301d12bbedf