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Paper Citation Record · LEDGER

RoboScape: Physics-informed Embodied World Model

As of 9 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 17 inbound Pith citation observations for arXiv:2506.23135.

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

pith.paper-citation-record.v1
2506.23135 v1

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:56:12.204432Z

measured 72 of 72 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:12:50.540589Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T04:09:35.073117Z

Reference resolution

55 of 55 outbound references displayed

  • verified exact0
  • verified fuzzy8
  • unresolved47
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 38930093-e900-414b-835b-7751ed3d240f · outbound

This paper cites GPT-4 Technical Report.

RoboScape: Physics-informed Embodied World Model GPT-4 Technical Report

Reference 1

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Observation 2e303d10-5f94-4c31-a800-b353f9fb53a5 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

RoboScape: Physics-informed Embodied World Model Gemini: A Family of Highly Capable Multimodal Models

Reference 2

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Observation d47fb436-0856-4b39-b449-74b9b92ddd03 · outbound

This paper cites Bridgedata v2: A dataset for robot learning at scale.

RoboScape: Physics-informed Embodied World Model Bridgedata v2: A dataset for robot learning at scale

Reference 3

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source=pdf_text observed=2026-08-06T21:56:07.026710Z digest=sha256:679a1d97656ff26421fe1c2ac0f9ada3c59cd04f17c1f7bedec841664badc9f9

Observation 3be0d1c2-ef87-464a-abb7-4030a58c1160 · outbound

This paper cites Open x- embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0.

RoboScape: Physics-informed Embodied World Model Open x- embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0

Reference 4

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Observation 10480055-fd18-4966-8bac-b26ec3fe30a6 · outbound

This paper cites DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.

RoboScape: Physics-informed Embodied World Model DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Reference 5

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Observation f436cb02-c51c-4eab-bd03-ade6e1cfde89 · outbound

This paper cites Recurrent world models facilitate policy evolution.

RoboScape: Physics-informed Embodied World Model Recurrent world models facilitate policy evolution

Reference 7

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source=pdf_text observed=2026-08-06T21:56:07.203399Z digest=sha256:b0630d182bac4f71f88193855d60d19a76f4a0cd6384545f77f30fe9d86ce8b7

Observation c5fdb139-b76b-4091-8cf7-a790a14b5b24 · outbound

This paper cites Learning Interactive Real-World Simulators.

RoboScape: Physics-informed Embodied World Model Learning Interactive Real-World Simulators

Reference 8

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source=pdf_text observed=2026-08-06T21:56:07.249016Z digest=sha256:047e1ff7d04e44a0ac3c8c691d0767146bae5c7904d2d9bcb6369147adf13d2f

Observation 7d94741e-4de4-4bf5-9775-e26df3caed41 · outbound

This paper cites Video generation models as world simulators.

RoboScape: Physics-informed Embodied World Model Video generation models as world simulators

Reference 9

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source=pdf_text observed=2026-08-06T21:56:07.330002Z digest=sha256:9c3c61a07b3c8250c4caf60e7c21d8b3a946b8f8ecb51dab130c8f38e0dad5c5

Observation ec0af1ce-0849-43d9-b8bc-48751245927f · outbound

This paper cites Learning Real-World Action-Video Dynamics with Heterogeneous Masked Autoregression.

RoboScape: Physics-informed Embodied World Model Learning Real-World Action-Video Dynamics with Heterogeneous Masked Autoregression

Reference 10

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source=pdf_text observed=2026-08-06T21:56:07.377797Z digest=sha256:3061760b3db37809bd903d93193b65ff7ea53dbd4229fadf8413e7126bf10173

Observation bf904acc-7b61-439b-b3c8-65131c99846d · outbound

This paper cites ivideogpt: Interactive videogpts are scalable world models.

RoboScape: Physics-informed Embodied World Model ivideogpt: Interactive videogpts are scalable world models

Reference 11

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Observation 59802a9e-ac9d-4f1f-bb97-e1730548f2ea · outbound

This paper cites IRASim: A Fine-Grained World Model for Robot Manipulation.

RoboScape: Physics-informed Embodied World Model IRASim: A Fine-Grained World Model for Robot Manipulation

Reference 12

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source=pdf_text observed=2026-08-06T21:56:07.466192Z digest=sha256:50dfd4f69acea60a18b3ef341e9cab25952361f67666efa637b43e5a0d4582ae

Observation 2e4c45f8-31e5-4b5a-975f-31b039fcfc9a · outbound

This paper cites Cosmos World Foundation Model Platform for Physical AI.

RoboScape: Physics-informed Embodied World Model Cosmos World Foundation Model Platform for Physical AI

Reference 13

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source=pdf_text observed=2026-08-06T21:56:07.501402Z digest=sha256:60ba44777793c35cc733f10fc4a2de7a95ebcc6c126d9bf02410374b79059da5

Observation f054bf13-fc0e-48e0-86e2-0be15f2f1ee4 · outbound

This paper cites How Far is Video Generation from World Model: A Physical Law Perspective.

RoboScape: Physics-informed Embodied World Model How Far is Video Generation from World Model: A Physical Law Perspective

Reference 14

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source=pdf_text observed=2026-08-06T21:56:07.565879Z digest=sha256:8648b29bb0bc2bb06fdc33251e13cac1902391eae07e66c54be27b5e08b3d0c6

Observation 3c3a4515-d0cb-4339-af5e-a68e731f2e1e · outbound

This paper cites Exploring the Evolution of Physics Cognition in Video Generation: A Survey.

RoboScape: Physics-informed Embodied World Model Exploring the Evolution of Physics Cognition in Video Generation: A Survey

Reference 15

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Observation 4e1360c3-4a96-4455-9b03-44228dfbfd3a · outbound

This paper cites T2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation.

RoboScape: Physics-informed Embodied World Model T2VPhysBench: A First-Principles Benchmark for Physical Consistency in Text-to-Video Generation

Reference 16

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source=pdf_text observed=2026-08-06T21:56:07.727890Z digest=sha256:a0051686b27d4d111b69175e16dbed2e0559e762b0b7da280f167856af773b18

Observation 5460f98f-f4f8-4e6c-8c7c-cb9989583a64 · outbound

This paper cites Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation.

RoboScape: Physics-informed Embodied World Model Towards World Simulator: Crafting Physical Commonsense-Based Benchmark for Video Generation

Reference 17

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source=pdf_text observed=2026-08-06T21:56:07.821112Z digest=sha256:675d800fffdcc18ec65ed10d8d63da97fb16da486d816d900dd2504e0006a0ec

Observation 9db8673e-38d0-4ceb-8157-a53aa974c35e · outbound

This paper cites Towards physical understanding in video generation: A 3d point regularization approach.

RoboScape: Physics-informed Embodied World Model Towards physical understanding in video generation: A 3d point regularization approach

Reference 18

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Observation b78daa0b-2159-404a-93e0-cca00ca4d0fa · outbound

This paper cites Enhancing sketch animation: Text-to-video diffusion models with temporal consistency and rigidity constraints.

RoboScape: Physics-informed Embodied World Model Enhancing sketch animation: Text-to-video diffusion models with temporal consistency and rigidity constraints

Reference 19

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Observation 0788611f-475c-415f-a0ac-1c665c83cb77 · outbound

This paper cites Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis.

RoboScape: Physics-informed Embodied World Model Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis

Reference 20

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Observation 5946e152-ca8b-4cb6-975b-4e71f24d4aa9 · outbound

This paper cites PhysAnimator: Physics-Guided Generative Cartoon Animation.

RoboScape: Physics-informed Embodied World Model PhysAnimator: Physics-Guided Generative Cartoon Animation

Reference 21

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source=pdf_text observed=2026-08-06T21:56:08.214089Z digest=sha256:648f8304bb4e323a8b21d4500d985ba9887a723394e6778f9adff50ceafed98e

Observation 06cc2792-25ab-49b5-9ded-9723e705f757 · outbound

This paper cites Gpt4motion: Scripting physical motions in text-to-video generation via blender-oriented gpt planning.

RoboScape: Physics-informed Embodied World Model Gpt4motion: Scripting physical motions in text-to-video generation via blender-oriented gpt planning

Reference 22

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

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Observation 2e18e9ed-41d3-4ef0-8157-9f526113eced · outbound

This paper cites Physgen: Rigid-body physics-grounded image-to-video generation.

RoboScape: Physics-informed Embodied World Model Physgen: Rigid-body physics-grounded image-to-video generation

Reference 23

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Observation 58962108-fb24-42b8-9e23-d0df415aab19 · outbound

This paper cites PhysMotion: Physics-Grounded Dynamics From a Single Image.

RoboScape: Physics-informed Embodied World Model PhysMotion: Physics-Grounded Dynamics From a Single Image

Reference 24

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Observation ce43a6c4-03da-45fd-af79-2176a0d5f9c7 · outbound

This paper cites Physdreamer: Physics-based interaction with 3d objects via video generation.

RoboScape: Physics-informed Embodied World Model Physdreamer: Physics-based interaction with 3d objects via video generation

Reference 25

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Observation a223f87d-b986-43e8-9e83-03237484d2e8 · outbound

This paper cites Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion.

RoboScape: Physics-informed Embodied World Model Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusion

Reference 26

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Observation 4ffffeba-f3ef-4403-9fde-e191382adbfd · outbound

This paper cites Aether: Geometric-Aware Unified World Modeling.

RoboScape: Physics-informed Embodied World Model Aether: Geometric-Aware Unified World Modeling

Reference 27

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source=pdf_text observed=2026-08-06T21:56:08.961309Z digest=sha256:154d76cca49e0472719314b61c7ac402ece515f660f9171f5a09fa695e76c550

Observation b018b080-f0af-4bf8-a2ad-e54a5136b2ab · outbound

This paper cites TesserAct: Learning 4D Embodied World Models.

RoboScape: Physics-informed Embodied World Model TesserAct: Learning 4D Embodied World Models

Reference 28

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Observation 733886c6-ac3b-4665-86be-1e50bb808e95 · outbound

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

RoboScape: Physics-informed Embodied World Model Diffusion policy: Visuomotor policy learning via action diffusion

Reference 29

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Observation 2b2a1caa-447f-4d81-bbe8-bce695c732be · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

RoboScape: Physics-informed Embodied World Model $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 30

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Observation ddf523f2-5879-4fe0-9116-f32619e7454c · outbound

This paper cites Video Depth Anything: Consistent Depth Estimation for Super-Long Videos.

RoboScape: Physics-informed Embodied World Model Video Depth Anything: Consistent Depth Estimation for Super-Long Videos

Reference 31

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Observation 79f4b0f2-414a-4492-a8d1-20fd09c838f8 · outbound

This paper cites Spatialtracker: Tracking any 2d pixels in 3d space.

RoboScape: Physics-informed Embodied World Model Spatialtracker: Tracking any 2d pixels in 3d space

Reference 32

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Source-reported events for the cited work

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

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Observation 6f3cd3ec-8c72-431b-b358-607b843d4c24 · outbound

This paper cites Transnet v2: An effective deep network architecture for fast shot transition detection.

RoboScape: Physics-informed Embodied World Model Transnet v2: An effective deep network architecture for fast shot transition detection

Reference 33

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Observation 56ae5ccc-a901-4170-80d9-f1f8c373656d · outbound

This paper cites Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks.

RoboScape: Physics-informed Embodied World Model Internvl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks

Reference 34

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Observation d62178f5-29a6-4262-9999-f1842054b8fa · outbound

This paper cites Flownet: Learning optical flow with convolutional networks.

RoboScape: Physics-informed Embodied World Model Flownet: Learning optical flow with convolutional networks

Reference 35

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Observation 8b8ef04c-b948-4502-849b-0ab30aa44fde · outbound

This paper cites A survey on curriculum learning.IEEE transactions on pattern analysis and machine intelligence, 44(9):4555–4576, 2021.

RoboScape: Physics-informed Embodied World Model A survey on curriculum learning.IEEE transactions on pattern analysis and machine intelligence, 44(9):4555–4576, 2021

Reference 36

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Observation 33eeaa47-4a17-44c6-97c9-0afe8d5c81e5 · outbound

This paper cites Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation.

RoboScape: Physics-informed Embodied World Model Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation

Reference 37

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Observation cde2b557-8802-455a-aa35-641689226b4a · outbound

This paper cites AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems.

RoboScape: Physics-informed Embodied World Model AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems

Reference 38

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Observation 3249801c-cb57-4687-a3c2-ead22e373d20 · outbound

This paper cites Genie: Generative interactive environments.

RoboScape: Physics-informed Embodied World Model Genie: Generative interactive environments

Reference 39

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source=pdf_text observed=2026-08-06T21:56:10.366690Z digest=sha256:1823630190243b2ec446b011b5b8177bd0fb27865931a96b2d6d0c7d7aa8b538

Observation 166aaeeb-a43f-4eb5-a161-d577051e123d · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

RoboScape: Physics-informed Embodied World Model CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 40

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source=pdf_text observed=2026-08-06T21:56:10.485620Z digest=sha256:d0b214ff7d1586ef80374fc63e8ff1fc487c36b37b39fbe7bcaff0f102859b32

Observation c03deaa9-8c44-418d-b138-5a1ed326071e · outbound

This paper cites What Matters in Learning from Offline Human Demonstrations for Robot Manipulation.

RoboScape: Physics-informed Embodied World Model What Matters in Learning from Offline Human Demonstrations for Robot Manipulation

Reference 41

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source=pdf_text observed=2026-08-06T21:56:10.544121Z digest=sha256:180a259e40f5586d98b42d10278524494ff529fb243fdc7864f4e9cee870969d

Observation 7e93b563-f507-42fa-925f-327650e791b3 · outbound

This paper cites Libero: Benchmarking knowledge transfer for lifelong robot learning.

RoboScape: Physics-informed Embodied World Model Libero: Benchmarking knowledge transfer for lifelong robot learning

Reference 42

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source=pdf_text observed=2026-08-06T21:56:10.657866Z digest=sha256:34ffa1161375c937c172d4f86ae422225a9f07c62297540f5229f52fa6c36a66

Observation bf57973f-f9cc-428e-bf4a-5702ea1abdf9 · outbound

This paper cites World Models.

RoboScape: Physics-informed Embodied World Model World Models

Reference 43

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source=pdf_text observed=2026-08-06T21:56:10.750879Z digest=sha256:922c5e9ef3517a3a807486ef78282892926a48eaaab6875214bbf24ebc432b0b

Observation 4680ebf9-87d4-48c2-8b3c-8259a0c3acd7 · outbound

This paper cites Drive- dreamer: Towards real-world-drive world models for autonomous driving.

RoboScape: Physics-informed Embodied World Model Drive- dreamer: Towards real-world-drive world models for autonomous driving

Reference 44

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source=pdf_text observed=2026-08-06T21:56:10.853082Z digest=sha256:21e2090fc2686ffbd60e29a7adbea42fd893f38ada33706390f215071fa0ec93

Observation 9389d659-01db-47b2-9180-293db985965d · outbound

This paper cites Genad: Gen- erative end-to-end autonomous driving.

RoboScape: Physics-informed Embodied World Model Genad: Gen- erative end-to-end autonomous driving

Reference 45

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source=pdf_text observed=2026-08-06T21:56:10.978828Z digest=sha256:e417791da717137e1d4af229c6d31b8b459242b37f8d5185dbe2a7fb795be4f3

Observation 062e3e20-8ae8-4740-801f-1f3fb1c053ed · outbound

This paper cites GameGen-X: Interactive Open-world Game Video Generation.

RoboScape: Physics-informed Embodied World Model GameGen-X: Interactive Open-world Game Video Generation

Reference 46

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source=pdf_text observed=2026-08-06T21:56:11.097012Z digest=sha256:0fd69a038a44ecb961104dacb3dc023510faf701bdab761d5a66229657a838f0

Observation aba15f34-34c5-412d-9c21-e1055e448667 · outbound

This paper cites MaskGWM: A Generalizable Driving World Model with Video Mask Reconstruction.

RoboScape: Physics-informed Embodied World Model MaskGWM: A Generalizable Driving World Model with Video Mask Reconstruction

Reference 47

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source=pdf_text observed=2026-08-06T21:56:11.257053Z digest=sha256:bf2fd93f834abc77f4a315fbedbd1cda67aa7065bc5bb849c145a07e7957cd05

Observation 219f113c-544e-4e6e-b6a0-208840d454f5 · outbound

This paper cites Driving into the future: Multiview visual forecasting and planning with world model for autonomous driving.

RoboScape: Physics-informed Embodied World Model Driving into the future: Multiview visual forecasting and planning with world model for autonomous driving

Reference 48

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source=pdf_text observed=2026-08-06T21:56:11.354123Z digest=sha256:c23cd4bf8a20f16cccf1de94f64cd1bdf2f003e1ea7a162165c78fd3afbbcb61

Observation 94446495-7dff-4001-bc02-c8d88d388072 · outbound

This paper cites Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability.

RoboScape: Physics-informed Embodied World Model Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability

Reference 49

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source=pdf_text observed=2026-08-06T21:56:11.450513Z digest=sha256:8aa4e3273a33e85fbc8a9db42084f24718bee6c1d26cd3f098185efbeb683613

Observation add09686-cef4-4127-9abd-0581207968e3 · outbound

This paper cites GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Driving.

RoboScape: Physics-informed Embodied World Model GAIA-2: A Controllable Multi-View Generative World Model for Autonomous Driving

Reference 50

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source=pdf_text observed=2026-08-06T21:56:11.522836Z digest=sha256:734a192b82dbf8be439ec735242205dc93d5e030aa6c3a770518d8c10fd70f4b

Observation f118ccb3-4716-4904-95a7-ccbcbb9994b1 · outbound

This paper cites Learning robotic video dynamics with heterogeneous masked autoregression.

RoboScape: Physics-informed Embodied World Model Learning robotic video dynamics with heterogeneous masked autoregression

Reference 51

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

source=pdf_text observed=2026-08-06T21:56:11.648173Z digest=sha256:2a90fe04769c6fb24c763dfa9f4a20ed601f753d08e160c4f055ca596a20d381

Observation fa01d825-8aaa-4e91-8e27-0529267464fc · outbound

This paper cites Gamefactory: Creating new games with generative interactive videos.

RoboScape: Physics-informed Embodied World Model Gamefactory: Creating new games with generative interactive videos

Reference 52

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source=pdf_text observed=2026-08-06T21:56:11.733771Z digest=sha256:f3ff3f34c395e071ca16a71e9bfc51b8a08c746acfb967032589472713cb29ec

Observation 44bf1fbe-ec70-4b5e-9f81-f11d1edc7221 · outbound

This paper cites Pre-Trained Video Generative Models as World Simulators.

RoboScape: Physics-informed Embodied World Model Pre-Trained Video Generative Models as World Simulators

Reference 53

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source=pdf_text observed=2026-08-06T21:56:11.850755Z digest=sha256:dc26c50be41d33d33365b1c2b36c9e34c8947804fd0a6514be0131f8607f1a9a

Observation 5abedf24-2e1e-4d5f-ac89-0cf3d423dc06 · outbound

This paper cites Worldmem: Long-term consistent world simulation with memory.

RoboScape: Physics-informed Embodied World Model Worldmem: Long-term consistent world simulation with memory

Reference 54

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source=pdf_text observed=2026-08-06T21:56:11.947234Z digest=sha256:f240bc9ba62dc21b963e51d110e852791a8730f5e1a9c53719ccede3e8280338

Observation 99d9b239-e276-42e8-8525-9e4a5729cc4f · outbound

This paper cites Scalable diffusion models with transformers.

RoboScape: Physics-informed Embodied World Model Scalable diffusion models with transformers

Reference 55

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source=pdf_text observed=2026-08-06T21:56:12.072637Z digest=sha256:f05c492bc198708fcd47fa6c88ec61a2cf8b2d8a37e2100e3504a3ad56af61e1

Observation 966fd9c5-57ce-4322-b82d-302c9f40664e · outbound

This paper cites Seeing the future, perceiving the future: A uni- fied driving world model for future generation and perception.arXiv preprint arXiv:2503.13587, 2025.

RoboScape: Physics-informed Embodied World Model Seeing the future, perceiving the future: A uni- fied driving world model for future generation and perception.arXiv preprint arXiv:2503.13587, 2025

Reference 56

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source=pdf_text observed=2026-08-06T21:56:12.204432Z digest=sha256:abb1819f4e065177802b726c6ac08fb255074ebc6dcfa41170fc9a13c6ca66a8

Pith citing papers

Observation 9c88a007-1a15-4057-ade8-dede4d9cbb6a · inbound

A Comprehensive Survey on World Models for Embodied AI cites this paper.

A Comprehensive Survey on World Models for Embodied AI RoboScape: Physics-informed Embodied World Model

Reference 180

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source=pdf_text observed=2026-08-04T09:12:50.540589Z digest=sha256:b20822fba928d49c8de80f47258584da10b54b26e3a44c2130c8871f5083dcfc

Observation 57637e3b-60f3-4d39-a542-0b88da57c286 · inbound

When Vision Overrides Language: Evaluating and Mitigating Counterfactual Failures in VLAs cites this paper.

When Vision Overrides Language: Evaluating and Mitigating Counterfactual Failures in VLAs RoboScape: Physics-informed Embodied World Model

Reference 44

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source=pdf_text observed=2026-08-02T22:14:29.363273Z digest=sha256:1d825697e9031cf738eff7682e0ee47f0c7543150f6f9930ad732a6ab014adc0

Observation f42f9a17-424f-4226-8e30-79d303f1653b · inbound

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

Human Cognition in Machines: A Unified Perspective of World Models RoboScape: Physics-informed Embodied World Model

Reference 148

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arxiv_id, observed 2026-05-10T08:12:26.216061Z

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

source=pdf_text observed=2026-05-10T08:12:15.663761Z digest=sha256:6e4e6a16646c60e511480a996b4aaa9fb67a7a11a1691cb09ccc99302ef0e0f8

Observation d426032a-e27d-44ad-9cad-ff36a6bd7e82 · inbound

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

3D Generation for Embodied AI and Robotic Simulation: A Survey RoboScape: Physics-informed Embodied World Model

Reference 66

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arxiv_id, observed 2026-05-12T09:01:25.627188Z

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

source=pdf_text observed=2026-05-07T13:16:44.508344Z digest=sha256:56fd5c669edf0b9af4407471f08996e1baee1137e7f0ee78b341cc2fc96ac1a4

Observation e47e6e6a-f702-4b75-8771-51336da2d470 · inbound

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

3D Generation for Embodied AI and Robotic Simulation: A Survey RoboScape: Physics-informed Embodied World Model

Reference 66

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arxiv_id, observed 2026-05-11T22:01:14.129353Z

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

source=pdf_text observed=2026-05-08T03:31:05.311070Z digest=sha256:ba0e0f0e3b53f99533185e347e98962ac1eb4c1cf3f9db942de39f8f6704ad72

Observation 1eaa3cbd-aa32-4ac2-8366-287f17431018 · inbound

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

3D Generation for Embodied AI and Robotic Simulation: A Survey RoboScape: Physics-informed Embodied World Model

Reference 66

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arxiv_id, observed 2026-05-11T04:05:58.445921Z

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

source=pdf_text observed=2026-05-11T01:56:24.510913Z digest=sha256:9e1e795997e790f677b008fcd948229c2ada9db83cc284060eddb0ba352414f9

Observation f2fad854-525a-4365-aa7c-85e6a9450b89 · inbound

LaWM: Least Action World Models for Long-Horizon Physical Consistency from Visual Observations cites this paper.

LaWM: Least Action World Models for Long-Horizon Physical Consistency from Visual Observations RoboScape: Physics-informed Embodied World Model

Reference 18

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arxiv_id, observed 2026-05-12T00:51:15.618859Z

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

source=pdf_text observed=2026-05-12T00:49:47.283703Z digest=sha256:4a9b9e675f0e920c576464d337e4123f9a6946c9faed233530495bc64e891e94

Observation a09438cd-c62c-42c2-b86e-b460a869c4f3 · inbound

World Action Models: The Next Frontier in Embodied AI cites this paper.

World Action Models: The Next Frontier in Embodied AI RoboScape: Physics-informed Embodied World Model

Reference 41

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arxiv_id, observed 2026-05-13T05:07:18.367935Z

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Observation 6489af55-6b02-49aa-b278-02ec9e316297 · 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 RoboScape: Physics-informed Embodied World Model

Reference 20

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arxiv_id, observed 2026-05-20T11:03:13.655266Z

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

source=pdf_text observed=2026-05-20T10:59:54.879907Z digest=sha256:946d663d999533735fb432752103111f1603c36519ce4496bbf627a4f841acff

Observation da896781-fda5-4524-b0f7-815ccf9160ad · inbound

PH-Dreamer: A Physics-Driven World Model via Port-Hamiltonian Generative Dynamics cites this paper.

PH-Dreamer: A Physics-Driven World Model via Port-Hamiltonian Generative Dynamics RoboScape: Physics-informed Embodied World Model

Reference 29

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arxiv_id, observed 2026-05-20T12:28:16.642956Z

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source=arxiv_source observed=2026-05-20T12:27:13.931203Z digest=sha256:04ce76205792e79170b8c964ffcc15aa5e9e51598fbf65f5f7fc4d0abef561bc

Observation 79cc5bce-f565-448b-9c3d-acacc7555edd · inbound

World Action Models: A Survey cites this paper.

World Action Models: A Survey RoboScape: Physics-informed Embodied World Model

Reference 139

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arxiv_id, observed 2026-07-04T04:09:35.075140Z

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

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Observation 291c85bc-4e60-4dfb-9c64-43ad97278ae3 · inbound

PhysisForcing: Physics Reinforced World Simulator for Robotic Manipulation cites this paper.

PhysisForcing: Physics Reinforced World Simulator for Robotic Manipulation RoboScape: Physics-informed Embodied World Model

Reference 39

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arxiv_id, observed 2026-06-29T20:03:56.944785Z

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

source=pdf_text observed=2026-06-29T04:34:38.286863Z digest=sha256:c8e481bd4a58ef310f8e218acd016acae2f1f0b20dfa47af07e667d94836003d

Observation 98c5f914-e528-439a-9b1d-6920cbb0c665 · inbound

3D Point World Models: Point Completion Enables More Accurate Dynamics Learning cites this paper.

3D Point World Models: Point Completion Enables More Accurate Dynamics Learning RoboScape: Physics-informed Embodied World Model

Reference 17

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arxiv_id, observed 2026-07-02T18:57:16.312504Z

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

source=pdf_text observed=2026-07-02T18:49:21.268436Z digest=sha256:1809d18a78ccb0d9482257eb07bcdddc8fb8d4751f75e1db31a81aa6f675d763

Observation 9bcd3fec-a7ff-4f7c-b461-5a65f73a6867 · inbound

From World Models to World Action Models: A Concise Tutorial for Robotics cites this paper.

From World Models to World Action Models: A Concise Tutorial for Robotics RoboScape: Physics-informed Embodied World Model

Reference 20

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arxiv_id, observed 2026-07-02T11:26:53.598722Z

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

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Observation 538961d0-f7ea-4f8e-a46e-f1815aa46964 · inbound

From World Models to World Action Models: A Concise Tutorial for Robotics cites this paper.

From World Models to World Action Models: A Concise Tutorial for Robotics RoboScape: Physics-informed Embodied World Model

Reference 20

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arxiv_id, observed 2026-07-03T20:38:55.071831Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-07-03T20:35:21.512564Z digest=sha256:2e3e6a148fa2551903a6212fd04055186308cf5d8eff3eb28773bb3093aa716d

Observation 67fe7133-97a8-4a3c-8f59-4de49a24ec89 · inbound

From World Models to World Action Models: A Concise Tutorial for Robotics cites this paper.

From World Models to World Action Models: A Concise Tutorial for Robotics RoboScape: Physics-informed Embodied World Model

Reference 20

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no resolver link, observed 2026-07-12T09:15:00.615740Z

Source-reported events for the cited work

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source=pdf_text observed=2026-07-12T09:15:00.615740Z digest=sha256:da0642c27c185c43dbab0cde3b0f6a9321a3c9cd636657873841bfa9e63a3a27

Observation 34389e60-3875-4b15-816b-0f6f6a8ee6d4 · inbound

From World Models to World Action Models: A Concise Tutorial for Robotics cites this paper.

From World Models to World Action Models: A Concise Tutorial for Robotics RoboScape: Physics-informed Embodied World Model

Reference 20

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no resolver link, observed 2026-08-02T09:18:02.223470Z

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