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Paper Citation Record · LEDGER

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents

As of 14 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2607.19190.

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

pith.paper-citation-record.v1
2607.19190 v3

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T13:15:56.302292Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

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External citation measurements

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Outbound references

Observation 93b37eed-f95e-4f1c-8e97-550bf90eaa1d · outbound

This paper cites PhysX-Omni: Unified Simulation-Ready Physical 3D Generation for Rigid, Deformable, and Articulated Objects.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents PhysX-Omni: Unified Simulation-Ready Physical 3D Generation for Rigid, Deformable, and Articulated Objects

Reference 1

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source=pdf_text observed=2026-08-01T13:15:53.947465Z digest=sha256:0c38c67198ac6837c06e4e1d5f86ac0b94a6f08aa2723d6951278ecc612e5e74

Observation 9b5440b6-bfe7-40a0-8f19-08807f723709 · outbound

This paper cites SAM 3: Segment Anything with Concepts.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents SAM 3: Segment Anything with Concepts

Reference 2

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source=pdf_text observed=2026-08-01T13:15:54.035542Z digest=sha256:0699645a451cda5a1bb55c89a05247373031d25956cf7caba95b30475b7c7506

Observation 02228804-6549-45f4-97be-e3bcc556ef04 · outbound

This paper cites SAM 3D: 3Dfy Anything in Images.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents SAM 3D: 3Dfy Anything in Images

Reference 3

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source=pdf_text observed=2026-08-01T13:15:54.174345Z digest=sha256:e4c28488f7a8022101e167e3c6d06db76eba590b5ab3a99b28ed85ec344dcbb3

Observation d2f7365f-3def-4c0a-88e8-5ab48ff62e91 · outbound

This paper cites Empm: Embodied mpm for modeling and simulation of deformable objects.IEEE Robotics and Automation Letters, 11(4):4179–4186, 2026.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Empm: Embodied mpm for modeling and simulation of deformable objects.IEEE Robotics and Automation Letters, 11(4):4179–4186, 2026

Reference 4

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source=pdf_text observed=2026-08-01T13:15:54.299020Z digest=sha256:57b3a603ac69876474f726f0e524d3c8600a3d410e299a91a9b891246137e215

Observation 8e396de3-c3a8-4b9b-b3bd-f9886dfc882c · outbound

This paper cites Twinaligner: Visual-dynamic alignment empowers physics-aware real2sim2real for robotic manipulation.arXiv preprint arXiv:2512.19390, 2025.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Twinaligner: Visual-dynamic alignment empowers physics-aware real2sim2real for robotic manipulation.arXiv preprint arXiv:2512.19390, 2025

Reference 5

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source=pdf_text observed=2026-08-01T13:15:54.397819Z digest=sha256:3cb8cfc27c876cf07621e44dad3cd28e0e65aaee3b727a2c823a8f31303b07d7

Observation 48cff756-402d-4957-9446-faddeb85092f · outbound

This paper cites Skillmimicgen: Automated demonstration generation for efficient skill learning and deployment.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Skillmimicgen: Automated demonstration generation for efficient skill learning and deployment

Reference 6

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source=pdf_text observed=2026-08-01T13:15:54.520899Z digest=sha256:d92f8c38767c6527ce786f11b8ac64cea65e42d007f0fb11b69cbead04afd3f3

Observation d1904e39-1ab2-441b-aabd-93d5330dcb47 · outbound

This paper cites Harvey, Mike Yurick, Derek Nowrouzezahrai, and Christopher Pal.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Harvey, Mike Yurick, Derek Nowrouzezahrai, and Christopher Pal

Reference 7

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source=pdf_text observed=2026-08-01T13:15:54.625505Z digest=sha256:07db36681351157dc6dc60a80417d37d348c3a1a075c770ce189fd13df378ac3

Observation 5e298cd7-b0e8-4cf5-a620-3c0bbb96a86f · outbound

This paper cites Pointworld: Scaling 3d world models for in-the-wild robotic manipulation.arXiv preprint arXiv:2601.03782, 2026.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Pointworld: Scaling 3d world models for in-the-wild robotic manipulation.arXiv preprint arXiv:2601.03782, 2026

Reference 8

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source=pdf_text observed=2026-08-01T13:15:54.702019Z digest=sha256:8a95089d9a0664065ae19e535c53e8c57a5c2eeae576f59801fd363eee3043d6

Observation 2d7d7b8f-024d-4537-89ee-db544eb14df1 · outbound

This paper cites Phystwin: Physics-informed reconstruction and simulation of deformable objects from videos.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Phystwin: Physics-informed reconstruction and simulation of deformable objects from videos

Reference 9

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source=pdf_text observed=2026-08-01T13:15:54.790962Z digest=sha256:4d2d6dea7cd8ce235536b8a55f8f59135930e01cad71eccf18db39d52cabb38d

Observation 4375cf3e-dd32-471e-9962-f15ae228c40e · outbound

This paper cites SimWorld Studio: Automatic Environment Generation with Evolving Coding Agent for Embodied Agent Learning.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents SimWorld Studio: Automatic Environment Generation with Evolving Coding Agent for Embodied Agent Learning

Reference 10

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source=pdf_text observed=2026-08-01T13:15:54.859079Z digest=sha256:c1fbdc77c174261d9bcd28f7d04267b463fb2806c083fba9543e2068c830e24c

Observation 7d7e5c37-0f8a-40c1-ae55-7bbe7e9064d1 · outbound

This paper cites Gen2sim: Scaling up robot learning in simulation with generative models.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Gen2sim: Scaling up robot learning in simulation with generative models

Reference 11

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source=pdf_text observed=2026-08-01T13:15:54.961973Z digest=sha256:380e73c2057932c2cd672ceb0bc3f8731e783173d24df16f82c10efa2bc361b3

Observation 7c04690e-9d54-415d-9512-f4e6761faac0 · outbound

This paper cites Droid: A large-scale in-the-wild robot manipulation dataset.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Droid: A large-scale in-the-wild robot manipulation dataset

Reference 12

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source=pdf_text observed=2026-08-01T13:15:55.060789Z digest=sha256:cd8f2bbc91f6e39ae7d83f67472dffa16290ecd3c28480fd27038e5b5ac7f1a3

Observation c0ed8e27-e5e3-4c47-b0d0-66b23b95c2be · outbound

This paper cites Bfm-zero: A promptable behavioral foundation model for humanoid control using unsupervised reinforcement learning, 2025.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Bfm-zero: A promptable behavioral foundation model for humanoid control using unsupervised reinforcement learning, 2025

Reference 13

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source=pdf_text observed=2026-08-01T13:15:55.137606Z digest=sha256:58c2b54db6f498f164634c9d8b193a74eda05ec3a2eec250ec8f2065530fd425

Observation eef86c5c-ca73-460b-97dc-d11bf0c9f67e · outbound

This paper cites LychSim: A Controllable and Interactive Simulation Framework for Vision Research.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents LychSim: A Controllable and Interactive Simulation Framework for Vision Research

Reference 14

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source=pdf_text observed=2026-08-01T13:15:55.233597Z digest=sha256:8c50e08e62d25912290cb09fe8c3c62e4f8e457a85cea1db79fbffd7e8d7d092

Observation ed0356c6-4486-4f3c-ac88-c43d6bef39b0 · outbound

This paper cites Scalable real2sim: Physics- aware asset generation via robotic pick-and-place setups.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Scalable real2sim: Physics- aware asset generation via robotic pick-and-place setups

Reference 15

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source=pdf_text observed=2026-08-01T13:15:55.316521Z digest=sha256:383333675a719f2d75acedcf0199a52f6c6ac059de1609321a2a764e900c79fb

Observation 4a504766-b0f8-4a8b-b0a3-ed1ac7fac5c7 · outbound

This paper cites SceneSmith: Agentic Generation of Simulation-Ready Indoor Scenes.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents SceneSmith: Agentic Generation of Simulation-Ready Indoor Scenes

Reference 16

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source=pdf_text observed=2026-08-01T13:15:55.463714Z digest=sha256:f7218bbdd0828beb3f63ca6bae0fca9f2acbe565b21524678bc3c50e1ff0f5eb

Observation 7e254e71-43d6-440b-9b97-73b924d9df32 · outbound

This paper cites SimFoundry: Modular and Automated Scene Generation for Policy Learning and Evaluation.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents SimFoundry: Modular and Automated Scene Generation for Policy Learning and Evaluation

Reference 17

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source=pdf_text observed=2026-08-01T13:15:55.586476Z digest=sha256:4c5efb0940145dc539befaeb0d84d85aa9d11056c70af103ebc0d3521df6d95d

Observation 96f9c192-62d5-4823-b932-cf57cddd4581 · outbound

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

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Mujoco: A physics engine for model-based control

Reference 18

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Observation 497df3ff-1303-432e-8780-74fddbcda23d · outbound

This paper cites Lodestar: Long-horizon dexterity via synthetic data augmentation from human demonstrations.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Lodestar: Long-horizon dexterity via synthetic data augmentation from human demonstrations

Reference 19

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source=pdf_text observed=2026-08-01T13:15:55.700512Z digest=sha256:cf5c89c9fc3c86f92cb1cd9846fc33deecc1b3f15677c5f63301ca804a7985ee

Observation 9972f34e-6139-4c03-9a14-ef076499a4cf · outbound

This paper cites Physcensis: Physics-augmented llm agents for complex physical scene arrangement.arXiv preprint arXiv:2602.14968, 2026.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Physcensis: Physics-augmented llm agents for complex physical scene arrangement.arXiv preprint arXiv:2602.14968, 2026

Reference 20

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source=pdf_text observed=2026-08-01T13:15:55.794771Z digest=sha256:11bfac7452ae08aa9715b068c5d0d8cdd1671ba37bb483b0622a515d78ae7c96

Observation e8c349ec-381a-4cc6-aa4b-ad8f62a99866 · outbound

This paper cites Foundationpose: Unified 6d pose estimation and tracking of novel objects.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Foundationpose: Unified 6d pose estimation and tracking of novel objects

Reference 21

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source=pdf_text observed=2026-08-01T13:15:55.879952Z digest=sha256:b85792cde06983c78f7da2f7b171f32b7b59a656c55d3fc4b2b024252966edfd

Observation bf5bd90d-dcd3-4a20-9762-aaf109607c13 · outbound

This paper cites Founda- tionstereo: Zero-shot stereo matching.CVPR, 2025.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Founda- tionstereo: Zero-shot stereo matching.CVPR, 2025

Reference 22

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source=pdf_text observed=2026-08-01T13:15:55.978815Z digest=sha256:900fe548bbf56864a86d0d1c31e1c14c78b492567e78cb18587f799cc4118aac

Observation de28ec71-fb38-4fec-8eda-d1cbee748bf0 · outbound

This paper cites Holodeck: Language guided generation of 3d embodied ai environments.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Holodeck: Language guided generation of 3d embodied ai environments

Reference 23

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source=pdf_text observed=2026-08-01T13:15:56.052909Z digest=sha256:b7e4dd1edf4fb6d89deabedba28abe70b4b8e93d1e4a22da0655742d48a0fc62

Observation 8df72a91-6301-4072-b0a6-be72d3df2ab9 · outbound

This paper cites Sceneweaver: All-in-one 3d scene synthesis with an extensible and self-reflective agent.Advances in neural information processing systems, 38: 140319–140351, 2026.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Sceneweaver: All-in-one 3d scene synthesis with an extensible and self-reflective agent.Advances in neural information processing systems, 38: 140319–140351, 2026

Reference 24

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source=pdf_text observed=2026-08-01T13:15:56.127443Z digest=sha256:1b9fa8ea6527b75e9469907eccaa7ba661a8945f4a052a3c0e937eec42761d2e

Observation 8eef3c43-1a54-40d0-bf25-104ee605c57d · outbound

This paper cites Articraft: An Agentic System for Scalable Articulated 3D Asset Generation.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Articraft: An Agentic System for Scalable Articulated 3D Asset Generation

Reference 25

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source=pdf_text observed=2026-08-01T13:15:56.235471Z digest=sha256:6f75c0369f23f456ef378978f5897d6b1990677998ee9ad86804fbe43a007ef3

Observation c66400f4-67a9-446b-b752-2b2783e7efe2 · outbound

This paper cites Grs: Generating robotic simulation tasks from real-world images.

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents Grs: Generating robotic simulation tasks from real-world images

Reference 26

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Pith citing papers

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