Paper Citation Record · LEDGER

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

As of 20 August 2026, this Paper Citation Record lists 89 of 89 outbound references and 14 inbound Pith citation observations for arXiv:2504.16693.

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

pith.paper-citation-record.v1
2504.16693 v2

Coverage vector

measured 89 of 89 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:01:58.905427Z

measured 103 of 103 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:27:51.552081Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

89 of 89 outbound references displayed

verified exact1
verified fuzzy59
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation d74b8db0-d07d-43ce-9f15-4d2fa31fa58e · outbound

This paper cites Physically embodied gaussian splat- ting: A visually learnt and physically grounded 3d repre- sentation for robotics.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Physically embodied gaussian splat- ting: A visually learnt and physically grounded 3d repre- sentation for robotics

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.253896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a58a3fb0-fcb0-4b37-8de4-b3a7a7fc7218 · outbound

This paper cites Cosmos world foundation model platform for physical ai.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Cosmos world foundation model platform for physical ai

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.260535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4758254b-d89a-423c-a0b0-11b2fa4696b4 · outbound

This paper cites Posing polygonal objects in the plane by pushing.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Posing polygonal objects in the plane by pushing

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.266480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49799aad-2cfd-44ad-9132-f4f51d611123 · outbound

This paper cites Optnet: Differentiable optimization as a layer in neural networks.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Optnet: Differentiable optimization as a layer in neural networks

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.275086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b6e3b80-770c-4c3d-bae4-f9dd0f895c9f · outbound

This paper cites Incremental Few-Shot Adaptation for Non-Prehensile Object Manipulation using Parallelizable Physics Simulators.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Incremental Few-Shot Adaptation for Non-Prehensile Object Manipulation using Parallelizable Physics Simulators

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-16T11:01:59.192491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ccfc9e44-013b-4e22-b5b9-9c55a0fa78b8 · outbound

This paper cites Data quality in imitation learning.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Data quality in imitation learning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.295716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f9890f52-7b87-444f-8f65-8f32a399a983 · outbound

This paper cites Language models are few-shot learners.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Language models are few-shot learners

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.304780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da9f2b1e-d69f-4f69-bb11-370864f46d87 · outbound

This paper cites Neuma: Neural material adaptor for visual grounding of intrinsic dynamics.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Neuma: Neural material adaptor for visual grounding of intrinsic dynamics

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.315870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 99b077ae-47ab-4495-9717-7800c97c41a9 · outbound

This paper cites Neural radiance fields for dynamic view synthesis using local temporal priors.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Neural radiance fields for dynamic view synthesis using local temporal priors

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.321508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8ea5238-254c-40da-8ff9-9b4554b1a6c0 · outbound

This paper cites Towards Domain Rand.RoboGSimASID2D PhysicsPIN-WM Time lapse Fig.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Towards Domain Rand.RoboGSimASID2D PhysicsPIN-WM Time lapse Fig

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.327623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 455400ea-a16a-4427-bef8-ea982bfbbadc · outbound

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

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Diffusion policy: Visuomotor policy learning via action diffusion

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.334058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b577f91e-943d-43b3-b774-7948e94966d7 · outbound

This paper cites Policy transfer via modularity and reward guiding.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Policy transfer via modularity and reward guiding

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.846409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 461fd4bf-aef7-463d-a568-eae1e5f136ff · outbound

This paper cites Rigid body simulation with contact and constraints.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Rigid body simulation with contact and constraints

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.828434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0a2a3c95-6217-4e2b-8bf6-f2023e7e967f · outbound

This paper cites Pybullet, a python module for physics simulation for games, robotics and machine learning, 2016.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Pybullet, a python module for physics simulation for games, robotics and machine learning, 2016

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.351811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0df1d9e-8909-4e80-90eb-d0e294c7b1fe · outbound

This paper cites Automated creation of digital cousins for robust policy learning.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Automated creation of digital cousins for robust policy learning

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.784837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4537234f-052e-46cf-9fc1-a52e077c08ed · outbound

This paper cites End-to-end differentiable physics for learning and control.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation End-to-end differentiable physics for learning and control

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.763130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0ac12816-813d-48cb-858c-f19d46132733 · outbound

This paper cites A framework for push-grasping in clutter.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation A framework for push-grasping in clutter

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.741880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 75029239-0a51-400e-aacd-f0169d4e3ddb · outbound

This paper cites Finding formations for the non- prehensile object transportation with differentially-driven mobile robots.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Finding formations for the non- prehensile object transportation with differentially-driven mobile robots

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.720337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d0a426ba-5041-4066-a613-0aef61a4ff5a · outbound

This paper cites Con- text is everything: Implicit identification for dynamics adaptation.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Con- text is everything: Implicit identification for dynamics adaptation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.694517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fbc7efdd-103a-4db3-8864-cf3346e061d4 · outbound

This paper cites Rigid body dynamics algorithms.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Rigid body dynamics algorithms

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.392168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8401d88-d57f-4222-8195-0d73029dbcb8 · outbound

This paper cites Learning visuotactile estimation and control for non-prehensile manipulation under occlusions.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Learning visuotactile estimation and control for non-prehensile manipulation under occlusions

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.659829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b3f1b08a-0f08-4a8c-a7ce-4466bb2e5188 · outbound

This paper cites Relightable 3d gaussians: Realistic point cloud relighting with brdf decomposition and ray tracing.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Relightable 3d gaussians: Realistic point cloud relighting with brdf decomposition and ray tracing

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.639705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 57dce3b1-b74d-42dc-b081-b6f4b8431c53 · outbound

This paper cites Learning nonprehen- sile dynamic manipulation: Sim2real vision-based policy with a surgical robot.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Learning nonprehen- sile dynamic manipulation: Sim2real vision-based policy with a surgical robot

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.612913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9401d4af-5500-44e0-8107-7eb248536954 · outbound

This paper cites Digital twin: Miti- gating unpredictable, undesirable emergent behavior in complex systems.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Digital twin: Miti- gating unpredictable, undesirable emergent behavior in complex systems

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.590377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 93b3d10d-5dca-4d96-a2c9-e05ad25ee5cb · outbound

This paper cites World Models.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation World Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.428051Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8cde798-ed61-4534-9a4c-8b390c19198a · outbound

This paper cites Lillicrap, Jimmy Ba, and Mo- hammad Norouzi.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Lillicrap, Jimmy Ba, and Mo- hammad Norouzi

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.568041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ac756968-2e06-493a-bebd-b483a85078f2 · outbound

This paper cites Lillicrap, Mohammad Norouzi, and Jimmy Ba.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Lillicrap, Mohammad Norouzi, and Jimmy Ba

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.546293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b8da6802-16dc-4cd3-8ea3-dbd46ab8921d · outbound

This paper cites Temporal difference learning for model predictive control.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Temporal difference learning for model predictive control

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.519531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5454505c-758a-4223-ba9a-f30b6cdfc073 · outbound

This paper cites TD- MPC2: scalable, robust world models for continuous control.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation TD- MPC2: scalable, robust world models for continuous control

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.497591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 18fefd14-f1b3-4141-b47e-a79fe754288d · outbound

This paper cites Multiple view geometry in computer vision.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Multiple view geometry in computer vision

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.458759Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df71f163-789f-41c3-8e1c-e3ae7c2c0365 · outbound

This paper cites Neuralsim: Augmenting differentiable simulators with neural networks.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Neuralsim: Augmenting differentiable simulators with neural networks

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.461132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3454643f-a0fe-489b-a6df-45abf205c660 · outbound

This paper cites Denoising diffusion probabilistic models.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Denoising diffusion probabilistic models

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.443359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3a8f598f-6a34-475d-bbeb-6503176793dd · outbound

This paper cites Data scaling laws in imitation learning for robotic manipulation.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Data scaling laws in imitation learning for robotic manipulation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.422750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 45e4c416-f818-4933-803d-2b016c0d7445 · outbound

This paper cites 2d gaussian splatting for geometri- cally accurate radiance fields.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation 2d gaussian splatting for geometri- cally accurate radiance fields

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.493998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1fcd552-4127-45d2-a32a-449c8d0c691a · outbound

This paper cites Imitation learning: A survey of learning methods.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Imitation learning: A survey of learning methods

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.383579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2a82eb2e-f1bf-4710-a9c4-87b2954376e4 · outbound

This paper cites Rlbench: The robot learning bench- mark & learning environment.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Rlbench: The robot learning bench- mark & learning environment

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.355962Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 230f5294-706f-4a35-be0d-ff50a3795886 · outbound

This paper cites State: Learning structure and texture representations for novel view synthesis.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation State: Learning structure and texture representations for novel view synthesis

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.338440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6554356f-f642-42f4-9718-f5bbe83befeb · outbound

This paper cites Frnerf: Fusion and regularization fields for dynamic view synthesis.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Frnerf: Fusion and regularization fields for dynamic view synthesis

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.319028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8606c46b-f39f-412d-853f-fbec6914251d · outbound

This paper cites Scalable deep reinforcement learning for vision- based robotic manipulation.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Scalable deep reinforcement learning for vision- based robotic manipulation

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.285894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8c621947-c38f-4eb5-85c7-a62cf1ad289f · outbound

This paper cites Physics-based rigid body object tracking and friction filtering from rgb-d videos.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Physics-based rigid body object tracking and friction filtering from rgb-d videos

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.264577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3b367e5f-9b15-40c1-94cc-32c4c43de98e · outbound

This paper cites Scaling Laws for Neural Language Models.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Scaling Laws for Neural Language Models

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.541340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c581f499-32fa-471d-8db0-d2fb96b05690 · outbound

This paper cites 3d gaussian splatting for real-time radiance field rendering.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation 3d gaussian splatting for real-time radiance field rendering

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.555633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8501ec2-17c7-4ac8-a400-ce60414c547b · outbound

This paper cites Robotic control with partial visual information.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Robotic control with partial visual information

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.235305Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4850d297-0886-409f-b683-745831666b63 · outbound

This paper cites Investigating Compounding Prediction Errors in Learned Dynamics Models.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Investigating Compounding Prediction Errors in Learned Dynamics Models

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.585063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d03d745-9ecc-4488-9382-bbaf17a6d0f8 · outbound

This paper cites RoboGSim: A Real2Sim2Real Robotic Gaussian Splatting Simulator.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation RoboGSim: A Real2Sim2Real Robotic Gaussian Splatting Simulator

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.591954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82ba08b3-aced-4676-b082-a3e419002c05 · outbound

This paper cites Lin, Chenfanfu Jiang, and Chuang Gan.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Lin, Chenfanfu Jiang, and Chuang Gan

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.215198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e807c39e-a49a-4fc1-8ca6-3426aca4bd4c · outbound

This paper cites Difffr: Differentiable sph-based fluid-rigid coupling for rigid body control.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Difffr: Differentiable sph-based fluid-rigid coupling for rigid body control

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.193458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 71445422-9d30-4596-a855-1b6c5caca66d · outbound

This paper cites Deep lagrangian networks: Using physics as model prior for deep learning.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Deep lagrangian networks: Using physics as model prior for deep learning

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.172708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation cc742004-8b6e-468b-a671-a1ba8c521d75 · outbound

This paper cites Isaac gym: High performance GPU based physics simulation for robot learning.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Isaac gym: High performance GPU based physics simulation for robot learning

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.153471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 472c2fe7-d698-415b-960d-5a6af93d7cf5 · outbound

This paper cites Mechanics and planning of manip- ulator pushing operations.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Mechanics and planning of manip- ulator pushing operations

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.129345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fa11b022-1d76-4f91-8e4b-597a4ef9ff10 · outbound

This paper cites Cvxgen: A code generator for embedded convex optimization.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Cvxgen: A code generator for embedded convex optimization

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.107554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 76f72da6-98b1-49f8-8881-a35f226354e7 · outbound

This paper cites Active domain randomiza- tion.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Active domain randomiza- tion

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.081794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3573d252-1fae-4838-947a-64acd92cb0d3 · outbound

This paper cites ASID: Active explo- ration for system identification in robotic manipulation.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation ASID: Active explo- ration for system identification in robotic manipulation

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.050221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4daa0c3f-2d2d-4683-84b5-bd51ff5f421c · outbound

This paper cites Structured world models from human videos.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Structured world models from human videos

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:02:00.020918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8d32bf1f-cfbb-4690-b1bd-e9d01233913e · outbound

This paper cites Learning robust perceptive locomotion for quadrupedal robots in the wild.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Learning robust perceptive locomotion for quadrupedal robots in the wild

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.996017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 79b8ed07-cc26-442d-8ced-6b6a4e4ea0da · outbound

This paper cites Nerf: Representing scenes as neural radiance fields for view synthesis.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Nerf: Representing scenes as neural radiance fields for view synthesis

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.668997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67a13fbb-1826-4fed-9581-a0e096ad1763 · outbound

This paper cites Neural 3d reconstruction from sparse views using geometric priors.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Neural 3d reconstruction from sparse views using geometric priors

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.959706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d19aec20-2f7b-4d06-bc3a-a47786bb0443 · outbound

This paper cites Instant neural graphics primitives with a multiresolution hash encoding.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Instant neural graphics primitives with a multiresolution hash encoding

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.938489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 4366a8d7-4b07-40a5-9398-9b62dd0d40d4 · outbound

This paper cites an unresolved cited work.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Unresolved cited work

Reference 59

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:01:59.912731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 174a09b8-4aa5-4a3a-830f-14e7806bc44e · outbound

This paper cites Sim-to-real transfer of robotic control with dynamics randomization.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Sim-to-real transfer of robotic control with dynamics randomization

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.887995Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 95d69363-84c8-4660-b0be-ed33560386c6 · outbound

This paper cites Learning transferable visual models from natural lan- guage supervision.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Learning transferable visual models from natural lan- guage supervision

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.862604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0a7c5784-e0e8-415e-be69-8031986a1f58 · outbound

This paper cites Offline reinforcement learning from im- ages with latent space models.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Offline reinforcement learning from im- ages with latent space models

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.829892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 98e386c4-5f1a-4951-8f8f-9cf56728c0bc · outbound

This paper cites Physics-informed neural networks: A deep learn- ing framework for solving forward and inverse problems involving nonlinear partial differential equations.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Physics-informed neural networks: A deep learn- ing framework for solving forward and inverse problems involving nonlinear partial differential equations

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.807745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f374b153-0e4c-417e-b603-1a7a974ed5f5 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation SAM 2: Segment Anything in Images and Videos

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.729898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47140962-ff62-42f8-8264-d92cc8dfa2fb · outbound

This paper cites The cross- entropy method: a unified approach to combinatorial op- timization, Monte-Carlo simulation, and machine learn- ing.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation The cross- entropy method: a unified approach to combinatorial op- timization, Monte-Carlo simulation, and machine learn- ing

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.782115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 29dcbf14-4cac-47cc-a17d-11ea0dc0492e · outbound

This paper cites Proximal Policy Optimization Algorithms.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Proximal Policy Optimization Algorithms

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.743143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d714285-5396-4219-ad0a-9e86ddbd85a7 · outbound

This paper cites Learning to slide unknown objects with differentiable physics simu- lations.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Learning to slide unknown objects with differentiable physics simu- lations

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.758902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5c22b9dc-5756-47c7-af9c-7dbd111140ca · outbound

This paper cites Diffsdfsim: Dif- ferentiable rigid-body dynamics with implicit shapes.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Diffsdfsim: Dif- ferentiable rigid-body dynamics with implicit shapes

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.737566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 1b3a1179-fedf-482c-9be4-02cc3f37d6a9 · outbound

This paper cites Reinforcement learning: An introduc- tion.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Reinforcement learning: An introduc- tion

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.762543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e94ac0da-2b8a-45de-b235-8dba3dc5dab5 · outbound

This paper cites Sukhatme, Fabio Ramos, and Yashraj S.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Sukhatme, Fabio Ramos, and Yashraj S

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.691278Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation aab5e76d-528d-4554-8a20-bb9e9759b4a5 · outbound

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

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Domain ran- domization for transferring deep neural networks from simulation to the real world

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.668108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 9d686cc9-7737-4a22-9a07-8858059b8897 · outbound

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

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Foundationpose: Unified 6d pose estimation and tracking of novel objects

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.640832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b4ac34e0-ee42-4c55-9be1-19556569a005 · outbound

This paper cites Model predictive path integral control: From theory to parallel computation.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Model predictive path integral control: From theory to parallel computation

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.795709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68420ff1-4c65-4ba8-b28f-88772f61a0a0 · outbound

This paper cites Daydreamer: World models for physical robot learning.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Daydreamer: World models for physical robot learning

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.591683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 14b042ec-1d75-4855-8270-4da3a0ef80ca · outbound

This paper cites Recent advances in 3d gaussian splatting.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Recent advances in 3d gaussian splatting

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.559963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 936fa483-a27c-4bcc-9669-5331a7888128 · outbound

This paper cites Jnerf: An efficient heterogeneous nerf model zoo based on jittor.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Jnerf: An efficient heterogeneous nerf model zoo based on jittor

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.529648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6b5bd428-e7cb-43f3-b173-f6eb1d6090c7 · outbound

This paper cites Visual imitation made easy.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Visual imitation made easy

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.499756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2c367471-dbc0-42c4-9278-1547f0bc7e70 · outbound

This paper cites More than a million ways to be pushed.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation More than a million ways to be pushed

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.467834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ccbd101b-63c6-40ec-b5fb-b4062ea11f6f · outbound

This paper cites Mopo: Model-based offline policy optimization.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Mopo: Model-based offline policy optimization

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.446433Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 653b00ee-62e9-4314-97c2-0d4bca439062 · outbound

This paper cites Rearrangement with nonprehensile manipulation using deep reinforcement learning.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Rearrangement with nonprehensile manipulation using deep reinforcement learning

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.428075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 8f12f352-8dbf-43c8-910e-4b384bbc2e8f · outbound

This paper cites Domain randomization and pyramid consistency: Simulation-to-real generalization without accessing tar- get domain data.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Domain randomization and pyramid consistency: Simulation-to-real generalization without accessing tar- get domain data

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.404566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e8f4fd83-5458-4f65-8770-a10947287263 · outbound

This paper cites Learn- ing physically realizable skills for online packing of general 3d shapes.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Learn- ing physically realizable skills for online packing of general 3d shapes

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.359086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation d06bb3ef-aeed-4085-b772-0389f7fe77e8 · outbound

This paper cites Deliberate Planning of 3D Bin Packing on Packing Configuration Trees.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Deliberate Planning of 3D Bin Packing on Packing Configuration Trees

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.862374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8188f31d-da25-41c7-bf15-3ff86160bdaf · outbound

This paper cites DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-16T11:01:58.868131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bece1f0-cd47-4844-9e59-9f7c0c2ee9e8 · outbound

This paper cites Pushing revisited: Differential flatness, trajectory planning, and stabilization.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Pushing revisited: Differential flatness, trajectory planning, and stabilization

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.334452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 3650fdcc-0508-40c7-9e0c-839c318928b3 · outbound

This paper cites Domain Rand + I.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Domain Rand + I

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.315301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2b349150-0f14-44ab-8bc6-467bb8217d2b · outbound

This paper cites an unresolved cited work.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Unresolved cited work

Reference 87

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:01:59.288015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 94ad2ec7-d87e-490d-9831-47266d82bd1a · outbound

This paper cites To fairly compare the accuracy across different methods, we estimate one parameter at a time while keeping the others fixed at their GT values.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation To fairly compare the accuracy across different methods, we estimate one parameter at a time while keeping the others fixed at their GT values

Reference 88

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:01:59.251819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 02e1c049-d8da-4b01-b6fa-8e48cd73bc05 · outbound

This paper cites an unresolved cited work.

PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation Unresolved cited work

Reference 89

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:01:59.220280Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Pith citing papers

Observation c587bf31-9ef6-4dcb-8481-069e582342dd · inbound

Where to Touch, How to Contact: A Hierarchical RL-MPC Framework for Geometry-Aware Sim-to-Real Manipulation cites this paper.

Where to Touch, How to Contact: A Hierarchical RL-MPC Framework for Geometry-Aware Sim-to-Real Manipulation PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T10:14:07.992727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64ab2a59-6353-4359-b1e0-b56373ea7352 · inbound

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond cites this paper.

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 224

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:26:07.487363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a2c23be1-0113-4428-a6b2-8ed585a2ea9b · inbound

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond cites this paper.

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 224

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:29:59.620713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation ff42cb8b-7446-4380-8cc3-31be5c854700 · inbound

OrbiSim: World Models as Differentiable Physics Engines for Embodied Intelligence cites this paper.

OrbiSim: World Models as Differentiable Physics Engines for Embodied Intelligence PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-20T21:43:45.619309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 941475c3-e85f-4da5-8b11-15a963263dd8 · inbound

ECG-WM: A Physiology-Informed ECG World Model for Clinical Intervention Simulation cites this paper.

ECG-WM: A Physiology-Informed ECG World Model for Clinical Intervention Simulation PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T12:23:16.857043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b749a5fc-a22a-4c14-8c7e-54e364afd392 · inbound

Learning Action-Conditional and Object-Centric Gaussian Splatting World Models for Rigid Objects cites this paper.

Learning Action-Conditional and Object-Centric Gaussian Splatting World Models for Rigid Objects PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-01T23:26:22.804567Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation fa7ccbb4-e456-419a-bd13-c417fa885fd6 · inbound

Robots Need More than VLA and World Models cites this paper.

Robots Need More than VLA and World Models PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 41

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T13:46:59.212374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 72d1ac0b-7bbc-4c0a-89bf-973028303cdd · inbound

Looped World Models cites this paper.

Looped World Models PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 15

Resolution: metadata mismatch; arxiv_id, observed 2026-06-27T01:50:21.193268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5b95fe7e-3635-4ac4-b1cb-3b744c21238c · 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 PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T11:26:53.595527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6f12e01a-12f5-49f8-a814-4957dd28105d · 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 PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T20:38:55.083612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 90dbe2df-2ac6-4692-8dfe-45dee1b1be7f · 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 PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 14

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3676279f-902b-4da0-ada3-3fa53edfbe4c · 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 PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T09:18:01.909634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e15a5e84-dcd3-4b77-a693-48b5a36ccb91 · inbound

PhysMani: Physics-principled 3D World Model for Dynamic Object Manipulation cites this paper.

PhysMani: Physics-principled 3D World Model for Dynamic Object Manipulation PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 38

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T12:08:06.342824Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 18897452-fb25-4b94-83ba-2e40c48b5c45 · inbound

Energy-Structured Latent World Models with Neural Time Fields for Physically Constistent Open-World Motion Planning cites this paper.

Energy-Structured Latent World Models with Neural Time Fields for Physically Constistent Open-World Motion Planning PIN-WM: Learning Physics-INformed World Models for Non-Prehensile Manipulation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T14:27:51.552081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.