Paper Citation Record · LEDGER

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations

As of 7 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 1 inbound Pith citation observation for arXiv:2602.02741.

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

pith.paper-citation-record.v1
2602.02741 v2

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:19:09.631200Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-08T11:22:38.704101Z

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

29 of 29 outbound references displayed

verified exact0
verified fuzzy0
unresolved29
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation ad7c5284-49bd-451f-b36f-ca2a3a7820c5 · outbound

This paper cites Learning to generalize kinematic models to novel objects,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Learning to generalize kinematic models to novel objects,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:06.444037Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 302aac42-d356-4190-bf39-44351d40541f · outbound

This paper cites Flowbot++: Learning generalized articulated objects manipulation via articulation projection,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Flowbot++: Learning generalized articulated objects manipulation via articulation projection,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:06.538062Z

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Unavailable: canonical work link unavailable.

Observation cee67a05-90f3-486c-b022-032d8b03af7e · outbound

This paper cites Flowbot3d: Learning 3d artic- ulation flow to manipulate articulated objects,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Flowbot3d: Learning 3d artic- ulation flow to manipulate articulated objects,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:06.623772Z

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Observation 03756538-35a2-40d5-9dc6-16a1ab94ddbe · outbound

This paper cites URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations URDFormer: A Pipeline for Constructing Articulated Simulation Environments from Real-World Images

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:06.749102Z

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Observation d2618fdc-cf18-4444-be93-e3c2c42e4bba · outbound

This paper cites GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable Parts.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations GAPartNet: Cross-Category Domain-Generalizable Object Perception and Manipulation via Generalizable and Actionable Parts

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:06.870734Z

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Observation a14f0f8f-de43-4b1f-832e-d1338bcebdda · outbound

This paper cites Screwnet: Category- independent articulation model estimation from depth images using screw theory,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Screwnet: Category- independent articulation model estimation from depth images using screw theory,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:06.961638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea28ecb1-b979-44fb-8b45-4a0fd22a7e13 · outbound

This paper cites Distributional depth-based estimation of object articulation models,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Distributional depth-based estimation of object articulation models,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:07.047356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0ea3f8a-6133-4433-9f5b-3157beadc59a · outbound

This paper cites NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:07.155652Z

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Observation 22664b87-e4e5-4776-b9c5-69cc4a413e77 · outbound

This paper cites NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstruction

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:07.317806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0651a07-3924-468a-a638-1ee123729f39 · outbound

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

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations 3d gaussian splatting for real-time radiance field rendering,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:07.392736Z

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Observation 663d1a76-4d85-446a-ad3e-5048cf5d3bbf · outbound

This paper cites ScrewSplat: An End-to-End Method for Articulated Object Recognition.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations ScrewSplat: An End-to-End Method for Articulated Object Recognition

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:07.463155Z

Source-reported events for the cited work

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Observation fa24995a-dae1-42db-8c94-5260b70fd5ae · outbound

This paper cites ArtGS:3D Gaussian Splatting for Interactive Visual-Physical Modeling and Manipulation of Articulated Objects.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations ArtGS:3D Gaussian Splatting for Interactive Visual-Physical Modeling and Manipulation of Articulated Objects

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:07.591273Z

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Observation 9ef28814-bb1d-4c32-bf3d-edccf7be2b41 · outbound

This paper cites ArtGS: Building Interactable Replicas of Complex Articulated Objects via Gaussian Splatting.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations ArtGS: Building Interactable Replicas of Complex Articulated Objects via Gaussian Splatting

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:07.672618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2ac6351-c3c9-4e76-a307-8eed2ee3b230 · outbound

This paper cites Robot See Robot Do: Imitating Articulated Object Manipulation with Monocular 4D Reconstruction.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Robot See Robot Do: Imitating Articulated Object Manipulation with Monocular 4D Reconstruction

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:07.773063Z

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Unavailable: canonical work link unavailable.

Observation 2db63951-46f1-4ab9-8087-3a59a7602d8f · outbound

This paper cites Category-Level Articulated Object Pose Estimation.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Category-Level Articulated Object Pose Estimation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:07.876571Z

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Observation b3acac3d-30e4-43b8-bc1e-5a12bc170d64 · outbound

This paper cites Deep part induction from articulated object pairs,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Deep part induction from articulated object pairs,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:07.951149Z

Source-reported events for the cited work

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Observation 745097c8-2801-4cd9-9ac2-6d94385528f2 · outbound

This paper cites Manipulating articulated objects with interac- tive perception,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Manipulating articulated objects with interac- tive perception,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:08.012101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f77d79db-1c26-4315-933b-35bbf045de15 · outbound

This paper cites Interactive segmentation, tracking, and kinematic modeling of unknown 3d artic- ulated objects,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Interactive segmentation, tracking, and kinematic modeling of unknown 3d artic- ulated objects,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:08.138860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e959e910-643f-407d-925f-28ff27dc50e7 · outbound

This paper cites An integrated approach to visual perception of articulated objects,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations An integrated approach to visual perception of articulated objects,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:08.216235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11397be9-4f4e-4e65-bb48-a2468b266f19 · outbound

This paper cites Structure from action: Learning interactions for articulated object 3d structure discovery,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Structure from action: Learning interactions for articulated object 3d structure discovery,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:08.344752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68679722-0dff-4080-9fc0-6b889e820a65 · outbound

This paper cites PARIS: Part-level recon- struction and motion analysis for articulated objects,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations PARIS: Part-level recon- struction and motion analysis for articulated objects,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:08.513212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9123d90f-b94a-452b-9965-013017947ddd · outbound

This paper cites Neural implicit representation for building digital twins of unknown articulated objects,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Neural implicit representation for building digital twins of unknown articulated objects,

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:08.581886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d4fa4f2-b088-4f72-8758-c643ba2c8d14 · outbound

This paper cites SAPIEN: A simulated part-based interactive environment,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations SAPIEN: A simulated part-based interactive environment,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:08.758762Z

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Unavailable: canonical work link unavailable.

Observation ad1915b1-375e-4f9d-bd53-2a0f8ebfc12b · outbound

This paper cites ShapeNet: An Information-Rich 3D Model Repository.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations ShapeNet: An Information-Rich 3D Model Repository

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:08.925323Z

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Observation 620b4673-9481-4c20-ab5b-6cc30b7d53bf · outbound

This paper cites PartNet: A large-scale benchmark for fine-grained and hierarchical part-level 3D object understanding,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations PartNet: A large-scale benchmark for fine-grained and hierarchical part-level 3D object understanding,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:09.033908Z

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Observation 3095347d-2bc0-4cac-8f86-9cd0af844637 · outbound

This paper cites Automatic generation and detection of highly reliable fiducial markers under occlusion,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Automatic generation and detection of highly reliable fiducial markers under occlusion,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:09.154215Z

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Observation 96e4e6fe-f0a5-45a6-98f2-7df572385d8f · outbound

This paper cites End-to-End Object Detection with Transformers.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations End-to-End Object Detection with Transformers

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:09.309064Z

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Observation d459b7d0-d486-462a-a2dd-8b9c81f86f98 · outbound

This paper cites PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:09.441508Z

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Observation db997932-63e7-448e-b7dc-c2ed18bf2eee · outbound

This paper cites Attention is all you need,.

PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations Attention is all you need,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T05:19:09.631200Z

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Pith citing papers

Observation c7404b82-5c02-42cf-99ba-af17c8d16f08 · inbound

QDTraj: Exploration of Diverse Trajectory Primitives for Articulated Objects Robotic Manipulation cites this paper.

QDTraj: Exploration of Diverse Trajectory Primitives for Articulated Objects Robotic Manipulation PokeNet: Learning Kinematic Models of Articulated Objects from Human Observations

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-07-16T02:21:45.096680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.