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Paper Citation Record · LEDGER

Generalizable Articulated Object Perception with Superpoints

As of 19 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2412.16656.

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

pith.paper-citation-record.v1
2412.16656 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:25:55.798347Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

31 of 31 outbound references displayed

  • verified exact0
  • verified fuzzy17
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2016c903-aef9-44e7-81e9-f278260e3e16 · outbound

This paper cites V ocapter: V oting- based pose tracking for category-level articulated object via inter-frame priors,.

Generalizable Articulated Object Perception with Superpoints V ocapter: V oting- based pose tracking for category-level articulated object via inter-frame priors,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T10:25:56.423327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.642430Z digest=sha256:5e871eaf49658af984d4f2737dabb98e2bf5c5af5bd7d8e5d3cd5a99a6637eed

Observation 017774a1-8049-47ae-8c2f-251bf9630dfb · outbound

This paper cites Kpa- tracker: Towards robust and real-time category-level articulated object 6d pose tracking,.

Generalizable Articulated Object Perception with Superpoints Kpa- tracker: Towards robust and real-time category-level articulated object 6d pose tracking,

Reference 2

Resolution
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raw_fallback, observed 2026-08-11T10:25:56.405575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.647797Z digest=sha256:c5cb852024e9bdcd7366201dfdd7d7c25c1c83d963c35412786b0ed1246983c1

Observation 65ece37c-82e7-4a6a-a6e6-edceb1926c4a · outbound

This paper cites ManiPose: A Comprehensive Benchmark for Pose-aware Object Manipulation in Robotics.

Generalizable Articulated Object Perception with Superpoints ManiPose: A Comprehensive Benchmark for Pose-aware Object Manipulation in Robotics

Reference 3

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:25:55.652727Z digest=sha256:614621692da9fcbe3a8a91a2ef7ace17cbfc7fab46e84eb7dd6cc9f4e8f71c62

Observation fa478620-0cb7-4084-b545-0c9d16067ed2 · outbound

This paper cites Gapartnet: Cross-category domain-generalizable object perception and manipulation via generalizable and actionable parts,.

Generalizable Articulated Object Perception with Superpoints Gapartnet: Cross-category domain-generalizable object perception and manipulation via generalizable and actionable parts,

Reference 4

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source=pdf_text observed=2026-08-11T10:25:55.658158Z digest=sha256:ef8c4d9019bbd2c6d58f6bfb04c132da88a2924284f5cf592c997642e02efdef

Observation f5fb9d78-5049-4991-8462-e64f8834ea88 · outbound

This paper cites End-to-End Affordance Learning for Robotic Manipulation.

Generalizable Articulated Object Perception with Superpoints End-to-End Affordance Learning for Robotic Manipulation

Reference 5

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source=pdf_text observed=2026-08-11T10:25:55.663281Z digest=sha256:fca8351e6572187a44243d0109dd015f9057cc990914fd86c8e833c51c25af2b

Observation ed69884b-1f22-4548-8cc3-8046f76c5d14 · outbound

This paper cites Where2act: From pixels to actions for articulated 3d objects,.

Generalizable Articulated Object Perception with Superpoints Where2act: From pixels to actions for articulated 3d objects,

Reference 6

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:25:55.670296Z digest=sha256:e4ffbcd0010c2e7f20abb90ab75c52887ecb440863cf9fc5b4be2143f19839e6

Observation 644c65d5-2421-454c-9bbf-ef259f75cd29 · outbound

This paper cites Category-level articulated object 9d pose estimation via reinforcement learning,.

Generalizable Articulated Object Perception with Superpoints Category-level articulated object 9d pose estimation via reinforcement learning,

Reference 7

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.676079Z digest=sha256:bf0aea47608e85cbf80999825185b31de2b6bdb7f205694a718b0a3eade77610

Observation 8bcbdf53-6fae-4fe0-8edb-d763f6a99ba4 · outbound

This paper cites VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects.

Generalizable Articulated Object Perception with Superpoints VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects

Reference 8

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source=pdf_text observed=2026-08-11T10:25:55.681332Z digest=sha256:4748ec5aaa191a845a6168b8a1cba50ad79fc81cbbc40685aa642c89fde4a7e5

Observation a10e4edb-1449-4333-94d5-ee7d927540ef · outbound

This paper cites Where2explore: Few- shot affordance learning for unseen novel categories of articulated objects,.

Generalizable Articulated Object Perception with Superpoints Where2explore: Few- shot affordance learning for unseen novel categories of articulated objects,

Reference 9

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raw_fallback, observed 2026-08-11T10:25:56.349285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.686470Z digest=sha256:86110a6f9749d9bde296dab200477b36af50711baef3563d2b7a9966a5c9159f

Observation a112e3d9-9265-491a-b913-4a3972bd79b1 · outbound

This paper cites Survey on Modeling of Human-made Articulated Objects.

Generalizable Articulated Object Perception with Superpoints Survey on Modeling of Human-made Articulated Objects

Reference 10

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source=pdf_text observed=2026-08-11T10:25:55.691666Z digest=sha256:3fd1caa1891185d4859d62b2b1f9a9600db16bf19e4594622fd99b176ee12781

Observation 845806db-fa81-4f6f-aa47-ea992ca08b41 · outbound

This paper cites Captra: Category-level pose tracking for rigid and articulated objects from point clouds,.

Generalizable Articulated Object Perception with Superpoints Captra: Category-level pose tracking for rigid and articulated objects from point clouds,

Reference 11

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raw_fallback, observed 2026-08-11T10:25:56.332060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.697730Z digest=sha256:62dfcff5a49b4a30e5eeb06f36ae6dd98dd49c672887f54a23c07e549c8c08bc

Observation 6b1ffd22-0e24-4c47-9d10-9c88c9113077 · outbound

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

Generalizable Articulated Object Perception with Superpoints Screwnet: Category- independent articulation model estimation from depth images using screw theory,

Reference 12

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source=pdf_text observed=2026-08-11T10:25:55.702778Z digest=sha256:bc88c1e0823b4403da9d32731f80cd4e151bc97d290a431d8a47419c708b7781

Observation ebd38056-83dc-40ac-8484-916dca1a9814 · outbound

This paper cites FlowBot++: Learning Generalized Articulated Objects Manipulation via Articulation Projection.

Generalizable Articulated Object Perception with Superpoints FlowBot++: Learning Generalized Articulated Objects Manipulation via Articulation Projection

Reference 13

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:25:55.707856Z digest=sha256:f0175d6995c35290db45be17bff5574cc3199eece019cca6f085db3bc18adf83

Observation fffe2ebc-5df8-4da8-b594-8775fbdd13fc · outbound

This paper cites Ditto: Building digital twins of articulated objects from interaction,.

Generalizable Articulated Object Perception with Superpoints Ditto: Building digital twins of articulated objects from interaction,

Reference 14

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:25:55.713316Z digest=sha256:6bb7bce47ccf3a2ed75b4a501cc7374a158f66a3a897861c32f87b710b153315

Observation 6dd1c3ad-5b97-4843-9ead-01b72371dcf7 · outbound

This paper cites Gamma: Generalizable articulation modeling and manipulation for articulated objects,.

Generalizable Articulated Object Perception with Superpoints Gamma: Generalizable articulation modeling and manipulation for articulated objects,

Reference 15

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raw_fallback, observed 2026-08-11T10:25:56.291574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.718246Z digest=sha256:f35f60c874f06ab187f0f8fd1f1d154097f6610ec8aad6fbe8beb7a291be5f51

Observation 82734ad5-b713-4542-a9fe-94a328f33b23 · outbound

This paper cites Pointnet++: Deep hierarchical feature learning on point sets in a metric space,.

Generalizable Articulated Object Perception with Superpoints Pointnet++: Deep hierarchical feature learning on point sets in a metric space,

Reference 16

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raw_fallback, observed 2026-08-11T10:25:56.274529Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.723394Z digest=sha256:ffb51d3b703f20c742c940f85d586c1928df644f75df4b9337f623fd37dbc58e

Observation 1512866b-3aae-4f20-a3d8-566c054bd41d · outbound

This paper cites Category-level articulated object pose estimation,.

Generalizable Articulated Object Perception with Superpoints Category-level articulated object pose estimation,

Reference 17

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source=pdf_text observed=2026-08-11T10:25:55.727993Z digest=sha256:f0e43e292c75c8f6f74eaaed15a9f353b945e39251b079d0c1185c3ca163b033

Observation 6164bf54-0ba2-4965-8902-92dfec268616 · outbound

This paper cites Rethinking 3d convolution in ℓp-norm space,.

Generalizable Articulated Object Perception with Superpoints Rethinking 3d convolution in ℓp-norm space,

Reference 18

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.732847Z digest=sha256:eb95ac5a138d1d9ccbea13242bbbd49ec621f2bbdbb42f2f18b6d97a6f1355ab

Observation c7c09eb0-303a-4acb-b425-04a53bf58340 · outbound

This paper cites Efficient 3d semantic segmentation with superpoint transformer,.

Generalizable Articulated Object Perception with Superpoints Efficient 3d semantic segmentation with superpoint transformer,

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.737902Z digest=sha256:e766df6d42124ab6ce89ead62381fa7c86836ab326be31e56a3399c66b5ba342

Observation 40c690c8-f027-4949-b641-e60e47646e9f · outbound

This paper cites Superpoint network for point cloud oversegmentation,.

Generalizable Articulated Object Perception with Superpoints Superpoint network for point cloud oversegmentation,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.742854Z digest=sha256:08ba93196ebd2e1ea4bf6b13fd2de192ed8e357a56fd6ed603a685c5dfee3316

Observation 335137c7-2498-4b6a-a047-150e28660d93 · outbound

This paper cites Oneformer3d: One transformer for unified point cloud segmentation,.

Generalizable Articulated Object Perception with Superpoints Oneformer3d: One transformer for unified point cloud segmentation,

Reference 21

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:25:55.748059Z digest=sha256:0d3f4bf23af911298351adc7ae36275c0853afa5b15041f1cf4f22df446fc752

Observation 19a273cd-5b76-4108-b334-b8b59e3628bb · outbound

This paper cites Segment anything,.

Generalizable Articulated Object Perception with Superpoints Segment anything,

Reference 22

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source=pdf_text observed=2026-08-11T10:25:55.752977Z digest=sha256:938049dc0e1a08cc6b56a940d0250e1f72cac4d89a121ab6c0eb8279fa86c668

Observation 3de6bdb0-34ed-4450-babb-7452379b7f3a · outbound

This paper cites Point transformer v2: Grouped vector attention and partition-based pooling,.

Generalizable Articulated Object Perception with Superpoints Point transformer v2: Grouped vector attention and partition-based pooling,

Reference 23

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source=pdf_text observed=2026-08-11T10:25:55.758148Z digest=sha256:963d28141c82c42167e2ee29d9585194cea73be88dfd439c92cc52f752fbe978

Observation f898d32b-3266-433a-a553-da07e880ad68 · outbound

This paper cites Weakly supervised segmentation-aided classification of urban scenes from 3d lidar point clouds,.

Generalizable Articulated Object Perception with Superpoints Weakly supervised segmentation-aided classification of urban scenes from 3d lidar point clouds,

Reference 24

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.763037Z digest=sha256:31197d4105facf79c95d06f79527f3ee4a28bb8a75341b7976cc89aad85669e2

Observation 7c924bca-d5d1-4782-88d5-589f99623e02 · outbound

This paper cites Superpoint transformer for 3d scene instance segmentation,.

Generalizable Articulated Object Perception with Superpoints Superpoint transformer for 3d scene instance segmentation,

Reference 25

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.767779Z digest=sha256:6acc41cd8989522b56dd6d22f9185245da9b51deba5a2d95cf2b7c1210f54494

Observation f2d1bfe4-29b9-41d2-979c-9e888355e6a1 · outbound

This paper cites Query refinement transformer for 3d instance segmentation,.

Generalizable Articulated Object Perception with Superpoints Query refinement transformer for 3d instance segmentation,

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.772820Z digest=sha256:844ff12a5166bd58cf39ee22be27a2287901524fa678d367fa9e375d27b8ad1a

Observation fe9a7f41-611d-4cb6-9127-05874d4d8c76 · outbound

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

Generalizable Articulated Object Perception with Superpoints Sapien: A simulated part-based interactive environment,

Reference 27

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raw_fallback, observed 2026-08-11T10:25:55.990044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.778145Z digest=sha256:edf4ddf3e80d69d8111677bfd10d1d87d4a225dfe601188244646c0b87dc9b4f

Observation e1d445ee-ce5d-4e02-8fe4-20863dbdae2a · outbound

This paper cites Scannet: Richly-annotated 3d reconstructions of indoor scenes,.

Generalizable Articulated Object Perception with Superpoints Scannet: Richly-annotated 3d reconstructions of indoor scenes,

Reference 28

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no resolver link, observed 2026-08-11T10:25:55.783061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:25:55.783061Z digest=sha256:3086fe7cde80d3f43c7ddd5b1c3de45fca79a972aa3dbecafe6bf65966302c6e

Observation e884f546-d067-4ff5-9273-31df8982b1cf · outbound

This paper cites Pointgroup: Dual- set point grouping for 3d instance segmentation,.

Generalizable Articulated Object Perception with Superpoints Pointgroup: Dual- set point grouping for 3d instance segmentation,

Reference 29

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raw_fallback, observed 2026-08-11T10:25:55.961761Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.788513Z digest=sha256:a945398de11ebff3d6935c87df1c0a66f38be2d3b943df54f0611d45dd4fc514

Observation 32e7c740-eeea-4f2c-815a-93d4975f033b · outbound

This paper cites Softgroup for 3d instance segmentation on point clouds,.

Generalizable Articulated Object Perception with Superpoints Softgroup for 3d instance segmentation on point clouds,

Reference 30

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raw_fallback, observed 2026-08-11T10:25:55.945247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.793362Z digest=sha256:9c313961f4173bcd76ab7540ed78f736623c54c44a6e1436b0024825c88103ca

Observation 67a7c034-2b9c-4f81-b0c3-68e2b81ba0bf · outbound

This paper cites Autogpart: Intermediate supervision search for generalizable 3d part segmentation,.

Generalizable Articulated Object Perception with Superpoints Autogpart: Intermediate supervision search for generalizable 3d part segmentation,

Reference 31

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raw_fallback, observed 2026-08-11T10:25:55.928002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T10:25:55.798347Z digest=sha256:99e741b8fd3bccaa6438d35fd7d238cb42685026c5b883e39bd19f8a2b337c77

Pith citing papers

No inbound Pith citation observations are available.