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Paper Citation Record · LEDGER

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network

As of 18 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2605.28362.

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

pith.paper-citation-record.v1
2605.28362 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T11:26:25.795231Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

35 of 35 outbound references displayed

  • verified exact4
  • verified fuzzy0
  • unresolved31
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External citation measurements

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Outbound references

Observation 1a03d372-6969-407d-baf8-eddad1c769a9 · outbound

This paper cites an unresolved cited work.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Unresolved cited work

Reference 1

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Observation a9612f1d-e610-46a7-824b-c5f08a418f03 · outbound

This paper cites Sampling-based robot motion planning: A review,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Sampling-based robot motion planning: A review,

Reference 2

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Observation ef4d9d50-b9d0-48cb-9e32-11a2c5902b72 · outbound

This paper cites A formal basis for the heuristic determination of minimum cost paths,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network A formal basis for the heuristic determination of minimum cost paths,

Reference 3

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Observation 6c6a482f-b1c0-4f7b-b64e-a6796e58e87d · outbound

This paper cites A note on two problems in connexion with graphs,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network A note on two problems in connexion with graphs,

Reference 4

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Observation 5fa63c30-2c8c-4557-b78a-a66ad402b2cb · outbound

This paper cites Rapidly-exploring random trees : a new tool for path planning,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Rapidly-exploring random trees : a new tool for path planning,

Reference 5

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Observation caa28997-dfdc-467e-ab15-d870124d6723 · outbound

This paper cites Prob- abilistic roadmaps for path planning in high-dimensional configuration spaces,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Prob- abilistic roadmaps for path planning in high-dimensional configuration spaces,

Reference 6

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Observation 1b4a7850-693c-490b-8374-c396d1fbd20c · outbound

This paper cites Chomp: Gradient optimization techniques for efficient motion planning,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Chomp: Gradient optimization techniques for efficient motion planning,

Reference 7

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Observation 4abd7e3c-8fb2-47cc-b669-88dd8325bb30 · outbound

This paper cites Model predictive control: Theory and practice—a survey,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Model predictive control: Theory and practice—a survey,

Reference 8

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Observation 72d7d777-e4e6-41ff-af63-46fbe5522905 · outbound

This paper cites Neural rrt*: Learning-based optimal path planning,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Neural rrt*: Learning-based optimal path planning,

Reference 9

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Observation c83b6103-321e-4e9d-b5d9-e3e3422fbaf8 · outbound

This paper cites Path planning using neural a* search,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Path planning using neural a* search,

Reference 10

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Observation e6bb4238-0f01-4f02-b881-ce1202ee9ba8 · outbound

This paper cites Motion planning networks,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Motion planning networks,

Reference 11

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Observation 58842994-a6bf-4947-9db6-2d5c3d358501 · outbound

This paper cites A survey on deep learning for robot navigation,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network A survey on deep learning for robot navigation,

Reference 12

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Observation d247682b-63e0-4dbb-bf49-ae7b8e87d718 · outbound

This paper cites Motion planning transformers: One model to plan them all,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Motion planning transformers: One model to plan them all,

Reference 13

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Observation 42c66bc9-c092-4b77-b55d-5a9e1dcf4f03 · outbound

This paper cites Attention is all you need,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Attention is all you need,

Reference 14

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Observation 3d48eef4-86a7-4147-982e-c760b26659df · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network U-net: Convolutional networks for biomedical image segmentation,

Reference 15

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Observation e94ea90e-469b-4444-96f5-4a33a51e3bdf · outbound

This paper cites Vision transformer with deformable attention,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Vision transformer with deformable attention,

Reference 16

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Observation 0000b47e-4b04-43b6-8fab-bb6dcefed811 · outbound

This paper cites Learning deconvolution network for semantic segmentation,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Learning deconvolution network for semantic segmentation,

Reference 17

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Observation 0456802f-d931-414e-b6cc-99398d7ea98d · outbound

This paper cites Sensor based motion planning: the hierarchical generalized voronoi graph,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Sensor based motion planning: the hierarchical generalized voronoi graph,

Reference 18

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Observation e8d2d402-7212-4035-80ad-e9917961b8bb · outbound

This paper cites Computational topology: An introduc- tion,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Computational topology: An introduc- tion,

Reference 19

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Observation 18450ded-b375-4957-83e3-6b23083f2275 · outbound

This paper cites Dynamic snake convo- lution based on topological geometric constraints for tubular structure segmentation,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Dynamic snake convo- lution based on topological geometric constraints for tubular structure segmentation,

Reference 20

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Observation 4bbc7eba-3643-432a-be27-3371e83806f6 · outbound

This paper cites Topology-Preserving Deep Image Segmentation.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Topology-Preserving Deep Image Segmentation

Reference 21

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Source-reported events for the cited work

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Observation 52e304f8-da1a-4e46-9c66-46db4bbdece4 · outbound

This paper cites Sampling-based algorithms for optimal motion planning,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Sampling-based algorithms for optimal motion planning,

Reference 22

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Observation 9d2a9365-fb68-4138-846b-e6491917388f · outbound

This paper cites Informed RRT*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Informed RRT*: Optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic,

Reference 23

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Observation 33df4820-a046-4dcf-ad16-3db70fa24d62 · outbound

This paper cites Learning sampling distributions for robot motion planning,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Learning sampling distributions for robot motion planning,

Reference 24

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Observation 9b1dcb80-2763-4aa1-83cb-ef7803630b68 · outbound

This paper cites Fully convolutional networks for semantic segmentation,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Fully convolutional networks for semantic segmentation,

Reference 25

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Observation 799e4c34-c863-465e-b699-b0287da380c8 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 26

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Observation 7d682857-a6de-4d8c-b3b9-974030ae6580 · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted win- dows,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Swin transformer: Hierarchical vision transformer using shifted win- dows,

Reference 27

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Observation fbd51785-1d5e-4018-b6b6-4d73b2cd31d9 · outbound

This paper cites Segformer: Simple and efficient design for semantic segmentation with transformers,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Segformer: Simple and efficient design for semantic segmentation with transformers,

Reference 28

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Observation b11c3cb1-dabc-4ef6-ad8f-ba1647d11eb5 · outbound

This paper cites The perceptron: a probabilistic model for information storage and organization in the brain.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network The perceptron: a probabilistic model for information storage and organization in the brain

Reference 29

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Observation fb02cf69-a5c6-475f-b1a5-fba617f49749 · outbound

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Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network V-net: Fully convolutional neural networks for volumetric medical image segmentation,

Reference 30

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Observation 53aa38c9-441f-4779-ae81-70452d761dc2 · outbound

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Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Deep GrabCut for Object Selection

Reference 31

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Observation f42c80b5-17a1-49cd-a8de-3b5ec64d4877 · outbound

This paper cites Beyond the pixel-wise loss for topology-aware delineation,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Beyond the pixel-wise loss for topology-aware delineation,

Reference 32

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Observation c0db74b4-1dc5-409c-a02d-b995599b79bc · outbound

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Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Goodfellow, Y

Reference 33

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Observation b82aef9b-6ffc-455a-8d8e-2799898aff28 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Adam: A Method for Stochastic Optimization

Reference 34

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Observation 40c6c5d8-202f-470b-a60e-92d275f36686 · outbound

This paper cites Decoupled weight decay regularization,.

Accelerating Robot Path Planning via Connectivity-Preserving Region Proposal Network Decoupled weight decay regularization,

Reference 35

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