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Paper Citation Record · LEDGER

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning

As of 8 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2509.11594.

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

pith.paper-citation-record.v1
2509.11594 v3

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T16:50:22.299097Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

19 of 19 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation da117fb0-193f-4ef4-a30a-2c07f20d84d9 · outbound

This paper cites OK-Robot: What Really Matters in Integrating Open-Knowledge Models for Robotics.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning OK-Robot: What Really Matters in Integrating Open-Knowledge Models for Robotics

Reference 1

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source=pdf_text observed=2026-08-04T16:50:21.204425Z digest=sha256:f988d86f6acbc202bd915fa69cfbd26becc149370f31a67753eb6901d589b974

Observation 93bad157-a46f-411d-af9c-13f2513b9d8a · outbound

This paper cites Goat: Go to any thing — a universal navigation agent for open-vocabulary, multimodal goals,.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Goat: Go to any thing — a universal navigation agent for open-vocabulary, multimodal goals,

Reference 2

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source=pdf_text observed=2026-08-04T16:50:21.236696Z digest=sha256:1cdea8e68084309d42349cbcc56ce8ae02e0cf16e5007c02d758a150210a5441

Observation 9c79020c-de68-4c5c-bb85-dd26636123c6 · outbound

This paper cites A Survey of Robotic Language Grounding: Tradeoffs between Symbols and Embeddings.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning A Survey of Robotic Language Grounding: Tradeoffs between Symbols and Embeddings

Reference 3

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source=pdf_text observed=2026-08-04T16:50:21.298801Z digest=sha256:7c724875526be1885177736d170177ac077c934f40cffcd4935e00613aaa38ad

Observation 5eb8c7ce-22ac-4ad3-934d-9463dd4768ef · outbound

This paper cites Planning Robot Placement for Object Grasping.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Planning Robot Placement for Object Grasping

Reference 4

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source=pdf_text observed=2026-08-04T16:50:21.349840Z digest=sha256:577d95692f53455ba6007fc6cebcdc98ac0a8917bb73405e91df69e71d0728df

Observation 688028df-8dd1-49dc-b1ec-4bf9dcc4cd46 · outbound

This paper cites Integrated task and motion planning,.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Integrated task and motion planning,

Reference 5

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source=pdf_text observed=2026-08-04T16:50:21.407622Z digest=sha256:5fb7503a2ef20f5ef6aa19d520da1f52c19a852d0160d39a75cb1d8b433bcf40

Observation 4500b3d8-4455-4989-973f-c166ff5c5a3d · outbound

This paper cites Task and motion planning using mixed integer linear programming for solving fetch-and-carry tasks by a mobile manipulator,.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Task and motion planning using mixed integer linear programming for solving fetch-and-carry tasks by a mobile manipulator,

Reference 6

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source=pdf_text observed=2026-08-04T16:50:21.452274Z digest=sha256:d16d54fe6f8c6de3c9fd9e520a753a80254e80e1f72b2ea6e4d6908346633275

Observation 294ef3f2-b38b-4483-8fb9-12ba53228d77 · outbound

This paper cites Object-centric task and motion planning in dynamic environments,.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Object-centric task and motion planning in dynamic environments,

Reference 7

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source=pdf_text observed=2026-08-04T16:50:21.512778Z digest=sha256:319f6969ae8ca24266b07fc7af4a6337d9540891320ab6c822245c0f666f3754

Observation 1c4bb214-269a-4df4-9cc8-2aa6a017cd62 · outbound

This paper cites Reuleaux: Robot Base Placement by Reachability Analysis.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Reuleaux: Robot Base Placement by Reachability Analysis

Reference 8

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source=pdf_text observed=2026-08-04T16:50:21.538121Z digest=sha256:3e38bad145bbc6e2d92a29c9b87dddb4b77cbaa435ccdd77835f2bebbaabb329

Observation ce85a925-9ef0-4635-9642-2192786e5e60 · outbound

This paper cites A task and motion planning framework for partially observable household manipulation scenes,.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning A task and motion planning framework for partially observable household manipulation scenes,

Reference 9

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source=pdf_text observed=2026-08-04T16:50:21.583697Z digest=sha256:fe82c1be90c37c8823b50ad8e39153863593c1589dc291785b5c276a4ebadbba

Observation eddfc2d9-9031-42fe-ad79-a1b77458c073 · outbound

This paper cites Receding horizon “next-best-view.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Receding horizon “next-best-view

Reference 10

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source=pdf_text observed=2026-08-04T16:50:21.640959Z digest=sha256:2d15431bce979091403a83d86e8cc5940b902226086c5250dc40ec58fbfec88e

Observation 458c2a01-434d-4b27-b801-68ce1bc1d47b · outbound

This paper cites Pointnet++ grasping: Learning an end-to-end spatial grasp generation algorithm from sparse point clouds,.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Pointnet++ grasping: Learning an end-to-end spatial grasp generation algorithm from sparse point clouds,

Reference 11

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source=pdf_text observed=2026-08-04T16:50:21.722580Z digest=sha256:883ed70c21c826fa8b066de0752d4669b20304c947f35c901793cd291bc34c52

Observation b098273c-4b09-41d6-8d2a-ce6e64587883 · outbound

This paper cites Physics-based self-supervised grasp pose detection,.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Physics-based self-supervised grasp pose detection,

Reference 12

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source=pdf_text observed=2026-08-04T16:50:21.776978Z digest=sha256:4bbdc8d751190b0a360e93a700045756847dab3d24f62ebb7b2d29370dd970a5

Observation c05834c7-9044-4a4c-b62a-6b743b713e2f · outbound

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

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning PointNet++: Deep hierarchical feature learning on point sets in a metric space,

Reference 13

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source=pdf_text observed=2026-08-04T16:50:21.855583Z digest=sha256:017a2a26f3ab7088d3a3b0af5f899342264d5ffd153336abac044bebfd0c7632

Observation ad2f6ff7-bf98-43cc-a511-2487d25310e2 · outbound

This paper cites Point transformer,.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Point transformer,

Reference 14

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source=pdf_text observed=2026-08-04T16:50:21.912264Z digest=sha256:d8f65d1500f28f54e67de736f503b514084c639c2f534ef50d9670d7a6aa8eb5

Observation 1f31b9ae-4dfa-4989-8be3-8cda2473cae2 · outbound

This paper cites ProcTHOR: Large-Scale Embodied AI Using Procedural Generation.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning ProcTHOR: Large-Scale Embodied AI Using Procedural Generation

Reference 15

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source=pdf_text observed=2026-08-04T16:50:21.981970Z digest=sha256:8682c5a2d94a8912f32a15ccb9de43ec17f193fe888a0249c4787cedc0fc0cf6

Observation 939470e1-3dee-4f0a-8087-827dd7c5589b · outbound

This paper cites The YCB object and model set: Towards common benchmarks for manipulation research,.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning The YCB object and model set: Towards common benchmarks for manipulation research,

Reference 16

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source=pdf_text observed=2026-08-04T16:50:22.055935Z digest=sha256:920ffe91ca83f6f13bb5dda2ab30e7e0b9b52f115788ae6c414cb0c80fbfaa3c

Observation 0bc72bdf-dbeb-4b7f-a8d0-e209b91c789b · outbound

This paper cites Maniskill: Generalizable manipulation skill benchmark with large-scale demonstrations,.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Maniskill: Generalizable manipulation skill benchmark with large-scale demonstrations,

Reference 17

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Observation 2b9810a1-93dd-4a05-9bb7-d9c532c310de · outbound

This paper cites Detecting twenty-thousand classes using image-level supervision,.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Detecting twenty-thousand classes using image-level supervision,

Reference 18

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Observation 80dbb77c-0a2c-45c7-a291-e6e67de11a48 · outbound

This paper cites Stretch ai — an open-source toolkit for embodied intelligence on the stretch 3 mobile manipulator,.

GBPP: Grasp-Aware Base Placement Prediction for Robots via Two-Stage Learning Stretch ai — an open-source toolkit for embodied intelligence on the stretch 3 mobile manipulator,

Reference 19

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source=pdf_text observed=2026-08-04T16:50:22.299097Z digest=sha256:40fb5241e8469e9a7bb0022c8634735dd13fa17cb995989503ead978cf167fd1

Pith citing papers

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