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Paper Citation Record · LEDGER

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation

As of 6 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2602.11885.

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

pith.paper-citation-record.v1
2602.11885 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T01:21:34.705330Z

measured 36 of 36 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 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

36 of 36 outbound references displayed

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External citation measurements

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Outbound references

Observation 2eb55380-b541-4c03-8723-b33afa57b1ef · outbound

This paper cites Scaling Laws for Neural Language Models.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Scaling Laws for Neural Language Models

Reference 1

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source=pdf_text observed=2026-08-03T01:21:31.078145Z digest=sha256:2c12cc37e624e21600e3bfacbb9cc1673339721ee20341d9ddd690b6f821c4c8

Observation 57c97eeb-8467-47a2-88bb-e94e2da21a57 · outbound

This paper cites GPT-4 Technical Report.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation GPT-4 Technical Report

Reference 2

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source=pdf_text observed=2026-08-03T01:21:31.225906Z digest=sha256:c986ce7c16d4e84fe0d3fdd90e3a3eb9b267b96aa4d476a7481afcff6375f489

Observation a8a48ca5-ee79-4a3f-8b1e-25658afcc246 · outbound

This paper cites MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models

Reference 3

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Observation 839d6921-97a8-414b-bf1f-951ce054d1c7 · outbound

This paper cites Diff-control: A stateful diffusion-based policy for imitation learning,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Diff-control: A stateful diffusion-based policy for imitation learning,

Reference 5

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source=pdf_text observed=2026-08-03T01:21:31.492453Z digest=sha256:82fc729caebfba8e624f68494e8ebca3b08f1eae07126b8f491196160ce1668d

Observation d796dc3b-cdf8-40c3-8c45-cb03df6ee154 · outbound

This paper cites Octo: An Open-Source Generalist Robot Policy.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Octo: An Open-Source Generalist Robot Policy

Reference 6

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source=pdf_text observed=2026-08-03T01:21:31.560478Z digest=sha256:5f9bfa7958f0a6908a4936aa43ccc8cadcdf02d6ed1d55ddd223d5c186265739

Observation 0b778e61-5a4b-4e47-bc78-b0cedde5a78c · outbound

This paper cites RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation

Reference 7

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source=pdf_text observed=2026-08-03T01:21:31.642653Z digest=sha256:7839b5592ef2ae34e12dfe9928ca78a83a708a61c9263d1d6b9ec69200e4e801

Observation e8d1fa06-58f8-444a-8e05-ff3d6eb0ebaf · outbound

This paper cites Visual instruction tuning,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Visual instruction tuning,

Reference 8

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source=pdf_text observed=2026-08-03T01:21:31.692953Z digest=sha256:520d39f16f22c2cde8daa610b7dc8dbe2a2bd4419bfa0bd87eeb88154ad188d7

Observation 5b1a1761-0820-419a-a0d8-3c8860374be6 · outbound

This paper cites Openvla: An open-source vision-language-action model,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Openvla: An open-source vision-language-action model,

Reference 9

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source=pdf_text observed=2026-08-03T01:21:31.786282Z digest=sha256:b15730e540ee483e5ec8186f8c6b952dc3f5903614aae6b971de841cdc12b373

Observation 236d76d5-29ca-4d45-bd88-d90c9b90f424 · outbound

This paper cites Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success

Reference 10

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source=pdf_text observed=2026-08-03T01:21:31.841773Z digest=sha256:9ca1d185bf382e7ce3eebf3217699aa549e88b5a426e128daba694e7a60de455

Observation 4603c4c1-bc1c-4a54-ae48-c84a8ea3e876 · outbound

This paper cites ChatVLA: Unified Multimodal Understanding and Robot Control with Vision-Language-Action Model.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation ChatVLA: Unified Multimodal Understanding and Robot Control with Vision-Language-Action Model

Reference 11

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source=pdf_text observed=2026-08-03T01:21:31.938466Z digest=sha256:b56b173977edf507db667d174d5b9d06946055a3759a69d536e40a044a4a8d49

Observation 9c339eea-9074-4cff-92bd-a4abda4eff6c · outbound

This paper cites Rt-trajectory: Robotic task generalization via hindsight trajectory sketches,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Rt-trajectory: Robotic task generalization via hindsight trajectory sketches,

Reference 12

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source=pdf_text observed=2026-08-03T01:21:31.992902Z digest=sha256:0e0a0c39207772904a9b59f8d540b398a5d2eb83ebfa90d230076a60bf282e08

Observation bd40bf86-5a7f-453c-9fb8-e5fc1b75b503 · outbound

This paper cites Hamster: Hierarchical action models for open-world robot manipulation,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Hamster: Hierarchical action models for open-world robot manipulation,

Reference 13

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source=pdf_text observed=2026-08-03T01:21:32.046774Z digest=sha256:253f33fc7797254f58c155d8a7ab5d19650f0fca32e869628fd209cadb671a14

Observation 09979dfc-6cca-43ce-b6f7-c8fac30aeb3c · outbound

This paper cites Kite: Keypoint- conditioned policies for semantic manipulation,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Kite: Keypoint- conditioned policies for semantic manipulation,

Reference 14

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source=pdf_text observed=2026-08-03T01:21:32.078604Z digest=sha256:44b3165bf7f7f8a7749d61db2bf33e5a9635fff55bf1c777fc820fdeb06954b5

Observation e277a38b-cbf1-404a-b439-3acd829cb4cb · outbound

This paper cites VIP: Vision Instructed Pre-training for Robotic Manipulation.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation VIP: Vision Instructed Pre-training for Robotic Manipulation

Reference 15

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source=pdf_text observed=2026-08-03T01:21:32.163968Z digest=sha256:6327ef3f2bf16eed7b31712541292b36734a21d15a84dd1d2050768aa7cac05b

Observation bc5396ec-be68-467c-9a99-493b0295f0ce · outbound

This paper cites Yolov8: A novel object detection algorithm with enhanced performance and robustness,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Yolov8: A novel object detection algorithm with enhanced performance and robustness,

Reference 16

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source=pdf_text observed=2026-08-03T01:21:32.217528Z digest=sha256:1d1ade5e3396e3d50add2a3418540844724565603c74c04814d7ba7be4aa12fc

Observation 96e945fe-4a2d-488a-a4a4-e0de86c89d27 · outbound

This paper cites Roboturk: A crowdsourcing platform for robotic skill learning through imitation,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Roboturk: A crowdsourcing platform for robotic skill learning through imitation,

Reference 17

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source=pdf_text observed=2026-08-03T01:21:32.308730Z digest=sha256:e0b93662d27b68a7bc915443741f3609902ee9e2d2eef0feca1981175508c73c

Observation 8135c0a0-e149-4829-adc1-4945aa018995 · outbound

This paper cites Open-TeleVision: Teleoperation with Immersive Active Visual Feedback.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Open-TeleVision: Teleoperation with Immersive Active Visual Feedback

Reference 18

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source=pdf_text observed=2026-08-03T01:21:32.379663Z digest=sha256:d2812a9def46ed285fc436da16743df7b04c8020f9bb3cb05c4fd0689ed925d5

Observation 60d5fd2f-b682-4dfd-8959-368d0705f38e · outbound

This paper cites Deep imitation learning for complex manipulation tasks from virtual reality teleoperation,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Deep imitation learning for complex manipulation tasks from virtual reality teleoperation,

Reference 19

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source=pdf_text observed=2026-08-03T01:21:32.450646Z digest=sha256:107e11e6cea6ca438c97bcbdafda0cc3b70a7525691c85a4f398ede08890a7fd

Observation 108c2342-b8d1-4b58-af3b-bfa64ab5637f · outbound

This paper cites Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

Reference 20

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source=pdf_text observed=2026-08-03T01:21:32.563719Z digest=sha256:e6121e5c66a801d34cb1582169a952fe5f7cde8c6cf5736071888fcac7de9d02

Observation 33bbbd69-12f4-4dbf-9b0e-6e34b5d10280 · outbound

This paper cites Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots

Reference 21

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source=pdf_text observed=2026-08-03T01:21:32.690751Z digest=sha256:88a3a6abd4371d26a0c529c0b1c4d1feec35ac29ed8383e3d0b6602bd5b41110

Observation 5650ef9e-6dc4-4df7-b7bf-8b33c758f0cb · outbound

This paper cites UMI on Legs: Making Manipulation Policies Mobile with Manipulation-Centric Whole-body Controllers.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation UMI on Legs: Making Manipulation Policies Mobile with Manipulation-Centric Whole-body Controllers

Reference 22

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source=pdf_text observed=2026-08-03T01:21:32.769942Z digest=sha256:93df8dee686457853a9cf1bcec91dd50b82dbd1477c227d0e58c907ea5ef588f

Observation 73d80f47-85ef-4f83-841f-a7d730e5a243 · outbound

This paper cites Diffusion policy: Visuomotor policy learning via ac- tion diffusion,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Diffusion policy: Visuomotor policy learning via ac- tion diffusion,

Reference 23

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source=pdf_text observed=2026-08-03T01:21:32.850332Z digest=sha256:48c8d23b71af65620319e734658020e3fce2e4d71efe0546999b3d86890794e7

Observation a5b77748-2cb2-4a35-a5e7-b62921b78012 · outbound

This paper cites Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models

Reference 24

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source=pdf_text observed=2026-08-03T01:21:32.916883Z digest=sha256:4d3e6b14ad186f6f76c6e2f336928e9b26747264e4f19ab12d0d87790ed2a34f

Observation 49b8c02b-0181-4063-94bc-37e06fabc945 · outbound

This paper cites Vision-based robotic grasping from object localization, object pose estimation to grasp estimation for parallel grippers: a review,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Vision-based robotic grasping from object localization, object pose estimation to grasp estimation for parallel grippers: a review,

Reference 25

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source=pdf_text observed=2026-08-03T01:21:33.057165Z digest=sha256:c39b79e713839d80e6442fda2c671bdd67aa8f186b5bfae29f4ad59a815df246

Observation 94fe9e6d-afd9-4dc2-8986-8c474eaa2e50 · outbound

This paper cites An intelligent emulsion explosive grasping and filling system based on yolo-simam-grcnn,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation An intelligent emulsion explosive grasping and filling system based on yolo-simam-grcnn,

Reference 26

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source=pdf_text observed=2026-08-03T01:21:33.168096Z digest=sha256:36851f553833f7aae2377a125dc89f5c19cc427e70b64b23d0fbf636c471213c

Observation aa3d85a3-7492-424e-96d6-3eb4d8156351 · outbound

This paper cites Earl: Eye-on-hand reinforcement learner for dynamic grasping with active pose estimation,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Earl: Eye-on-hand reinforcement learner for dynamic grasping with active pose estimation,

Reference 27

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source=pdf_text observed=2026-08-03T01:21:33.357757Z digest=sha256:0dacca1cd8cb6b328deb76e89623ea04511468a17661c167d424db1d709a49d0

Observation 2d927fba-05be-44c7-bfef-109c0e2d0b9f · outbound

This paper cites Manibox: Enhancing spatial grasping generalization via scalable simulation data generation,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Manibox: Enhancing spatial grasping generalization via scalable simulation data generation,

Reference 28

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source=pdf_text observed=2026-08-03T01:21:33.548413Z digest=sha256:d895f93d912defb2bbf6d5b1159001bc4ab40f306d6b777a7c44b45cfc0921ca

Observation 328979b3-b491-453b-a5d7-208de0b56442 · outbound

This paper cites Flow as the Cross-Domain Manipulation Interface.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Flow as the Cross-Domain Manipulation Interface

Reference 29

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source=pdf_text observed=2026-08-03T01:21:33.652860Z digest=sha256:162353f4e4c8bef3b27f36e379b4d24a4129df74989aceac6c185301bb9de358

Observation 6b6c5df0-fb04-48c6-ba4d-f15016b8cc0d · outbound

This paper cites Robotic control via embodied chain-of-thought reasoning,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Robotic control via embodied chain-of-thought reasoning,

Reference 30

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source=pdf_text observed=2026-08-03T01:21:33.737272Z digest=sha256:b46ea1e2c2f6f1816b7e3f1861983531539736332274214788b094393bc24c47

Observation 07ad8fd9-13c1-495d-af4d-17354c43e14f · outbound

This paper cites Energy-based models are zero-shot planners for compositional scene rearrangement,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Energy-based models are zero-shot planners for compositional scene rearrangement,

Reference 31

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source=pdf_text observed=2026-08-03T01:21:33.856986Z digest=sha256:77c3dd3a187eb6bd80d4050d18164ac31bfcddd78d587a603e00061fe5b3b1d4

Observation 0cb56221-06ba-46eb-b504-2dd00ad680e0 · outbound

This paper cites A single multi-task deep neural network with post-processing for object detection with reasoning and robotic grasp detection,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation A single multi-task deep neural network with post-processing for object detection with reasoning and robotic grasp detection,

Reference 32

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source=pdf_text observed=2026-08-03T01:21:33.990136Z digest=sha256:fe928e37271d30a0fdd26950190e13fef0d821736caabe5ae368c6ed5f0c1651

Observation 2090f779-2cff-4a34-9917-5e3dc6ecf9c7 · outbound

This paper cites A multi- task convolutional neural network for autonomous robotic grasping in object stacking scenes,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation A multi- task convolutional neural network for autonomous robotic grasping in object stacking scenes,

Reference 33

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source=pdf_text observed=2026-08-03T01:21:34.111370Z digest=sha256:509662f288c4f5e8a4b487d020a558ad92cd357f387a191f1c890685cf7c4aa0

Observation e59c743e-08fc-42e1-a923-24f3708ff3a8 · outbound

This paper cites Denoising Diffusion Implicit Models.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Denoising Diffusion Implicit Models

Reference 34

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source=pdf_text observed=2026-08-03T01:21:34.293762Z digest=sha256:7675930addab511bb1c967e279624855a7290b1aa6cae85cae1cc5bb50b7bcb0

Observation f38dbeb8-9442-44a5-9741-2742831d3e65 · outbound

This paper cites Data Scaling Laws in Imitation Learning for Robotic Manipulation.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Data Scaling Laws in Imitation Learning for Robotic Manipulation

Reference 35

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source=pdf_text observed=2026-08-03T01:21:34.414129Z digest=sha256:7d3350f4c3638abb9616eef75b74adcaa8457aaeaa461901a4741621ba254d26

Observation e86dfb24-180e-4c39-9ed4-75fcde268ef4 · outbound

This paper cites Learning transferable visual models from natural language supervision,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Learning transferable visual models from natural language supervision,

Reference 36

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This paper cites Open-world object manipulation using pre-trained vision-language models,.

Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation Open-world object manipulation using pre-trained vision-language models,

Reference 37

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