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Paper Citation Record · LEDGER

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation

As of 22 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2607.27890.

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

pith.paper-citation-record.v1
2607.27890 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T23:37:17.647823Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

48 of 48 outbound references displayed

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  • verified fuzzy0
  • unresolved48
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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Outbound references

Observation ee81798b-c616-4a15-af15-26bf41462f04 · outbound

This paper cites Diffusion Policy: Visuomotor Policy Learning via Action Diffusion.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Diffusion Policy: Visuomotor Policy Learning via Action Diffusion

Reference 1

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source=pdf_text observed=2026-07-31T23:37:12.676063Z digest=sha256:dcfb2bc3f74fd63ee2dcf70e3cd53fe75ccb6e90bede8550f80aff713a7d9735

Observation 15a4a797-612e-4874-8abd-f9038cf9a825 · outbound

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

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

Reference 2

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source=pdf_text observed=2026-07-31T23:37:12.747739Z digest=sha256:dd39d2d93ff1f3f21b440e4501e15b4caf326e81c8ea3bd6da030c18f137b245

Observation 4cbbbcb5-03f9-4613-9f43-9638dc26a565 · outbound

This paper cites Reuss, M.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Reuss, M

Reference 3

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source=pdf_text observed=2026-07-31T23:37:12.862686Z digest=sha256:4ea92b9de4905e327bb7f740599ee1f0c6892364cd0e2cdd7f1a582336e11e4a

Observation 8906ae90-6107-46cf-ac7a-f6c85136296f · outbound

This paper cites Open X-Embodiment: Robotic Learning Datasets and RT-X Models.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Reference 4

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source=pdf_text observed=2026-07-31T23:37:12.930396Z digest=sha256:cdee33ac8c527f5f8fa40110a4aab0d075c4a1a1c748b24c59be2152f288ac74

Observation d6cd04dd-6978-427b-adfd-57bfa537a446 · outbound

This paper cites DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Reference 5

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source=pdf_text observed=2026-07-31T23:37:13.006281Z digest=sha256:e7858e132d36472680835e13d1caa1757eb44718eec1e46e85acdc4831fec317

Observation c299257e-8b05-439c-aa29-24596d05abe5 · outbound

This paper cites an unresolved cited work.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Unresolved cited work

Reference 6

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source=pdf_text observed=2026-07-31T23:37:13.101454Z digest=sha256:83abec043cbc3ed0289d3b1366b143bc15142fa3b198b34cfc6eab0f4cce1179

Observation c6b64cb8-c151-4540-8e75-765ebdb61729 · outbound

This paper cites Black, M.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Black, M

Reference 7

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source=pdf_text observed=2026-07-31T23:37:13.195729Z digest=sha256:e36469448f299397101b15a221f98d86191693ba2b0e052ffcb9b9c096c99a29

Observation 2f41f931-bf29-47a2-8534-001fb2cd87ad · outbound

This paper cites SAIL: Faster-than-Demonstration Execution of Imitation Learning Policies.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation SAIL: Faster-than-Demonstration Execution of Imitation Learning Policies

Reference 8

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source=pdf_text observed=2026-07-31T23:37:13.431035Z digest=sha256:686c227cfabf03fa8bf179e9dbe082fcc95f1908ea8a038f0aacb7e31117d741

Observation 1d259815-920b-47ad-b744-56fe4e5110d2 · outbound

This paper cites Catch It! Learning to Catch in Flight with Mobile Dexterous Hands.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Catch It! Learning to Catch in Flight with Mobile Dexterous Hands

Reference 9

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source=pdf_text observed=2026-07-31T23:37:13.576605Z digest=sha256:dbf1a49ddf8506eecf4619a43061062bd7d6c0b34f97063700592b737c273bd2

Observation 32237d5f-e7e5-4614-a96e-87a2d0b7887c · outbound

This paper cites Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulation.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Reactive Diffusion Policy: Slow-Fast Visual-Tactile Policy Learning for Contact-Rich Manipulation

Reference 10

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source=pdf_text observed=2026-07-31T23:37:13.701774Z digest=sha256:709f1bcd35aa201eef25f0f61eaf74d7cbf3e829c6c6868015bc71e8c0b78382

Observation f3d1dcf3-ee06-40c8-895a-fc55a0ab1d4d · outbound

This paper cites RoCoDA: Counterfactual Data Augmentation for Data-Efficient Robot Learning from Demonstrations.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation RoCoDA: Counterfactual Data Augmentation for Data-Efficient Robot Learning from Demonstrations

Reference 11

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source=pdf_text observed=2026-07-31T23:37:13.820037Z digest=sha256:173d880d42f345977b611987af009f77a62f6668cbaae21338d97e40699793fe

Observation 8f095153-6af5-4340-84f8-803f7596adec · outbound

This paper cites CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models

Reference 12

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source=pdf_text observed=2026-07-31T23:37:13.972703Z digest=sha256:c80f0cbf0f9454cfb795906ebc161d97150b3e95bee15d178e69248b580c54f6

Observation 558ac2b9-87ec-43d1-a1d9-08a0408634b8 · outbound

This paper cites Equivariant Diffusion Policy.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Equivariant Diffusion Policy

Reference 13

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source=pdf_text observed=2026-07-31T23:37:14.065390Z digest=sha256:2eef7da7874c194f21e8e7ef486add5e0edff7724cd3b3dd2a2457d5b5e71321

Observation b87022e1-e9b5-40ae-9ab1-1d00af1709b6 · outbound

This paper cites SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space

Reference 14

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source=pdf_text observed=2026-07-31T23:37:14.217485Z digest=sha256:98e5f48347739bb3fbafa334af0b31ed89fb3820a7bf208b838b91878dd443fa

Observation c0d72154-d1f7-40d9-b2e8-1b4406efb5a5 · outbound

This paper cites What Matters in Learning from Large-Scale Datasets for Robot Manipulation.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation What Matters in Learning from Large-Scale Datasets for Robot Manipulation

Reference 15

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source=pdf_text observed=2026-07-31T23:37:14.373825Z digest=sha256:a408d0e5bf4b9f7dd1957704f724be1db4f340ced6cd6deb3d4b5aa208f9cfd9

Observation e395991d-6ad4-4344-b0fe-688ff80e2fd7 · outbound

This paper cites ImMimic: Cross-Domain Imitation from Human Videos via Mapping and Interpolation.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation ImMimic: Cross-Domain Imitation from Human Videos via Mapping and Interpolation

Reference 16

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source=pdf_text observed=2026-07-31T23:37:14.482989Z digest=sha256:c59b1784e989f3ef65e3c6bf89ba9c9768c7cb939c475b37e893caca4534928c

Observation cb5805fa-41a5-4dc8-a6ff-65fe7c0c7743 · outbound

This paper cites an unresolved cited work.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Unresolved cited work

Reference 17

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source=pdf_text observed=2026-07-31T23:37:14.624506Z digest=sha256:9b87c67271e976af15abdacc95853e272aa87874bb1a59f1af672b6f21115168

Observation e9f658da-969a-4710-93ca-0d839bf85eee · outbound

This paper cites Video2Sim2Real: Full-Stack Autonomous Dexterous Skill Acquisition from a Single Human Video.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Video2Sim2Real: Full-Stack Autonomous Dexterous Skill Acquisition from a Single Human Video

Reference 18

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source=pdf_text observed=2026-07-31T23:37:14.845419Z digest=sha256:c02e9eea21fbb09eaf39cd3a2799c7f8b38d56bce20d790dce178378a1bbefab

Observation 81ebb962-f3cf-453e-bafb-733a638a618b · outbound

This paper cites A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning

Reference 19

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source=pdf_text observed=2026-07-31T23:37:14.917770Z digest=sha256:aea667314a7278184894e06164521024845cc4bcb49890e8af183107da6843cf

Observation b08faf32-06f7-458b-a454-a45e23dd3918 · outbound

This paper cites DART: Noise Injection for Robust Imitation Learning.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation DART: Noise Injection for Robust Imitation Learning

Reference 20

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source=pdf_text observed=2026-07-31T23:37:15.046142Z digest=sha256:75381c8339b79dff85ae873de042bc61e5b2490437ecfec12eb9ab3aa09a38ab

Observation 1cd57af5-ec8f-43cc-b64b-bb867d080369 · outbound

This paper cites Latent Policy Barrier: Learning Robust Visuomotor Policies by Staying In-Distribution.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Latent Policy Barrier: Learning Robust Visuomotor Policies by Staying In-Distribution

Reference 21

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source=pdf_text observed=2026-07-31T23:37:15.104289Z digest=sha256:400c34bf4c96ee6dffd0cb7ae96f93c84f714ae423e1be5312d0fe43e1235538

Observation d468edee-7a7d-4fef-9f73-ad3b8c55b300 · outbound

This paper cites Simulation Distillation: Pretraining World Models in Simulation for Rapid Real-World Adaptation.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Simulation Distillation: Pretraining World Models in Simulation for Rapid Real-World Adaptation

Reference 22

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source=pdf_text observed=2026-07-31T23:37:15.232279Z digest=sha256:853e6922d8cccc3e2d2881470005eafebb1005aff6630b7f485906a8975cd0ff

Observation 388c4cc2-bb8b-4bbc-85dd-aba231663f5f · outbound

This paper cites Du and S.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Du and S

Reference 23

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source=pdf_text observed=2026-07-31T23:37:15.356744Z digest=sha256:56e1605541d1ab489a70fa809be44b7cf30ad009d683d1b3e55153e2ca472247

Observation ab7a56c8-7ab9-4d27-b10d-85c95be8506c · outbound

This paper cites Towards Generalizable Robotic Manipulation in Dynamic Environments.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Towards Generalizable Robotic Manipulation in Dynamic Environments

Reference 24

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source=pdf_text observed=2026-07-31T23:37:15.484836Z digest=sha256:ce100260a545d2661c57da9e190a640d6002abdec346e6c63266e6fec0aecb75

Observation 9def2791-e519-4edd-adef-683a8940a9f3 · outbound

This paper cites FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objects

Reference 25

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Observation ffd14d39-1c90-427c-99f1-9f3f08514f00 · outbound

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Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Unresolved cited work

Reference 26

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source=pdf_text observed=2026-07-31T23:37:15.430813Z digest=sha256:cb2d9973a989507873602b93fe1124d6cc195c5d892d073049337efb64ffd54e

Observation 56a08347-985d-4f31-b6d6-696dd0534c6f · outbound

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Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Unresolved cited work

Reference 27

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source=pdf_text observed=2026-07-31T23:37:15.853889Z digest=sha256:88f1f24e973269a5f4a03f039d29986cb9003a3b3ef7054601e8cbcfca3b1742

Observation 5f43597b-d403-414f-bc5a-f7ba02e62829 · outbound

This paper cites Mandlekar, S.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Mandlekar, S

Reference 28

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source=pdf_text observed=2026-07-31T23:37:15.970443Z digest=sha256:4ad2c038e17bff8922dc1acc6571b94eeb3943f9ce8068b58b622dd648684fec

Observation 5b867bf3-48bb-4a83-9bbb-436dae28f93b · outbound

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Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Unresolved cited work

Reference 29

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source=pdf_text observed=2026-07-31T23:37:15.698331Z digest=sha256:93da89f7e82938970e9b65ca24654948816dda6e76893cdcd2272ef10b6fb6b6

Observation 5f75700d-dc4b-43bf-949c-a79ba09ca76f · outbound

This paper cites SkillMimicGen: Automated Demonstration Generation for Efficient Skill Learning and Deployment.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation SkillMimicGen: Automated Demonstration Generation for Efficient Skill Learning and Deployment

Reference 30

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source=pdf_text observed=2026-07-31T23:37:16.324988Z digest=sha256:a0e600ee31d8f2130893fc47a94625a59174f7b817595a1931b4cfeb4e90e208

Observation e2004f3a-b61a-468d-92c3-d236b6b1506f · outbound

This paper cites an unresolved cited work.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Unresolved cited work

Reference 31

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source=pdf_text observed=2026-07-31T23:37:16.453439Z digest=sha256:118a93abe2850aed6535a425124aca110a366a3491331eda2ca8451686390239

Observation 4ef8960e-e28b-481c-9ef0-588a43c3739a · outbound

This paper cites ET-SEED: Efficient Trajectory-Level SE(3) Equivariant Diffusion Policy.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation ET-SEED: Efficient Trajectory-Level SE(3) Equivariant Diffusion Policy

Reference 32

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source=pdf_text observed=2026-07-31T23:37:16.521345Z digest=sha256:fe44f89138381fb88d881cb2f565aa8fd01655dc8aa3aaefac937937d7a4e65d

Observation b799e91b-8215-41cd-841b-2661fe3a4673 · outbound

This paper cites DemoGen: Synthetic Demonstration Generation for Data-Efficient Visuomotor Policy Learning.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation DemoGen: Synthetic Demonstration Generation for Data-Efficient Visuomotor Policy Learning

Reference 33

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source=pdf_text observed=2026-07-31T23:37:16.146377Z digest=sha256:80c17d0867ae33f43a7b6d064cbfd155759a9e076190a6a5666562dfd7b67139

Observation 96587ae4-e455-4788-a03f-1e77e69b6445 · outbound

This paper cites Model Predictive Path Integral Control using Covariance Variable Importance Sampling.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Model Predictive Path Integral Control using Covariance Variable Importance Sampling

Reference 34

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source=pdf_text observed=2026-07-31T23:37:16.753914Z digest=sha256:5361054dcd50f66e70f2accf1a691bb2d411f40cee0f4a47b1948454a1fcbb9b

Observation dca4367f-1dff-42c0-94b4-3d12d6bdc1ea · outbound

This paper cites DINOv3.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation DINOv3

Reference 35

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source=pdf_text observed=2026-07-31T23:37:16.867942Z digest=sha256:a79ebea5755635a7acc98aadce3de8f00420446cba2fa83df601cca12cbab911

Observation 3209899b-99e7-493a-805e-a7bfb265be54 · outbound

This paper cites Deep Residual Learning for Image Recognition.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Deep Residual Learning for Image Recognition

Reference 36

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source=pdf_text observed=2026-07-31T23:37:17.008657Z digest=sha256:06c57f69193dd4e4be7b5f55e9dca12548def61e089db519a86c2df73f877d1c

Observation 2ec58904-75a7-4f00-ad3d-2d88783209da · outbound

This paper cites EquiBot: SIM(3)-Equivariant Diffusion Policy for Generalizable and Data Efficient Learning.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation EquiBot: SIM(3)-Equivariant Diffusion Policy for Generalizable and Data Efficient Learning

Reference 37

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source=pdf_text observed=2026-07-31T23:37:16.627904Z digest=sha256:3ffe21bedaa3d5c200701e426d8d21314613711a4d440eacf925d18708553f9b

Observation 50f1626b-69c1-4052-8a8e-4f689751af97 · outbound

This paper cites an unresolved cited work.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Unresolved cited work

Reference 38

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source=pdf_text observed=2026-07-31T23:37:17.138569Z digest=sha256:2fe7e7c111dc6de6b8288a46893f6fac0941dfed3c6436af84bbab654c68d154

Observation fd0e5887-2e20-47b6-944f-f88a72d37bbd · outbound

This paper cites robosuite: A Modular Simulation Framework and Benchmark for Robot Learning.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation robosuite: A Modular Simulation Framework and Benchmark for Robot Learning

Reference 39

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no resolver link, observed 2026-07-31T23:37:17.247138Z

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source=pdf_text observed=2026-07-31T23:37:17.247138Z digest=sha256:cddf09ae04cc8fa4fd013649418b7e9a8c9c6c4e640993a432e41e5d5d717693

Observation 78c28863-5588-4ba3-923a-f3371f89ce2f · outbound

This paper cites What Matters in Learning from Offline Human Demonstrations for Robot Manipulation.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation What Matters in Learning from Offline Human Demonstrations for Robot Manipulation

Reference 40

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no resolver link, observed 2026-07-31T23:37:17.304965Z

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source=pdf_text observed=2026-07-31T23:37:17.304965Z digest=sha256:753aebb316313924e7a21eda851ad8951916a59aa0471208cdef96c7c12b538b

Observation 1d77fe73-50e8-47f2-9f7c-b56f24cfa80a · outbound

This paper cites Weiler and G.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Weiler and G

Reference 41

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no resolver link, observed 2026-07-31T23:37:17.071063Z

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source=pdf_text observed=2026-07-31T23:37:17.071063Z digest=sha256:09776b09c9bec6e367f449ca56d86bfd412be4949f76bc16a86097632abf6399

Observation f771e864-d1b9-40ce-9d46-b0696e3c8a78 · outbound

This paper cites an unresolved cited work.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Unresolved cited work

Reference 42

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no resolver link, observed 2026-07-31T23:37:17.460102Z

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source=pdf_text observed=2026-07-31T23:37:17.460102Z digest=sha256:3b3996850dbec7b94233606675b1a23ebe58f129ebb6599e0796f3a807e28c2d

Observation 163c2027-ccc2-47f4-9dce-28c84704d911 · outbound

This paper cites On the analysis of movement smoothness.Journal of NeuroEngineering and Rehabilitation, 12(1):112, 2015.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation On the analysis of movement smoothness.Journal of NeuroEngineering and Rehabilitation, 12(1):112, 2015

Reference 43

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no resolver link, observed 2026-07-31T23:37:17.515995Z

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source=pdf_text observed=2026-07-31T23:37:17.515995Z digest=sha256:a42ba72d3c007aa12f55eec2127f866a7ec2a41bc18715f32d2eaa0fb65decab

Observation c825f2c9-0e85-4561-9f65-030c9c7bc27e · outbound

This paper cites Balasubramanian, A.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Balasubramanian, A

Reference 44

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no resolver link, observed 2026-07-31T23:37:17.647823Z

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source=pdf_text observed=2026-07-31T23:37:17.647823Z digest=sha256:4c0d7812ccca73b4f4adb1df0dcf90a61fd5e29fe672ecce60d954eb8a526716

Observation d477c0d5-df14-40e3-8bc7-73b0c8cb4a83 · outbound

This paper cites Todorov, T.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Todorov, T

Reference 45

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no resolver link, observed 2026-07-31T23:37:17.411473Z

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source=pdf_text observed=2026-07-31T23:37:17.411473Z digest=sha256:096ca4917312e461ef81029e46cce18d83ee25d9a627cc4d78197bbf6425fa32

Observation b8f76e6f-2b17-476a-be5f-4d8469edbb89 · outbound

This paper cites MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations

Reference 2023

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no resolver link, observed 2026-07-31T23:37:16.076795Z

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source=pdf_text observed=2026-07-31T23:37:16.076795Z digest=sha256:4efb1048b4e1448b405b2722188d1089f1b29817f53ca77c3d49c55cfd6b8f19

Observation 597b5b9a-502e-4dd9-88d5-1e93af795c1a · outbound

This paper cites Real-Time Execution of Action Chunking Flow Policies.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation Real-Time Execution of Action Chunking Flow Policies

Reference 2025

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no resolver link, observed 2026-07-31T23:37:13.319123Z

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source=pdf_text observed=2026-07-31T23:37:13.319123Z digest=sha256:2b376c53109fd479dd0b9158ca28333aa85a464c2bde01c0e4b9a20d3ee152d9

Observation 585d1705-64bd-412a-86ee-2a83cc8b4989 · outbound

This paper cites EgoEngine: From Egocentric Human Videos to High-Fidelity Dexterous Robot Demonstrations.

Static In, Dynamic Out: Counterfactual Action Augmentation for Moving Object Manipulation EgoEngine: From Egocentric Human Videos to High-Fidelity Dexterous Robot Demonstrations

Reference 2026

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no resolver link, observed 2026-07-31T23:37:14.747862Z

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source=pdf_text observed=2026-07-31T23:37:14.747862Z digest=sha256:6910b33a77412a27b6f23297ec3efe470c4a1eb1b56ff6a891a61fb0c967b5d5

Pith citing papers

No inbound Pith citation observations are available.