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Paper Citation Record · LEDGER

GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 31 inbound Pith citation observations for arXiv:2302.06671.

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

pith.paper-citation-record.v1
2302.06671 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 31 of 31 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T22:55:57.677962Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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  • malformed identifier0
  • metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation dab5ad20-b10f-4769-917b-c71d0fe54d75 · inbound

Scaling Robot Learning with Semantically Imagined Experience cites this paper.

Scaling Robot Learning with Semantically Imagined Experience GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 55

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verified exact
arxiv_id, observed 2026-05-17T18:59:10.487020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T18:59:10.352342Z digest=sha256:56035a4e9e077b92cdfa3fcf71929098df6870568a7af37a578f3e5a09b7e3fd

Observation 3dbe3ab5-33df-4e30-9828-896774bb6177 · inbound

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution cites this paper.

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 77

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metadata mismatch
arxiv_id, observed 2026-05-16T08:12:31.395071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-16T08:12:30.984870Z digest=sha256:be4dbf1c2992ab692b5ea82ec465bc1e6e094e981146a827a1b457741345e083

Observation 8590713e-edf7-4745-82f4-ef75f9b2f9fb · inbound

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

Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 11

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verified exact
arxiv_id, observed 2026-05-16T05:54:59.107183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-16T05:54:58.940428Z digest=sha256:b5bc08c8db305d050f37dc086f67bacbfc6f9310a222dba0aa07ff0afe0e3a99

Observation b6f4a743-dfad-44ef-82ff-7dc7d32172ce · inbound

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

MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-17T09:47:55.258825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T09:47:54.977716Z digest=sha256:71645805cf0c52bace6c8eb9284f240ccd42af32908f88ef5628b5fce97cbb5e

Observation 1ad39efe-35c4-4d15-b0cd-a72505058b70 · inbound

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models cites this paper.

Sora: A Review on Background, Technology, Limitations, and Opportunities of Large Vision Models GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 169

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verified exact
arxiv_id, observed 2026-05-13T13:43:11.238613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-13T13:43:11.024069Z digest=sha256:f40415f079293c8130cb609514861a228e3fa671eaa4f530903ad8c1eedcc4ad

Observation cb6c9d56-1ecf-4234-a1a5-cccd9cd9d6f3 · inbound

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

Octo: An Open-Source Generalist Robot Policy GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-11T00:26:15.552931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T00:26:15.163358Z digest=sha256:a96863a3b305019520bbdbfac378a1eb4b6a424350c6ff930684f9e6a0debf7a

Observation 2eface9f-0b69-46e6-aab5-ff9407666e0b · inbound

Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation cites this paper.

Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-15T12:17:01.412942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T12:17:01.294466Z digest=sha256:98c544157edc5ecda8175e78bd50dae3779b79d0abf1de92086d7abb597b0aa4

Observation ddc1bdf7-0c2c-4b5f-8edf-e08b2fc7b07d · inbound

Learning Real-World Action-Video Dynamics with Heterogeneous Masked Autoregression cites this paper.

Learning Real-World Action-Video Dynamics with Heterogeneous Masked Autoregression GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 10

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unresolved
no resolver link, observed 2026-08-08T22:55:57.677962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T22:55:57.677962Z digest=sha256:e28da75d4ba52b3e237ec989b0d7c2d3354380fcd45f95dc3bbb612b0ac4c848

Observation fa3cdd50-5425-46ed-913c-254a187df79e · inbound

Predictive Red Teaming: Breaking Policies Without Breaking Robots cites this paper.

Predictive Red Teaming: Breaking Policies Without Breaking Robots GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 53

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unresolved
no resolver link, observed 2026-08-08T15:04:10.921801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:04:10.921801Z digest=sha256:873731bbf1601a373a6f4aa6aa12a2767e711dff6086774765e0eafe13286e8e

Observation 7ac627bd-1b99-428a-b28c-d6e433763e05 · inbound

Video2Policy: Scaling up Manipulation Tasks in Simulation through Internet Videos cites this paper.

Video2Policy: Scaling up Manipulation Tasks in Simulation through Internet Videos GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 318

Resolution
unresolved
no resolver link, observed 2026-08-07T20:14:52.801645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:14:52.801645Z digest=sha256:0dea5ab01bb5f22512883725fd1fe41430673d6659a6f409b509629eae2e3676

Observation 6f6ea8e4-0bf0-4d77-894f-9c439d7750d1 · inbound

GR00T N1: An Open Foundation Model for Generalist Humanoid Robots cites this paper.

GR00T N1: An Open Foundation Model for Generalist Humanoid Robots GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-10T19:09:10.198675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T19:09:10.112304Z digest=sha256:19d5191973bf66e3a08c3fdba4a09cfbadccae3cd7acdfa82ff8623494cbae74

Observation 72a630fc-ebfd-47a0-b652-905b23cc4ad1 · inbound

GraspVLA: a Grasping Foundation Model Pre-trained on Billion-scale Synthetic Action Data cites this paper.

GraspVLA: a Grasping Foundation Model Pre-trained on Billion-scale Synthetic Action Data GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 46

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verified exact
arxiv_id, observed 2026-05-17T20:55:52.222706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T20:55:52.109166Z digest=sha256:a85bc8dd55a23f9f9040c9b1c4a3a2fbc81b6b871847d1de1dde0a4c991bf1b3

Observation 50974783-7f03-45de-86c6-1e662ef20871 · inbound

DreamGen: Unlocking Generalization in Robot Learning through Video World Models cites this paper.

DreamGen: Unlocking Generalization in Robot Learning through Video World Models GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-15T23:50:45.492833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-15T23:50:45.332466Z digest=sha256:177d6e9937d72d1bc5a862f4870df19a1b9f7a7a9ae9cb5f7f3ff8bbf2762b6a

Observation ad5f9cc3-f896-4435-b659-b4da11317449 · inbound

RwoR: Generating Robot Demonstrations from Human Hand Collection for Policy Learning without Robot cites this paper.

RwoR: Generating Robot Demonstrations from Human Hand Collection for Policy Learning without Robot GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 62

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unresolved
no resolver link, observed 2026-08-06T20:04:38.252110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:04:38.252110Z digest=sha256:942deb6056442e716cd8c7bb1235951080e85ef7ec8f96d76d917c98a1a72eb9

Observation 01f98653-d881-486f-acbb-574458c8d389 · inbound

VLM-TDP: VLM-guided Trajectory-conditioned Diffusion Policy for Robust Long-Horizon Manipulation cites this paper.

VLM-TDP: VLM-guided Trajectory-conditioned Diffusion Policy for Robust Long-Horizon Manipulation GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T19:51:08.485238Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:51:08.485238Z digest=sha256:f4554cce946659d6563b3e6b5ecde61cf8065dc4419c4691c3cdcc4ee1a41018

Observation 7fe0b49a-3265-49fe-a6aa-54abf355c307 · inbound

ERMV: Editing 4D Robotic Multi-view images to enhance embodied agents cites this paper.

ERMV: Editing 4D Robotic Multi-view images to enhance embodied agents GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T14:53:34.194140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:53:34.194140Z digest=sha256:18a6fc0c9423fd99ad5bc74bcbb6011e5d754aef51acb47116628196d33d7195

Observation 05e02b74-570a-4c96-a8d8-7fab115d319c · inbound

DockAnywhere: Data-Efficient Visuomotor Policy Learning for Mobile Manipulation via Novel Demonstration Generation cites this paper.

DockAnywhere: Data-Efficient Visuomotor Policy Learning for Mobile Manipulation via Novel Demonstration Generation GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 24

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verified exact
arxiv_id, observed 2026-05-10T10:19:20.208412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T10:17:26.903231Z digest=sha256:fa24e0dcefdd4dd67ed5d863a1171fdb27fe6f29a73ab07f14b4e56d8b5eb132

Observation e7b9427a-bca5-4cfa-b7e9-60af368e5a20 · inbound

${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities cites this paper.

${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 74

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verified exact
arxiv_id, observed 2026-05-10T11:45:21.612020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T11:42:34.409651Z digest=sha256:4541bf81c8d3c5ef1b0a1ba140f15267df83b193cb9b23540305a20d3cc69286

Observation bdcf4cd0-d7d1-44d9-919e-f469766054d8 · inbound

3D Generation for Embodied AI and Robotic Simulation: A Survey cites this paper.

3D Generation for Embodied AI and Robotic Simulation: A Survey GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 194

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verified exact
arxiv_id, observed 2026-05-12T09:01:25.654932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-07T13:16:44.508344Z digest=sha256:7fef9292385130e6a86f6b735d043b176b354eccd4b40b39f95d89d2aea0c0c6

Observation d8c72122-37f8-4073-96dd-c7f1802425d2 · inbound

3D Generation for Embodied AI and Robotic Simulation: A Survey cites this paper.

3D Generation for Embodied AI and Robotic Simulation: A Survey GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 194

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verified exact
arxiv_id, observed 2026-05-11T22:06:12.977447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-08T03:31:05.311070Z digest=sha256:c791fe5aa3941f2aa13cc5e7e630b6708c81fc05610d6f369dc7c9bb577a1ad6

Observation 833b9ee8-4a5a-4f8e-9817-def2b93c5770 · inbound

3D Generation for Embodied AI and Robotic Simulation: A Survey cites this paper.

3D Generation for Embodied AI and Robotic Simulation: A Survey GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 193

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verified exact
arxiv_id, observed 2026-05-11T04:05:58.919240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:56:24.510913Z digest=sha256:1311c45db2c95b062424a95249103135a4ae0559ff6c13c86169254cf19d545a

Observation 4be697e3-7f06-48d9-9800-9b2d5a447a2e · inbound

Lucid-XR: An Extended-Reality Data Engine for Robotic Manipulation cites this paper.

Lucid-XR: An Extended-Reality Data Engine for Robotic Manipulation GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:31:08.582410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-09T19:48:57.065807Z digest=sha256:d1f01200411813592ca55fb987329ec71da582d8d98c8d7835903967724d2d2c

Observation a62c5998-7190-4a31-a568-6d886337c996 · inbound

BioProVLA-Agent: An Affordable, Protocol-Driven, Vision-Enhanced VLA-Enabled Embodied Multi-Agent System with Closed-Loop-Capable Reasoning for Biological Laboratory Manipulation cites this paper.

BioProVLA-Agent: An Affordable, Protocol-Driven, Vision-Enhanced VLA-Enabled Embodied Multi-Agent System with Closed-Loop-Capable Reasoning for Biological Laboratory Manipulation GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 34

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verified exact
arxiv_id, observed 2026-05-11T04:20:59.215912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-11T01:28:14.142842Z digest=sha256:75638d55dcf399622f90fd0c024353c4d858d0741a4d6a5e161c175688eba488

Observation 6f69803e-1aa0-4c5d-b467-f4ba18f04a50 · inbound

BioProVLA-Agent: An Affordable, Protocol-Driven, Vision-Enhanced VLA-Enabled Embodied Multi-Agent System with Closed-Loop-Capable Reasoning for Biological Laboratory Manipulation cites this paper.

BioProVLA-Agent: An Affordable, Protocol-Driven, Vision-Enhanced VLA-Enabled Embodied Multi-Agent System with Closed-Loop-Capable Reasoning for Biological Laboratory Manipulation GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 34

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verified exact
arxiv_id, observed 2026-06-30T23:35:07.909232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T23:26:01.191863Z digest=sha256:d5ac53c2e885d4a97298ce59ee0d202f7a75ca7a95cb9f278cc4df0e2d172513

Observation 415ce2a2-c593-415c-84e0-89a3c9e7a220 · inbound

SID: Sliding into Distribution for Robust Few-Demonstration Manipulation cites this paper.

SID: Sliding into Distribution for Robust Few-Demonstration Manipulation GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-14T19:17:50.439335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-14T19:15:45.167147Z digest=sha256:f5812ef8b2d3ffada4c2811a9e6cc58afa83aae2eb8be262613fff0ac246ae93

Observation 6c50e6ea-a029-483f-ba43-187507c8f36c · inbound

What Makes Synthetic Data Effective in Image Segmentation cites this paper.

What Makes Synthetic Data Effective in Image Segmentation GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 5

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verified exact
arxiv_id, observed 2026-05-20T07:13:06.661878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-20T07:08:16.047730Z digest=sha256:5d3ebdf0f6fcdb9dbdbaf5231b5a6bb0ea81f359a8ffbb4a05833c9711329f98

Observation 92bd6c64-527a-4198-9240-7fa4fe945610 · inbound

SKIP: Sparse Keyframe Interpolation Paradigm for Efficient Embodied World Models cites this paper.

SKIP: Sparse Keyframe Interpolation Paradigm for Efficient Embodied World Models GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 27

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verified exact
arxiv_id, observed 2026-06-28T20:22:37.778297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T18:44:39.497333Z digest=sha256:1767567d81dc40cbd5427d6de116e2f705e6c1646051970ece4216358ae31d5d

Observation 761d5f89-ba82-4f1e-b4f0-a323773a175d · inbound

Pose6DAug: Physically Plausible Multi-view Object Swapping for Robot Data Augmentation cites this paper.

Pose6DAug: Physically Plausible Multi-view Object Swapping for Robot Data Augmentation GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-04T03:59:33.627526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T17:23:49.431731Z digest=sha256:c270caead9614aebdd08485c1b988946242ad6586eadc338086e33e6887c0fdc

Observation 4b2fb3f8-e1b0-4377-83b6-18ed28b780da · inbound

Affordance-Based Manipulation Planning with Text Goals and Sim-to-Real Generalisation via Real-to-Sim Image Conversion cites this paper.

Affordance-Based Manipulation Planning with Text Goals and Sim-to-Real Generalisation via Real-to-Sim Image Conversion GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 23

Resolution
unresolved
no resolver link, observed 2026-07-14T07:44:10.532385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T07:44:10.532385Z digest=sha256:d5ff9add805b0914850dc24487851c894754e209c3b369f27ce6efeb4ff6e7bd

Observation ee5c71a6-093d-4119-bcb7-9d4fc125164a · inbound

DynamicManip: Enabling Dynamic Manipulation from a Single Static Demonstration cites this paper.

DynamicManip: Enabling Dynamic Manipulation from a Single Static Demonstration GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 15

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unresolved
no resolver link, observed 2026-08-06T00:14:28.611286Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:14:28.611286Z digest=sha256:d81bdbbb5a94c7aa9e275943dc6c5d7258daa3cc969cf1dc3d41b9736213905b

Observation e23e6fe7-4178-41f8-a25d-1be942f955a9 · inbound

Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills cites this paper.

Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 34

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unresolved
no resolver link, observed 2026-08-04T19:45:28.290804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:45:28.290804Z digest=sha256:65541fa1937ca0d5c8996e0ba30715dd2b240fa1d5c7125f2dc972805ed2e7cf