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Paper Citation Record · LEDGER

Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2407.15815.

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

pith.paper-citation-record.v1
2407.15815 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:18:25.935849Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:19:42.969889Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e26ed806-c873-40f5-b2ec-e33036ff3f3a · inbound

FunGrasp: Functional Grasping for Diverse Dexterous Hands cites this paper.

FunGrasp: Functional Grasping for Diverse Dexterous Hands Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 16

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unresolved
no resolver link, observed 2026-08-12T14:01:46.766565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:01:46.766565Z digest=sha256:1dadacbc53b2acc09e68cff1a9d33fd3adb1668423c812e9a52c5229f7f2005e

Observation e425115c-9b20-484f-b73e-69965c97da97 · inbound

Diffusion-VLA: Generalizable and Interpretable Robot Foundation Model via Self-Generated Reasoning cites this paper.

Diffusion-VLA: Generalizable and Interpretable Robot Foundation Model via Self-Generated Reasoning Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 62

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unresolved
no resolver link, observed 2026-08-11T22:38:33.305761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:38:33.305761Z digest=sha256:c8dfbf243f2a56da1b7eb67786c4972bdb65468068ab49891f6f737e3d552235

Observation 807a81e8-a895-4c32-ae7b-74a84e5ab0a8 · inbound

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo cites this paper.

DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 77

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no resolver link, observed 2026-08-11T20:57:12.521885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:57:12.521885Z digest=sha256:8d10f10bc5e6f48ad405a3b17be032808383f903f331751088805e920f5eb107

Observation a4f59524-45c5-47fa-aaba-0f5a101f07b1 · inbound

Wheeled Lab: Modern Sim2Real for Low-cost, Open-source Wheeled Robotics cites this paper.

Wheeled Lab: Modern Sim2Real for Low-cost, Open-source Wheeled Robotics Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 38

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unresolved
no resolver link, observed 2026-08-08T13:00:39.187433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:00:39.187433Z digest=sha256:b9713026a5aed5510488f4223e8c5fe5138fc74cc6483311841b5ad37521b176

Observation ac7961d7-f576-4719-bf5f-4b87edb85ed2 · inbound

Novel Demonstration Generation with Gaussian Splatting Enables Robust One-Shot Manipulation cites this paper.

Novel Demonstration Generation with Gaussian Splatting Enables Robust One-Shot Manipulation Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-16T12:18:25.935849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:18:25.935849Z digest=sha256:f07b82aac99d0a0a162154e5327d78791903cff9391c3447cb6f046db24fe310

Observation 65bf7690-6596-44bd-8681-3bd7e2cb2384 · inbound

Merging and Disentangling Views in Visual Reinforcement Learning for Robotic Manipulation cites this paper.

Merging and Disentangling Views in Visual Reinforcement Learning for Robotic Manipulation Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T23:29:32.078898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:29:32.078898Z digest=sha256:971ff25058636218716cf9327b1db4f7749f1407b62668d3536c132025b3b423

Observation 2f254162-3a68-4e61-9d13-f02813d20fe3 · inbound

H$^3$DP: Triply-Hierarchical Diffusion Policy for Visuomotor Learning cites this paper.

H$^3$DP: Triply-Hierarchical Diffusion Policy for Visuomotor Learning Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 5

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unresolved
no resolver link, observed 2026-08-15T22:12:22.886471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:12:22.886471Z digest=sha256:dc7fc4130b23c642fcdd37a85b3781266f697685018ed3e706fa12b773e19ae9

Observation 5fb88f38-08dc-41bf-a731-8ecdce4377e2 · inbound

RoboPearls: Editable Video Simulation for Robot Manipulation cites this paper.

RoboPearls: Editable Video Simulation for Robot Manipulation Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 88

Resolution
unresolved
no resolver link, observed 2026-08-06T22:04:34.686270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:04:34.686270Z digest=sha256:36bdf5a13a8ab5377f6ee2b505d28f48202c9922456903d9192f5083579d9476

Observation 7e08bd72-de2f-48df-b64a-94b96a15a174 · inbound

DeGuV: Depth-Guided Visual Reinforcement Learning for Generalization and Interpretability in Manipulation cites this paper.

DeGuV: Depth-Guided Visual Reinforcement Learning for Generalization and Interpretability in Manipulation Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-05T05:47:31.510415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T05:47:31.510415Z digest=sha256:c43fe52ca917b28763ab2d5b0f4407485c971996793625c9e6cbf57c6e0148b1

Observation af4cad6e-cb31-41c1-bd65-1c506c350e7c · inbound

SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning cites this paper.

SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-15T08:02:11.434219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-15T08:02:11.189795Z digest=sha256:bb06da99d020f5757ba7ebcd4d0da0aa9e785aa7df50987cc0bc0a848ef79358

Observation 9b9c7080-d926-47d3-913e-f52d6051a52f · inbound

One Hand to Rule Them All: Canonical Representations for Unified Dexterous Manipulation cites this paper.

One Hand to Rule Them All: Canonical Representations for Unified Dexterous Manipulation Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-21T12:30:07.553096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-21T12:29:09.497661Z digest=sha256:4ffdeb9062e9f59425092421146d26ddb4cbf69c9e93b3c030930f0e48a8fc6c

Observation 4f1c7726-e860-4e3f-b64e-f548c7943598 · 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 Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 14

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verified exact
arxiv_id, observed 2026-05-10T10:19:20.200096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-10T10:17:26.903231Z digest=sha256:def058e4181af2db73820f2f81a159acf56724763900a5af411db77db5ae4fc1

Observation b1be1fe7-1c3f-40b0-9138-748b8fb43046 · inbound

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

3D Generation for Embodied AI and Robotic Simulation: A Survey Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 172

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:01:25.431015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-07T13:16:44.508344Z digest=sha256:e0bed6209de2ea815f7ef8727ac0eafe63f70f2bb6be83ab08a76734034f9aa9

Observation 6f77de62-09fd-4640-9af4-f709e67b63b0 · inbound

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

3D Generation for Embodied AI and Robotic Simulation: A Survey Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 172

Resolution
verified exact
arxiv_id, observed 2026-05-11T22:06:13.023187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-08T03:31:05.311070Z digest=sha256:9a8eb38795c82002a90456f14f0345358a1eebb5e15287d9c9fac41d493c1deb

Observation f53ec3fe-5641-462d-a7a3-51fe08ad38f1 · inbound

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

3D Generation for Embodied AI and Robotic Simulation: A Survey Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 172

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:05:59.046809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-05-11T01:56:24.510913Z digest=sha256:2a0aef096bad123560894e29ce09a7b8cb1099ca7d3086e47c72750bca084673

Observation 8cab7d7d-a445-40da-8c25-710cd62bd6c2 · inbound

Scalable Multi-Task Data Generation via Reinforcement Learning for Language-Conditioned Bimanual Dexterous Manipulation cites this paper.

Scalable Multi-Task Data Generation via Reinforcement Learning for Language-Conditioned Bimanual Dexterous Manipulation Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-07-04T09:19:42.971686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-26T10:18:01.230648Z digest=sha256:cc89c1afe828c63e554849172033243cd1e055d86d891a49428dc9583f271968

Observation 37a7f439-aa69-4a6a-be3e-2587b4f14265 · inbound

Scalable Multi-Task Data Generation via Reinforcement Learning for Language-Conditioned Bimanual Dexterous Manipulation cites this paper.

Scalable Multi-Task Data Generation via Reinforcement Learning for Language-Conditioned Bimanual Dexterous Manipulation Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-06-30T10:54:36.914892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-30T10:46:26.385071Z digest=sha256:dec512c139427cc316c8c7b9f26571d867060d3fd49ec391465d356381535b42

Observation ce9bad05-4d09-4e77-8520-05ba9bc6ce06 · inbound

HALO-WA: Hybrid-Attention Latent-Guided Online Reinforcement Learning for World-Action Models cites this paper.

HALO-WA: Hybrid-Attention Latent-Guided Online Reinforcement Learning for World-Action Models Learning to Manipulate Anywhere: A Visual Generalizable Framework For Reinforcement Learning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-07-11T20:32:22.412216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T20:32:22.412216Z digest=sha256:be97c336905c16dc1d36193bdb28f171695200727b71ee840c375332e214cf15