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Paper Citation Record · LEDGER

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment

As of 9 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 0 inbound Pith citation observations for arXiv:2608.05674.

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

pith.paper-citation-record.v1
2608.05674 v1

Coverage vector

measured 80 of 80 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T04:20:18.114193Z

measured 80 of 80 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

80 of 80 outbound references displayed

  • verified exact2
  • verified fuzzy26
  • unresolved52
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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Outbound references

Observation c6d40d33-a36c-48ab-bfdf-20ed7a5b93fa · outbound

This paper cites SemDeDup: Data-efficient learning at web-scale through semantic deduplication.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment SemDeDup: Data-efficient learning at web-scale through semantic deduplication

Reference 1

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source=pdf_text observed=2026-08-08T04:20:17.259542Z digest=sha256:6121028bd4091c20852aa5555888ad9dc995daa1c97a959fc7673d55fb7a8428

Observation ffb24185-2136-4dfd-90b5-17f10d2c9957 · outbound

This paper cites AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems

Reference 2

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source=pdf_text observed=2026-08-08T04:20:17.265573Z digest=sha256:e3ba417c90b59d615ef9fa8b6d1a8025dbb91ed774385ca0cc5232f53aaaeb5f

Observation 721ae9f4-4df6-461b-bbbb-6b0262e2bf3c · outbound

This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 3

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source=pdf_text observed=2026-08-08T04:20:17.292790Z digest=sha256:0e69368274746c83a8c32283cc0ebbbdaffd91a32be9f4005980d6b4ea1b89f3

Observation 8a46947c-82bf-44e0-bfea-ad0cb5565f05 · outbound

This paper cites Motus: A Unified Latent Action World Model.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Motus: A Unified Latent Action World Model

Reference 4

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source=pdf_text observed=2026-08-08T04:20:17.319779Z digest=sha256:bf256ad776e65078a36897273a452857e2b40bd7061e80d21af9fadcfe1a8ec0

Observation 13f8b882-044e-4d1b-bfff-6d8f5828e5b0 · outbound

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

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

Reference 5

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source=pdf_text observed=2026-08-08T04:20:17.347473Z digest=sha256:8484e68036560b212fb0d6aab843635eec87ce89df354b769573eadde6d0670c

Observation 8ae98c6b-2744-47e9-b1ee-28f53e4b4286 · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 6

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source=pdf_text observed=2026-08-08T04:20:17.376394Z digest=sha256:cdc5092b9e4a9e757c2dd44a232cdcef2f4b9515558dfc57ca37eb805be1b5a1

Observation 9c32cd87-1cab-4c45-bd17-7cc9dfc3c558 · outbound

This paper cites RT-1: Robotics Transformer for Real-World Control at Scale.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment RT-1: Robotics Transformer for Real-World Control at Scale

Reference 7

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source=pdf_text observed=2026-08-08T04:20:17.405321Z digest=sha256:93e054809dbdff51477778da686d48df33293285f3fe2156cf93f840aa7c450c

Observation 24670e7b-91a9-43a3-86c4-e3b244b8d6ca · outbound

This paper cites Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, et al.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, et al

Reference 8

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source=pdf_text observed=2026-08-08T04:20:17.410700Z digest=sha256:ecdc1fdb8bf218f9d94ac35b7b09f4a4ba76e45c002912f220a2ef97e372442b

Observation 31f4f47e-a8c3-41bc-bf7b-724a234e8249 · outbound

This paper cites UniVLA: Learning to Act Anywhere with Task-centric Latent Actions.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment UniVLA: Learning to Act Anywhere with Task-centric Latent Actions

Reference 9

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source=pdf_text observed=2026-08-08T04:20:17.415546Z digest=sha256:960fbb2232a4c7ab4c5f3fe8114c021be79dcb6be8b379f34d0d89dccf1b72fd

Observation b73ea498-3bb7-43f4-930f-b8fc3c3e2dc3 · outbound

This paper cites Egocentric-100k, 2025.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Egocentric-100k, 2025

Reference 10

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source=pdf_text observed=2026-08-08T04:20:17.421097Z digest=sha256:2cdf60ff65344a117166c33e3f5614cb76b939212d68c4cfcc20b9660819f174

Observation aa93645c-2c4f-454d-b981-b08171337661 · outbound

This paper cites Orb-slam3: An accurate open-source library for visual, visual–inertial, and multimap slam.IEEE transactions on robotics, 37(6): 1874–1890, 2021.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Orb-slam3: An accurate open-source library for visual, visual–inertial, and multimap slam.IEEE transactions on robotics, 37(6): 1874–1890, 2021

Reference 11

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source=pdf_text observed=2026-08-08T04:20:17.425782Z digest=sha256:bd3a9ce297adaf14429a856e59178e9eff3990a88e0ac615cd9285142d4e184f

Observation 8f1b3314-28cd-4af7-ad0c-390c3519f802 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Emerging properties in self-supervised vision transformers

Reference 12

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source=pdf_text observed=2026-08-08T04:20:17.430562Z digest=sha256:f76e9ab5846bd3c1f8edadff9327d55247a94c17d2e620ab8ec929a69c90dc95

Observation 80515d3a-d747-4831-a1b6-a5338f3a7438 · outbound

This paper cites WorldVLA: Towards Autoregressive Action World Model.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment WorldVLA: Towards Autoregressive Action World Model

Reference 13

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source=pdf_text observed=2026-08-08T04:20:17.435194Z digest=sha256:f905dbb8d94c7fca892a71e31b4adac6bbacc244b2e85a1427309e9b33a510ad

Observation 716aa8d5-1370-4c20-8bb7-a0f5b4d68207 · outbound

This paper cites Mirage: Cross-Embodiment Zero-Shot Policy Transfer with Cross-Painting.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Mirage: Cross-Embodiment Zero-Shot Policy Transfer with Cross-Painting

Reference 14

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source=pdf_text observed=2026-08-08T04:20:17.440001Z digest=sha256:16663269fe2feef8fb908df6ffa5b6b6b2454d55fff589a63eec470b91e1bef7

Observation 91ac49c7-f39c-4284-a055-45e07e72874f · outbound

This paper cites Moto: Latent motion token as the bridging language for learning robot manipulation from videos.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Moto: Latent motion token as the bridging language for learning robot manipulation from videos

Reference 15

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source=pdf_text observed=2026-08-08T04:20:17.444923Z digest=sha256:aef36aee358f859c48f70e7eb8481a3ef995062af1a4fa8f48be5ea172071555

Observation ee7d9eb6-1138-4f80-b461-5e64528d49d3 · outbound

This paper cites Rescaling egocentric vision: Collection, pipeline and challenges for epic-kitchens-100.International Journal of Computer Vision, 130:33–55, 2022.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Rescaling egocentric vision: Collection, pipeline and challenges for epic-kitchens-100.International Journal of Computer Vision, 130:33–55, 2022

Reference 16

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source=pdf_text observed=2026-08-08T04:20:17.449306Z digest=sha256:c9808ba422c9e04b3b6663a12f76eb8d4ac0d39fd58e9ce7b51aa534cddd1ec9

Observation 645db272-770a-4ebe-8f57-0426f8644a29 · outbound

This paper cites Video language planning.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Video language planning

Reference 17

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source=pdf_text observed=2026-08-08T04:20:17.454126Z digest=sha256:7525f1ada8e664d6d3fdf058c95574c3d97b1c05b5526143aa1af0a29a9043bf

Observation f0b5aba7-c0a0-46ac-b429-ae57247c91a0 · outbound

This paper cites DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos

Reference 18

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source=pdf_text observed=2026-08-08T04:20:17.459118Z digest=sha256:f2b4ec3626eeb214eb5e76fdbf227d73ffc84dd51c175a76f4994220482ffa22

Observation 8de8c896-699d-405d-8c7a-d2b608ad8e81 · outbound

This paper cites Ego4d: Around the world in 3,000 hours of egocentric video.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Ego4d: Around the world in 3,000 hours of egocentric video

Reference 19

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source=pdf_text observed=2026-08-08T04:20:17.463745Z digest=sha256:458e091aadd9f1a0e364737adb42a15604b629352ce88b297f5a35f8aafd4c3e

Observation 11a84cdf-8427-4d45-bacd-aed56f77fb31 · outbound

This paper cites Ego-exo4d: Un- derstanding skilled human activity from first- and third-person perspectives.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Ego-exo4d: Un- derstanding skilled human activity from first- and third-person perspectives

Reference 20

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source=pdf_text observed=2026-08-08T04:20:17.468217Z digest=sha256:41ab59b7e7d939c4dc2103d030084fc31534868df0b59eacebcd1d7c283fa801

Observation 806eb031-ca14-46bd-9f85-a381988c4673 · outbound

This paper cites Prediction with action: Visual policy learning via joint denoising process.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Prediction with action: Visual policy learning via joint denoising process

Reference 21

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source=pdf_text observed=2026-08-08T04:20:17.472516Z digest=sha256:6ca2dfc26fd01e8283df850e32dbda3e2b5be3598145c4f5103ce112132ac46f

Observation f6bf58b0-c10d-4373-8062-2a1f7f34cecf · outbound

This paper cites Mastering Diverse Domains through World Models.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Mastering Diverse Domains through World Models

Reference 22

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Observation 90851362-bed0-4675-8750-10ce35cd6849 · outbound

This paper cites EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video

Reference 23

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Observation dc57ed6d-da16-499a-aa25-91ec782c4dcd · outbound

This paper cites Robomind 2.0: A multimodal, bimanual mobile manipulation dataset for generalizable embodied intelligence.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Robomind 2.0: A multimodal, bimanual mobile manipulation dataset for generalizable embodied intelligence

Reference 24

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source=pdf_text observed=2026-08-08T04:20:17.486347Z digest=sha256:d02b3bbd0c38b038befc6ba38d4b469bd798bf902e3e525b459d608660986c16

Observation 3d33ec86-7bfb-4347-8b68-057949a39568 · outbound

This paper cites Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representations.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representations

Reference 25

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source=pdf_text observed=2026-08-08T04:20:17.490892Z digest=sha256:cd4d08c15aa671326376184d1b8b3aa86ab2dd796bef92645520c9fa44f76f9d

Observation e334248f-1372-41be-af1f-6fa9c549d859 · outbound

This paper cites $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization

Reference 26

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source=pdf_text observed=2026-08-08T04:20:17.512801Z digest=sha256:23bde0fa6d4267c7ea6dff7a570fd30034bc26936af52b6337cb135fc567890a

Observation 6612c5d9-83e5-4945-befc-b98369cddf28 · outbound

This paper cites Interndata-m1.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Interndata-m1

Reference 27

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source=pdf_text observed=2026-08-08T04:20:17.540722Z digest=sha256:84d83dc6ff6c7fb4b16001e61bc955de9cf345b9b8d80fedba55b1fbbd4e1df1

Observation ef19f389-1546-4e98-9d15-fcb6ad89c383 · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment OpenVLA: An Open-Source Vision-Language-Action Model

Reference 29

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source=pdf_text observed=2026-08-08T04:20:17.589345Z digest=sha256:faff68d2253fb45f43e41ac0b04d92380eea85b5d7787d99191db7f84079c15c

Observation 92148372-c732-448c-b85c-e6a1223c8fd8 · outbound

This paper cites Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

Reference 30

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source=pdf_text observed=2026-08-08T04:20:17.617524Z digest=sha256:70c7b6ca24e39ac43b43b1cff8fbcf35650b673509345b98f352ae26273bdc02

Observation cc64ec47-9b59-422a-aee2-8170062b3ef7 · outbound

This paper cites Learning to act from actionless videos through dense correspondences.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Learning to act from actionless videos through dense correspondences

Reference 31

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source=pdf_text observed=2026-08-08T04:20:17.648052Z digest=sha256:7f59d73579e5fc4b05097e199726915c956fd6847a0653f25c1d1e559f0b36bf

Observation 9ab5775e-274d-45e6-84fa-4d69846f5fc1 · outbound

This paper cites Learning from the Best: Smoothness-Driven Metrics for Data Quality in Imitation Learning.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Learning from the Best: Smoothness-Driven Metrics for Data Quality in Imitation Learning

Reference 32

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source=pdf_text observed=2026-08-08T04:20:17.664691Z digest=sha256:5e5f1e4a3a33a8268da4b1b177742d9a1622eed743cd5440365ea1d5e0435049

Observation ee262e71-8c00-4974-941b-56bd4f637e34 · outbound

This paper cites Let-base-dataset.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Let-base-dataset

Reference 33

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source=pdf_text observed=2026-08-08T04:20:17.669540Z digest=sha256:d7a3693263d024b18e7206307c0afe6b571315eba86583e36ff6ed58005226d7

Observation ba2db704-6b9c-4731-a224-7c7b96626094 · outbound

This paper cites Behavior-1k: A benchmark for embodied ai with 1,000 everyday activities and realistic simulation.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Behavior-1k: A benchmark for embodied ai with 1,000 everyday activities and realistic simulation

Reference 34

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source=pdf_text observed=2026-08-08T04:20:17.674095Z digest=sha256:492805e4399cd0a6d2e904ce40149bee576b0aa335db7ad830419cef668c9401

Observation f51fd8b7-e43a-4063-8dac-8644d6c42c76 · outbound

This paper cites Causal World Modeling for Robot Control.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Causal World Modeling for Robot Control

Reference 35

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source=pdf_text observed=2026-08-08T04:20:17.678978Z digest=sha256:73086d0dd9b1fbe5d85b3ebfb96007f9c28bc2ae555f7808cd30c66d72647111

Observation 03893cec-0a12-4e22-b1eb-b4ace11a6aad · outbound

This paper cites CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation

Reference 36

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source=pdf_text observed=2026-08-08T04:20:17.684378Z digest=sha256:163a3be94fa5eb46db772e7b1d86e46e50ab6d27551ee3ce67b476944c972ead

Observation bbc9aa23-ba79-4b69-8162-e900abd766c9 · outbound

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

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Hamster: Hierarchical action models for open-world robot manipulation

Reference 37

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raw_fallback, observed 2026-08-08T04:20:19.423118Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:17.689247Z digest=sha256:61549df0a59d5c585de077cbb9ea3e8ada0b42f2057b72f66b3eb69e34d38110

Observation 73948b7d-7fdd-43fc-9723-f33f793faca5 · outbound

This paper cites EgoLive: A Large-Scale Egocentric Dataset from Real-World Human Tasks.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment EgoLive: A Large-Scale Egocentric Dataset from Real-World Human Tasks

Reference 38

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source=pdf_text observed=2026-08-08T04:20:17.693692Z digest=sha256:c03570053c6cf8a074f5b50d59dd52722288fe198bae4d0b7d44de17842ec25b

Observation 7b4f74ba-1b1a-44e1-88e8-3c2f236b46ba · outbound

This paper cites CLAM: Continuous Latent Action Models for Robot Learning from Unlabeled Demonstrations.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment CLAM: Continuous Latent Action Models for Robot Learning from Unlabeled Demonstrations

Reference 39

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source=pdf_text observed=2026-08-08T04:20:17.698342Z digest=sha256:f95ea405249e0ea0ebb53097aff7ca8f036c91462f2d65d655d6f8fba90d1dbe

Observation ed480fc6-81e9-41c0-a127-6500b714971a · outbound

This paper cites Flow Matching for Generative Modeling.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Flow Matching for Generative Modeling

Reference 40

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source=pdf_text observed=2026-08-08T04:20:17.702672Z digest=sha256:67183b812a366fe782a672c9458b3a63593bf3ce2ad00e51f806b93ce1ae7f04

Observation 13de0e7e-4ccc-4bd0-bbfc-316db8033c25 · outbound

This paper cites LARA: Latent Action Representation Alignment for Vision-Language-Action Models.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment LARA: Latent Action Representation Alignment for Vision-Language-Action Models

Reference 41

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source=pdf_text observed=2026-08-08T04:20:17.707960Z digest=sha256:cd31b80c5a44a3648ac709851e7f20d12ecde8ed115478698ffe518cdb3052d7

Observation 745ce748-b8d5-4ec5-b900-cf7f1d14e9c5 · outbound

This paper cites LDA-1B: Scaling Latent Dynamics Action Model via Universal Embodied Data Ingestion.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment LDA-1B: Scaling Latent Dynamics Action Model via Universal Embodied Data Ingestion

Reference 42

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source=pdf_text observed=2026-08-08T04:20:17.713043Z digest=sha256:183f03ee75911a788244c10757021072866fadb3bcc7beafc478b185041a898f

Observation bc3d9c78-2cd5-4b53-9a4c-1cecfb258ddb · outbound

This paper cites Unifying perception and action: A hybrid- modality pipeline with implicit visual chain-of-thought for robotic action generation.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Unifying perception and action: A hybrid- modality pipeline with implicit visual chain-of-thought for robotic action generation

Reference 43

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raw_fallback, observed 2026-08-08T04:20:19.408442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:17.717794Z digest=sha256:7182ec70efe09dc2b7f1561b06794a2d1737175932a5549de4734cf017b4d432

Observation 67d6486f-d4e1-4932-bd3d-51e284061543 · outbound

This paper cites Latent Action Learning Requires Supervision in the Presence of Distractors.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Latent Action Learning Requires Supervision in the Presence of Distractors

Reference 44

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source=pdf_text observed=2026-08-08T04:20:17.721810Z digest=sha256:a41de96042a14b6e6fdd9acbe429b81d9d15895cb01bd5814f88458c924f47fd

Observation c60be46d-ef60-4bb0-9bfe-b0fcc6a8cd73 · outbound

This paper cites Cosmos-embed1: A joint video-text embedder for physical ai, 2025.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Cosmos-embed1: A joint video-text embedder for physical ai, 2025

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-08T04:20:19.393027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:17.726667Z digest=sha256:83e4c2ffe9e3ab08ac3bef7a33ed0ec75eb1d425625e499cfd283603b3c1563a

Observation 80cb2622-d304-4db9-9a44-f4131d897aa1 · outbound

This paper cites Baihu dataset.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Baihu dataset

Reference 46

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verified fuzzy
raw_fallback, observed 2026-08-08T04:20:19.377284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:17.731387Z digest=sha256:b06957142e63eedaa3dcb6b3262da580304d11480cc9562b9d6cb155fd6d99b3

Observation 1f61b309-80d9-4290-9ca4-723161c95eca · outbound

This paper cites mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAs.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment mimic-video: Video-Action Models for Generalizable Robot Control Beyond VLAs

Reference 47

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source=pdf_text observed=2026-08-08T04:20:17.735904Z digest=sha256:e177c12415e7bdbe4d1a7fba6658c3b73c23881cd6373ab55ea1115a59766f0d

Observation 0a76d984-57a8-4cc9-b325-ca2139ae8ddc · outbound

This paper cites Reconstructing hands in 3d with transformers.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Reconstructing hands in 3d with transformers

Reference 48

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source=pdf_text observed=2026-08-08T04:20:17.740500Z digest=sha256:30f05293e78949ff39568f19643d350052e42c8da49529a0538b0c345a92a961

Observation 7c76b65f-ff59-42b9-9ba4-09eef952411d · outbound

This paper cites FAST: Efficient Action Tokenization for Vision-Language-Action Models.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment FAST: Efficient Action Tokenization for Vision-Language-Action Models

Reference 49

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source=pdf_text observed=2026-08-08T04:20:17.745291Z digest=sha256:6720d10da47a6885d42ec9a4ed70f681b46617813059901a110bc2623295bfa7

Observation 7ea55de1-9e25-4592-918e-5463672ec670 · outbound

This paper cites EgoVerse: An Egocentric Human Dataset for Robot Learning from Around the World.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment EgoVerse: An Egocentric Human Dataset for Robot Learning from Around the World

Reference 50

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source=pdf_text observed=2026-08-08T04:20:17.749807Z digest=sha256:993e5547dc5b1f906693727b6df10e0401cf0e97689d22b95bbb47dba9e0a4de

Observation 4cb9c265-bc4e-4f9d-bec3-23bfec796d23 · outbound

This paper cites Embodied Hands: Modeling and Capturing Hands and Bodies Together.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Embodied Hands: Modeling and Capturing Hands and Bodies Together

Reference 51

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source=pdf_text observed=2026-08-08T04:20:17.754322Z digest=sha256:36030291d5be2c66d6e06541afd9871bc819518adff627303bc3d96c4d058591

Observation bfcce5ac-aa81-4693-a97c-b6043d703c47 · outbound

This paper cites Xperience-10m: A large-scale egocentric multimodal dataset with structured 3d/4d annotations, 2026.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Xperience-10m: A large-scale egocentric multimodal dataset with structured 3d/4d annotations, 2026

Reference 52

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raw_fallback, observed 2026-08-08T04:20:19.351131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:17.782938Z digest=sha256:1dfd6ee211da4177e867214852fafbf32d71e13b5ea18f2197e8af58de3fc386

Observation c4e4ba20-cd19-447b-8044-7863649f348a · outbound

This paper cites An Efficient Metric for Data Quality Measurement in Imitation Learning.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment An Efficient Metric for Data Quality Measurement in Imitation Learning

Reference 53

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verified exact
local_arxiv, observed 2026-08-08T04:20:18.595098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:17.811009Z digest=sha256:bf7876732d5f6d9c9da41cb48bc606d633ab8263f744b91a2260dc00e0a9c4c9

Observation 49364af1-a6d4-452d-8c19-456d3b749db8 · outbound

This paper cites Emma-x: An embodied multimodal action model with grounded chain of thought and look-ahead spatial reasoning.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Emma-x: An embodied multimodal action model with grounded chain of thought and look-ahead spatial reasoning

Reference 54

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raw_fallback, observed 2026-08-08T04:20:19.334060Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:17.854766Z digest=sha256:0417efe7b8cf1b2725d50b500267447abefd65abc92b1d1738feb45ab21660f9

Observation 2e5c3cd3-caf2-4afa-b41b-067b9a6ea88b · outbound

This paper cites Galaxea g0.5 technical report.arxiv, 2026.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Galaxea g0.5 technical report.arxiv, 2026

Reference 55

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raw_fallback, observed 2026-08-08T04:20:19.318339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:17.868299Z digest=sha256:a4e415bf31018457756452d6c3ff12abaea40290155363c58b12f9ecd764ccb6

Observation 4d62c81b-731e-4fd1-bafd-25ad225d4eb2 · outbound

This paper cites Motubrain: An Advanced World Action Model for Robot Control.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Motubrain: An Advanced World Action Model for Robot Control

Reference 56

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source=pdf_text observed=2026-08-08T04:20:17.873076Z digest=sha256:9a27769e960f1c9e4d3450c52f1b7d6e36f39ffe331dd3d215176cfb87863dc6

Observation d2755c85-91b4-40fb-ac52-1677357c9d8d · outbound

This paper cites Predictive in- verse dynamics models are scalable learners for robotic manipulation.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Predictive in- verse dynamics models are scalable learners for robotic manipulation

Reference 57

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verified fuzzy
raw_fallback, observed 2026-08-08T04:20:19.302893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:17.878492Z digest=sha256:e6d328b39e61761059594a3b4b1f9d3251fb697ca220f937ff710e9593b28fd2

Observation 99637964-6c58-47f5-98f7-218681273eae · outbound

This paper cites Interndata-a1: Pioneering high-fidelity synthetic data for pre-training generalist policy.arXiv preprint arXiv:2511.16651, 2025.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Interndata-a1: Pioneering high-fidelity synthetic data for pre-training generalist policy.arXiv preprint arXiv:2511.16651, 2025

Reference 58

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source=pdf_text observed=2026-08-08T04:20:17.883021Z digest=sha256:d35f24fcb2db120128c72604d89220dc0efd43ab70ff94edc921d1b57c7e7b24

Observation 60678bf3-db2a-423d-8762-9066059d9dec · outbound

This paper cites Vggt: Visual geometry grounded transformer.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Vggt: Visual geometry grounded transformer

Reference 59

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raw_fallback, observed 2026-08-08T04:20:19.287600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:17.887745Z digest=sha256:7905ce42dac14a17afd383a4830f38a4b8dc44f9c4a8025f1fcc674e4a1db85c

Observation 8edb9feb-10ab-4b9b-88a5-b499a8ed7b6d · outbound

This paper cites Scaling proprioceptive-visual learning with heterogeneous pre-trained transformers.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Scaling proprioceptive-visual learning with heterogeneous pre-trained transformers

Reference 60

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raw_fallback, observed 2026-08-08T04:20:19.271822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:17.892249Z digest=sha256:ebaf05822806bc5be7978bfc4ae9ea8c5ce0169a7a7a519b1bfff3c5f500d7fc

Observation 40fb96b1-1180-4285-9095-e64b55b5f79a · outbound

This paper cites Vq-vla: Improving vision-language-action models via scaling vector-quantized action tokenizers.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Vq-vla: Improving vision-language-action models via scaling vector-quantized action tokenizers

Reference 61

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source=pdf_text observed=2026-08-08T04:20:17.896725Z digest=sha256:1aee8bfd2ae47caaa9f5ef17695d09307caeb06f7b37b471d84595b0e08a4ed7

Observation 8480c661-946f-4c66-9deb-eb5acb8461be · outbound

This paper cites Humanego: Zero-shot robot learning from minutes of human egocentric videos.arXiv e-prints, pages arXiv–2605, 2026.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Humanego: Zero-shot robot learning from minutes of human egocentric videos.arXiv e-prints, pages arXiv–2605, 2026

Reference 62

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raw_fallback, observed 2026-08-08T04:20:19.247523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:17.901082Z digest=sha256:7956c5e213c6ba196c41f418d0b9ad4be493e729b3bb30810c10d1f29f111662

Observation 918693b3-e914-4992-9693-0fae7c5b7e5b · outbound

This paper cites RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment RoboMIND: Benchmark on Multi-embodiment Intelligence Normative Data for Robot Manipulation

Reference 63

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source=pdf_text observed=2026-08-08T04:20:17.905555Z digest=sha256:4ea8b16b6adc222dc690bad50f8f0feb34ce1ce725105f2b2f456ddc872fdeb1

Observation 6e59e679-5677-4692-ab51-6814aaf0aa31 · outbound

This paper cites RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment RoboCOIN: An Open-Sourced Bimanual Robotic Data Collection for Integrated Manipulation

Reference 64

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source=pdf_text observed=2026-08-08T04:20:17.918768Z digest=sha256:973b40b504fe2bbc0559b01ff2cda2b36a46c537c8d376a2499b8de69862fa6d

Observation 1d31e7d4-fdaa-4e38-98b1-9e465cf63053 · outbound

This paper cites RL Token: Bootstrapping Online RL with Vision-Language-Action Models.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment RL Token: Bootstrapping Online RL with Vision-Language-Action Models

Reference 65

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source=pdf_text observed=2026-08-08T04:20:17.942358Z digest=sha256:631d24529de3f14b7bd065b98190e80bca753b620575256d66195752be6b1baf

Observation 9addfd48-b0ce-41fd-a3a5-b9b61e6268fd · outbound

This paper cites Gigaworld-policy: An efficient action-centered world–action model.arXiv preprint arXiv:2603.17240, 2026.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Gigaworld-policy: An efficient action-centered world–action model.arXiv preprint arXiv:2603.17240, 2026

Reference 66

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source=pdf_text observed=2026-08-08T04:20:17.999798Z digest=sha256:bbe454ce7152188e1b86cbb7956d8214a027b23bfbc92708431be1eed62facdd

Observation cc4d0f29-1699-4bc0-901b-915f80d7efb2 · outbound

This paper cites Latent action pretraining from videos.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Latent action pretraining from videos

Reference 67

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verified fuzzy
raw_fallback, observed 2026-08-08T04:20:19.232813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:18.025997Z digest=sha256:49c97bdd5b1e227620636f56f89a7dee1a88eb0a055e00a8f6dd079b14f30975

Observation d7de02df-bdd7-4815-90b2-6a59d65b697e · outbound

This paper cites World Action Models are Zero-shot Policies.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment World Action Models are Zero-shot Policies

Reference 68

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source=pdf_text observed=2026-08-08T04:20:18.032859Z digest=sha256:6fdb23453f699a0d70a9fb73a4c3487bf389bb751ac78911f118c842021ca7f3

Observation 6127a04d-15b7-48aa-8494-b37d76481408 · outbound

This paper cites Genie Sim 3.0 : A High-Fidelity Comprehensive Simulation Platform for Humanoid Robot.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Genie Sim 3.0 : A High-Fidelity Comprehensive Simulation Platform for Humanoid Robot

Reference 69

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source=pdf_text observed=2026-08-08T04:20:18.038905Z digest=sha256:c279d94b2f6ab5e0ac12b7fcd28bd85e20d8f3195e05d0c29a20bb8403bd867c

Observation 2725f2c2-eb14-403b-843d-87eb122cc2a1 · outbound

This paper cites Qwen-RobotManip Technical Report: Alignment Unlocks Scale for Robotic Manipulation Foundation Models.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Qwen-RobotManip Technical Report: Alignment Unlocks Scale for Robotic Manipulation Foundation Models

Reference 70

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source=pdf_text observed=2026-08-08T04:20:18.044437Z digest=sha256:8ab7610af1f0af3e495854909532201de3b9a414a0c60ab2a667d4e5ff8de3d7

Observation 8fcfa032-8c04-4f04-b209-ca046708bcbe · outbound

This paper cites Fast-WAM: Do World Action Models Need Test-time Future Imagination?.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Fast-WAM: Do World Action Models Need Test-time Future Imagination?

Reference 71

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:20:18.049955Z digest=sha256:fd550150a444c0cca70dd83de06812d9afac242e1a071430afb1c01aa3220dd8

Observation f216a178-9176-4952-8d7d-dde9833a9aff · outbound

This paper cites Robotic Control via Embodied Chain-of-Thought Reasoning.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Robotic Control via Embodied Chain-of-Thought Reasoning

Reference 72

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no resolver link, observed 2026-08-08T04:20:18.055631Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-08T04:20:18.055631Z digest=sha256:930a877e4cc692ca92a978c700d49f1b82d76e7fd3875bfe14c3694df5d07d1a

Observation 3a61dded-a74b-4058-9477-5707da93762b · outbound

This paper cites Atomicvla: Unlocking the potential of atomic skill learning in robots, 2026.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Atomicvla: Unlocking the potential of atomic skill learning in robots, 2026

Reference 73

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-08T04:20:18.061102Z digest=sha256:8aa1893269a7272728503f98f8b1f97e43b0e975b835fddb4c75777c8a797605

Observation 3905c5e6-cfc9-4635-955a-e431ed44d0ed · outbound

This paper cites Efros, Eli Shechtman, and Oliver Wang.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Efros, Eli Shechtman, and Oliver Wang

Reference 74

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verified fuzzy
raw_fallback, observed 2026-08-08T04:20:19.218191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:18.066384Z digest=sha256:d01add8e0b0f18085fc86bd9373891dd0adf4ed5ed3fc158cce1d3e4ef09f9ef

Observation d3a32a04-3acf-40dc-8994-f45e6dcb8493 · outbound

This paper cites JoyAI-RA 0.1: A Foundation Model for Robotic Autonomy.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment JoyAI-RA 0.1: A Foundation Model for Robotic Autonomy

Reference 75

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no resolver link, observed 2026-08-08T04:20:18.073152Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-08T04:20:18.073152Z digest=sha256:2b970131ae78c3f3e00a481ba3317a83132620b240fcc2ec84f7a38f237a3d93

Observation fb08cb4e-37ef-4f48-a50d-bd418300f58e · outbound

This paper cites Dreamvla: a vision-language-action model dreamed with comprehensive world knowledge.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Dreamvla: a vision-language-action model dreamed with comprehensive world knowledge

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:20:19.202799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:18.089381Z digest=sha256:b8cbb1dd57a95600fb716d9017987d369b2ea11b686efb1fe11cf4926e7654a5

Observation 48253b1d-1e8b-4b68-a2bb-934fbdffb6f7 · outbound

This paper cites Cot-vla: Visual chain-of-thought reasoning for vision-language-action models.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Cot-vla: Visual chain-of-thought reasoning for vision-language-action models

Reference 77

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no resolver link, observed 2026-08-08T04:20:18.097497Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-08T04:20:18.097497Z digest=sha256:a275f81b3d975923f4f84e9566f3a7b4558bf37e95dd1049f4e478ba3b2740fc

Observation 21289431-3773-4879-9487-34d3f0d6fbbe · outbound

This paper cites Sim2real vla: Zero-shot generalization of synthesized skills to realistic manipulation.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Sim2real vla: Zero-shot generalization of synthesized skills to realistic manipulation

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:20:19.177763Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:18.103196Z digest=sha256:9cadfb5ebf8ce83c012e0048794b7fc348f2a28c403db6f448db22c42a23e131

Observation 0b821915-bf46-41c2-8330-6e208628e715 · outbound

This paper cites Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-08T04:20:18.108528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:20:18.108528Z digest=sha256:1d5a3c76900fa22e90fb6e145119637bf6c8defa16b5371254d28e7d590fd074

Observation ba009782-44f6-47f2-80f5-d6289af2b4da · outbound

This paper cites Rt-2: Vision-language-action models transfer web knowledge to robotic control.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Rt-2: Vision-language-action models transfer web knowledge to robotic control

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T04:20:19.161758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-08T04:20:18.114193Z digest=sha256:85b46da0c30caccc018883c4bbc27cea77f5264905627cbd401b4713ff89d76b

Observation 2441a3d6-23f3-4a82-99cc-c6675b880936 · outbound

This paper cites Galaxea Open-World Dataset and G0 Dual-System VLA Model.

JoyAI-RA 0.5: Scaling Robot Manipulation Learning via Dual Action Alignment Galaxea Open-World Dataset and G0 Dual-System VLA Model

Reference 2025

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unresolved
no resolver link, observed 2026-08-08T04:20:17.578972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T04:20:17.578972Z digest=sha256:47682cfaf4f81794b7c7adac1eeff5f6316dc372420c319be8b3a2ccfdc5697a

Pith citing papers

No inbound Pith citation observations are available.