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Paper Citation Record · LEDGER

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

As of 14 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 2026-08-14T06:32:32.682623+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

No source-named external measurement is stored.

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=sha256:2f064e572e6203dbd8b236879b2d5031c75dd0c3adf33b883bb6d5358280e1b0

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=sha256:61acb4f18059de47637baa0a16f611d433aaa91025dbfa97dfda2de738ebb23a

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=sha256:5efb0b555e9a9fc6ec8115e96b05ca4168c28e57e77d7c20f620bbe483aa836c

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=sha256:6dddd2d20852e60f96425a21f273632a7e9aeb1c8fe142af779104d020899e4c

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=sha256:1437754b7079856ecb81664f168727c8de3b6e8f92fa9d17eccbc3ec692898b7

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=sha256:72db03862fdd549b16307a53edf5832492bed763b27963e266f5f88c5ebea99e

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=sha256:5ab8a8c4b73f3415bebf0167dbcdb1bf98e4e9b8092abefc851b6dae09430626

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:be880073f30e2f739c7971352102a098d16bb6542bf79e165cd37d7b31383bc3

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=sha256:4140c830e5e006856433818e21e7327415ee66829dddeef8eca3982c0741f5e6

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=sha256:7c3433a007652564d6ef98bb2e73715c0ba67bbc155b7711770cb192b7ce9536

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:f2c05053c92dcca18b0ea5cb0de3f2a8978fac3b42773140d5824f0cd8446756

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=sha256:729672d1d1c94ec730b446cd65a3f7c6834512aeb7d0a7fb1542653a6f43611f

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:cbbf5daf0fbcc1d5bbc6dbcafcea212e069dacba16eaaa94f87860fc851d6985

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=sha256:1871437519dacd0ba28315aa9fde6e9464f4bf99f5e3dd00955ecff2e09634a0

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:efcdc2d4445ba66f18a1642da18ca6fda750c661651236e8b455f05a26008acd

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=sha256:4b2c60b1214d6d7850360bef2048d94a10ef9c39e608371fcec5e6cf8bba6e0e

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:eb2af648d870125c0553a71efa18074f1736dcf71f706bca3731f83ffa218aef

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=sha256:605cfe80235206f734ade05b633b1eee00ad5d1f38d844b2cbb3fc5871ceef1c

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:abf51a3e0d90df5b7f34330db49037f7eac6870732441f1943a2f61ef1fb593a

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=sha256:2e050c20f42516a6c635714df5393ce0c07c30c5b2cbaf5ed843477c491dec4d

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=sha256:92f2e88140b8e37d9f8a28dbf3247aef7849bdf49cd946f54432863ee35bbfba

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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source=pdf_text observed=2026-08-08T04:20:17.476950Z digest=sha256:7aedbade91aba96cdab123f3f8a2d660935fccad7f9d0319cea1ccb472d3f477

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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source=pdf_text observed=2026-08-08T04:20:17.481561Z digest=sha256:8276851914da00e624b4a652f7a1ac09853c9c9bb2276ec47ca55e6704ba006e

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=sha256:4225f5c38df8c891a5a19393782dc2f1a08dbeb56e89e351e739605d17497120

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=sha256:080f48ed33e6e75a40dacf89a8aa85e2e795e909baad046f649ed4bda2da44c6

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=sha256:8ee8cbdd86b3e8ea665049c0eb72c6fc784b13a9e41303c9186eab6c5a03e117

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=sha256:6d9b4b88741654b046f2f8c6cde9ff9294ba4307e3c9ac889a7433848730f805

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:d4fe1a9471d239cad8ff986375fa329c6f147548eea015287dfb9d5e4c2d03ec

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=sha256:7796603e65a0c99734f87b8554593bd968e5e2446dd2d35875e640b30861ee61

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=sha256:59873f90d936c570b153d457990e802a9049a08ead9f26624132b6fe6f4f73ac

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:f458400cdd6a66ddf641f6f766eb99be06b4c400e91a15cf093562dded8fe2ea

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:f6dbaf031f8b6fc3ce0337a5901a920460b1bad6728ed359fddf388337961e91

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=sha256:8385306d478608cca4d8a48db249fb5b779d4956215deb1fd84a3c88e9ce8a27

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=sha256:9765fb5ee7b1e91929d525fc8729324cc5c2bc6432e85d6c1756a4fe2d3fd1ef

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=sha256:4a336ec3d856edcec06b9f6e61c2159b686dcf57e218c2bba9183d8f71d52ecd

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:17.689247Z digest=sha256:f146732e203d6d689b28111c11a3b459c3b230f8e9171fa0c923a59d9dfb7199

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=sha256:1b8b1ca6b644b1d0655124a0fda80a9c9bfaeaa9d1630b79d0f1c80bfa002097

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:d73f10dfa715c6eb6a918640ce7abe31ca1fca9c8e0bb2975db46c199e6a9057

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=sha256:0c892e21fa299f403957494d81491ac02e7f8e233d1a4a4ff50c92c11202daf0

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:b13e4b659ebbcdccd7cf878b249c9c39bb1b7a9e4f1eb192add336d7426d3de2

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:da1af97f0356fb6fe14ab838594deab573d9723dd846fc2a7ace153e5aed40ec

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:17.717794Z digest=sha256:d3e34d01a37e323bc67853b9edc3a0791e56ae90184596ff9b0792b73693b0ef

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=sha256:657023b89c10d8aaa02fed495a78a7bbd4e668189794894e5ef83cbf9acfd581

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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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:17.726667Z digest=sha256:cdd840dafb26084db8aa8021bb3fc6a408f32aad88354006a4525b21a8a451b6

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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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:17.731387Z digest=sha256:6925144d6740716491b13ea5c47f8759c82cdfa2643eabaf0af4cae0d7b14128

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=sha256:1741bebe1d2fa26b8b74cb6bb34c9517b9071a1b9f9e2445474626dfc26ffd0a

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=sha256:2c5baeca4e68dc8b566fd894c006a1b7241c69d1482d13ef553c506ca7415173

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=sha256:4ad4b7bbcbb203b4808f4abf20e3754f99bb9a0c2eb8cb76f038018c0b4307fd

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=sha256:6b6867441ded63259359be1f6b48ccb9ea6c37bfdb18418b7bc1f5a506904021

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=sha256:11dcd7ad2203f09704ac177915f42564f3a375f812c307e606b459a7c641cd5d

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:17.782938Z digest=sha256:a6214eeab683755e5795d4bc705a081f1488b88c4bfad1f49e22d3aae1302198

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:17.811009Z digest=sha256:1a65557829a10bbf14f3038b34f245da33fa8fbde4d3141ee338faa7c3f924a2

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:17.854766Z digest=sha256:b1b978b1f0fa0bfa062b3d6663341eaee24fbd8280bbc2c1538cdf06e102abc2

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:17.868299Z digest=sha256:a5b74f338aef7bca1b5d33d4d2d733a8979760365ba88adc0fc383cff3d75a14

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:eaf98e378dff4b85fb92ce98e3c1f18dc30ec7dc113e2f9b1cdd3d4008f15fa0

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:17.878492Z digest=sha256:5d6568ab54b8dc03f896305c2300de77121d081c16d30c67d420938bea9b5462

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=sha256:2a386cef73b73899240ec238df11f007868384d0413f544e3126e3a6b52e5b0e

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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verified fuzzy
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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:17.887745Z digest=sha256:24346bf240c5dea8dd0e2979a2c7b8b8fdd0583de545c0502d1705d392593d38

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:17.892249Z digest=sha256:942922457fc2dc84f29b823e5dd7d61c364ea35231abd9d22507aa6db0582e18

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=sha256:4ca64f508a7bb86ac3f949980e2cf30dcb07103d903694f41af07ba5235d084e

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:17.901082Z digest=sha256:ac37c10cf73d059701b73724ed98ef96b7a2484f141feb82d7ee91e5591f7806

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=sha256:234a21f643fbcd0d84477c8bc59f3fe0dea9797059189ed9dcb9bc0b40b79ba0

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-reported events for the cited work

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source=pdf_text observed=2026-08-08T04:20:17.918768Z digest=sha256:baeb2899c6df2c9f40767e7fb0a29e510372c8a13e8b63e486ad475e9c6bd4b2

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=sha256:858076e55ca4e7009b23622be2abe40833e5339445f45c16ba324a1acca1aefe

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:df40930e6481dc66d0f5757b3d74089000ee1b8c3a37adbf2cb79e37d9624ee1

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:18.025997Z digest=sha256:a18995b87e52d80181add2522e13bd4027e2ff1bb92818b227e04d32d3883c0a

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:cf8ec2581950141eac646879226e44bdfb1c55bb1d13545181ed30f30d6235ec

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:b9feac4e65dcdacdded34ca7c126dc01e6de596c261b59d52703f9eca758bd4d

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=sha256:4202007c677df19e304f247d612b3317684a83c21fb8298ad6ef4de286a3c0c2

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=pdf_text observed=2026-08-08T04:20:18.049955Z digest=sha256:c0c6176ccfef8264d4ca6362347bde4adc8124a3cbaef9744c24d30f6c3d620f

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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source=pdf_text observed=2026-08-08T04:20:18.055631Z digest=sha256:6820e554a2fdce2ee3a32af9f40283bfa7121a4becd646b47fb7c02021df2abe

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=pdf_text observed=2026-08-08T04:20:18.061102Z digest=sha256:dccaddd43e761f9e0b2db98df3e2ddd92a00ed2d9563625076e34557d31c123e

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:18.066384Z digest=sha256:62dfb6f853cc1f392cda4495e2267ab8006f8b2525f4eb6ac1baf1ed5fb6a1c8

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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Source-reported events for the cited work

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source=pdf_text observed=2026-08-08T04:20:18.073152Z digest=sha256:eb89091c24c23a703d3a9d62b8f67314e94911c19eb6042e3c29d395fde57013

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:18.089381Z digest=sha256:dc8db645cb3311b807f2691ec54a2d9f287170c49abe75b4de4839f9363c7332

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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source=pdf_text observed=2026-08-08T04:20:18.097497Z digest=sha256:9c44e8f4f639a0924ee7015ea4d8c04880c3d9b0fa66b1b58236baa562397d4b

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:18.103196Z digest=sha256:a5daa0abc3f78af2739e17f31563d5bfe63f34006d067b236220ba5774678c03

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=sha256:7f79f5276b552dc2b2774eb8264d9020b3aaa09994a2de17e2afa7ea92517fe0

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-08T04:20:18.114193Z digest=sha256:15580bbe64f642fc58e0f4df8e8b5818f85ffee4c91a0157399297f8aa94d552

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
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Source-reported events for the cited work

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source=pdf_text observed=2026-08-08T04:20:17.578972Z digest=sha256:8729285b50ec8829c672fdc6ee86d45c9840d9393b2b92e369cb867c8d2d58bc

Pith citing papers

No inbound Pith citation observations are available.