Paper Citation Record · LEDGER

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning

As of 11 August 2026, this Paper Citation Record lists 86 of 86 outbound references and 15 inbound Pith citation observations for arXiv:2505.17006.

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

pith.paper-citation-record.v1
2505.17006 v3

Coverage vector

measured 86 of 86 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:56:41.618867Z

measured 101 of 101 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T06:18:04.994485Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-03T04:27:36.264850Z

Reference resolution

86 of 86 outbound references displayed

verified exact0
verified fuzzy33
unresolved53
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 22386f00-d9c6-4ada-a704-6328c1c6624a · outbound

This paper cites GPT-4 Technical Report.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning GPT-4 Technical Report

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:31.783573Z

Source-reported events for the cited work

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Observation 99f1f8fa-9ed1-4a25-945d-2f7e359b8c0b · outbound

This paper cites Learning dexterous in-hand manipulation.The Inter- national Journal of Robotics Research, 39(1):3–20, 2020.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Learning dexterous in-hand manipulation.The Inter- national Journal of Robotics Research, 39(1):3–20, 2020

Reference 2

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Observation 76ea3cf0-984a-4faa-b96e-7d13b059ff97 · outbound

This paper cites Affordances from human videos as a versatile representation for robotics.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Affordances from human videos as a versatile representation for robotics

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:31.950338Z

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Observation 1d7c1656-b81d-498e-b6b0-42b23703f075 · outbound

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

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Gen2Act: Human Video Generation in Novel Scenarios enables Generalizable Robot Manipulation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:32.082618Z

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Observation 386ece9e-0e21-4a07-9c8e-8e0413f31b48 · outbound

This paper cites Towards generalizable zero-shot manip- ulation via translating human interaction plans.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Towards generalizable zero-shot manip- ulation via translating human interaction plans

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:32.233704Z

Source-reported events for the cited work

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Observation d3afaf54-fca5-4125-8d64-718bae8d046c · outbound

This paper cites Track2act: Predicting point tracks from internet videos enables diverse zero-shot robot manip- ulation.arXiv e-prints, pages arXiv–2405, 2024.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Track2act: Predicting point tracks from internet videos enables diverse zero-shot robot manip- ulation.arXiv e-prints, pages arXiv–2405, 2024

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:32.384855Z

Source-reported events for the cited work

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Observation 8f4c2a1b-f6b6-4ac7-94f4-5a4b5aee3c0d · outbound

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

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:32.499878Z

Source-reported events for the cited work

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Observation 1f6a5cbe-014d-4cec-a6da-53216c3957cf · outbound

This paper cites an unresolved cited work.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:32.607048Z

Source-reported events for the cited work

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Observation fbd56a7c-1d17-4f38-96a9-c1913a060f50 · outbound

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

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning RT-1: Robotics Transformer for Real-World Control at Scale

Reference 9

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Source-reported events for the cited work

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Observation cc155f46-a02e-438c-9f55-e2a452569f54 · outbound

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

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning AgiBot World Colosseo: A Large-scale Manipulation Platform for Scalable and Intelligent Embodied Systems

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:32.616203Z

Source-reported events for the cited work

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Observation 7877c53e-9388-40f5-8970-c782b2c0e3f9 · outbound

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

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning UniVLA: Learning to Act Anywhere with Task-centric Latent Actions

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:32.640982Z

Source-reported events for the cited work

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Observation 1d476429-2f2e-4b3f-a7de-7f7bf0476c35 · outbound

This paper cites WorldVLA: Towards Autoregressive Action World Model.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning WorldVLA: Towards Autoregressive Action World Model

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:32.779945Z

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Observation 24bbbd95-4594-40e9-8c1b-be99106b09b0 · outbound

This paper cites GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:32.880004Z

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Observation 7535f42c-d1de-40cb-bfbf-eac6ee1cc129 · outbound

This paper cites DeepVerse: 4D Autoregressive Video Generation as a World Model.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning DeepVerse: 4D Autoregressive Video Generation as a World Model

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:33.022075Z

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Observation 87d28d03-a0ad-4bca-a374-5a7b333b7764 · outbound

This paper cites IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning IGOR: Image-GOal Representations are the Atomic Control Units for Foundation Models in Embodied AI

Reference 15

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Observation 890bf866-5c44-4517-8078-2936bd53db35 · outbound

This paper cites villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning villa-X: Enhancing Latent Action Modeling in Vision-Language-Action Models

Reference 16

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Observation d8314d15-f6de-4d58-99b1-a3cc8eea7fce · outbound

This paper cites Moto: Latent mo- tion token as the bridging language for learning robot ma- nipulation from videos.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Moto: Latent mo- tion token as the bridging language for learning robot ma- nipulation from videos

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:33.344464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b25bcbbb-f9ed-4986-9757-a39fa3f72be2 · outbound

This paper cites Universal manipulation interface: In-the-wild robot teaching without in-the-wild robots.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Universal manipulation interface: In-the-wild robot teaching without in-the-wild robots

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:49.850891Z

Source-reported events for the cited work

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Observation e57e62d6-09f1-4b6e-a4f5-1baea46075bb · outbound

This paper cites Diffusion policy: Visuomotor policy learning via action dif- fusion.The International Journal of Robotics Research, 44 (10-11):1684–1704, 2025.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Diffusion policy: Visuomotor policy learning via action dif- fusion.The International Journal of Robotics Research, 44 (10-11):1684–1704, 2025

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:49.659069Z

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Observation 8ec858f1-e571-4441-a762-6b4c3f6b9520 · outbound

This paper cites Dynamo: In-domain dynamics pretraining for visuo-motor control.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Dynamo: In-domain dynamics pretraining for visuo-motor control

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:49.424023Z

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Observation dc50e3be-39b8-4711-8ce8-e63e5b8da00d · outbound

This paper cites Bert: Pre-training of deep bidirectional trans- formers for language understanding.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Bert: Pre-training of deep bidirectional trans- formers for language understanding

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:49.183135Z

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Observation 017c1337-9fed-4e00-869e-2ad12297b903 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning An image is worth 16x16 words: Transformers for image recognition at scale

Reference 22

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Observation b8b988ff-16c2-4c2b-81a9-b914a0bf0585 · outbound

This paper cites Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better

Reference 23

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Observation ae624b62-179a-41cd-83ef-ce0090126007 · outbound

This paper cites Learning universal policies via text-guided video genera- tion.Advances in neural information processing systems, 36:9156–9172, 2023.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Learning universal policies via text-guided video genera- tion.Advances in neural information processing systems, 36:9156–9172, 2023

Reference 24

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Observation 63b67dff-4f12-45d7-a84c-d065bb2cc811 · outbound

This paper cites Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens

Reference 25

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Observation f23f9dd9-7973-42a6-a4de-bf8c67503b65 · outbound

This paper cites RH20T: A comprehensive robotic dataset for learning di- verse skills in one-shot.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning RH20T: A comprehensive robotic dataset for learning di- verse skills in one-shot

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:48.737146Z

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Observation 71c825b4-9aa3-4f05-98b7-4c0bee54a48f · outbound

This paper cites Adaworld: Learning adaptable world models with latent actions.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Adaworld: Learning adaptable world models with latent actions

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:48.544160Z

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Observation 87530bff-c61e-4481-80ef-73a7fec925b7 · outbound

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

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos

Reference 28

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Observation fe736a04-2a99-4177-9d95-354fab74729e · outbound

This paper cites RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches

Reference 29

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Observation 7da0c5f5-ca0f-4650-b360-6dfc8ec8397c · outbound

This paper cites Masked autoencoders are scalable vision learners.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Masked autoencoders are scalable vision learners

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:48.345966Z

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Observation 6b7d3554-622b-4b2d-93f3-c35a46291c63 · outbound

This paper cites Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Denoising dif- fusion probabilistic models.Advances in neural information processing systems, 33:6840–6851, 2020

Reference 31

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CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Unresolved cited work

Reference 32

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Observation d6229945-444b-4ae4-90a0-d372e6214676 · outbound

This paper cites Bc-z: Zero-shot task generalization with robotic imitation learning.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Bc-z: Zero-shot task generalization with robotic imitation learning

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:47.631415Z

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Observation b628af0f-f625-4924-acc0-de9089218dee · outbound

This paper cites Robotic grasp- ing using deep reinforcement learning.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Robotic grasp- ing using deep reinforcement learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:47.412144Z

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Observation aecd2f10-6cbe-4424-907c-b452be976e7c · outbound

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

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset

Reference 35

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Observation 6c8673aa-da7b-4db7-9ce5-7368e1f1a93b · outbound

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

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning OpenVLA: An Open-Source Vision-Language-Action Model

Reference 36

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Observation 17b4b429-82bc-484c-81d9-fa312b1c1061 · outbound

This paper cites Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success

Reference 37

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Observation da172c2c-1e2f-4231-9fb0-4479243c419b · outbound

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

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

Reference 38

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Observation 5e549f1e-a20d-4ea7-bd54-3d9136d0b7d7 · outbound

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CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Adam: A Method for Stochastic Optimization

Reference 39

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Observation 897fb361-f246-4069-8dda-9c61961e321c · outbound

This paper cites Segment any- thing.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Segment any- thing

Reference 40

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Observation b90f2d53-e0af-4fc1-b1d3-47ac69419831 · outbound

This paper cites Tenenbaum.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Tenenbaum

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:47.173564Z

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Observation e4f746b1-ce77-4f22-86d7-f8a30e27c75c · outbound

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

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning CogACT: A Foundational Vision-Language-Action Model for Synergizing Cognition and Action in Robotic Manipulation

Reference 42

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Observation 766028de-d46f-4126-9775-ffe1bf942bad · outbound

This paper cites Autoregressive image generation without vec- tor quantization.Advances in Neural Information Processing Systems, 37:56424–56445, 2024.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Autoregressive image generation without vec- tor quantization.Advances in Neural Information Processing Systems, 37:56424–56445, 2024

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Source-reported events for the cited work

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Observation e06d4802-c6bb-46fa-89b9-e32f33860c88 · outbound

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

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning CLAM: Continuous Latent Action Models for Robot Learning from Unlabeled Demonstrations

Reference 44

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Observation 1e14667b-ea42-4bdb-bd57-940576f72a41 · outbound

This paper cites Flow Matching for Generative Modeling.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Flow Matching for Generative Modeling

Reference 45

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Observation c1d3d381-2afc-4eae-bf5f-f94e1466912e · outbound

This paper cites Libero: Benchmarking knowl- edge transfer for lifelong robot learning.Advances in Neural Information Processing Systems, 36:44776–44791, 2023.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Libero: Benchmarking knowl- edge transfer for lifelong robot learning.Advances in Neural Information Processing Systems, 36:44776–44791, 2023

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:46.867371Z

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Observation b3a16e09-5265-4fce-a8f6-d80b1e4528fb · outbound

This paper cites HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Model.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning HybridVLA: Collaborative Diffusion and Autoregression in a Unified Vision-Language-Action Model

Reference 47

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Observation 91454c3f-fe8c-4128-9e8e-488ef8d54ee9 · outbound

This paper cites Rectified Flow: A Marginal Preserving Approach to Optimal Transport.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Rectified Flow: A Marginal Preserving Approach to Optimal Transport

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Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:37.435792Z

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Observation c016224b-a916-47ad-9b5a-5fbde84adce8 · outbound

This paper cites RDT-1B: a diffusion foundation model for bimanual manipulation.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning RDT-1B: a diffusion foundation model for bimanual manipulation

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:56:46.639358Z

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Observation 11329dda-5725-4c35-8729-918d64d90a99 · outbound

This paper cites Unified Embodied VLM Reasoning with Robotic Action via Autoregressive Discretized Pre-training.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Unified Embodied VLM Reasoning with Robotic Action via Autoregressive Discretized Pre-training

Reference 50

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Observation 4395234a-2a81-4578-aa68-10a761eca08c · outbound

This paper cites DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models

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Resolution: unresolved; no resolver link, observed 2026-08-07T14:56:37.727000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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This paper cites Being-h0.

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Observation 22292ca0-7802-4340-b494-99ad30100678 · outbound

This paper cites Towards generalist robot learning from in- ternet video: A survey.Journal of Artificial Intelligence Re- search, 83, 2025.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Towards generalist robot learning from in- ternet video: A survey.Journal of Artificial Intelligence Re- search, 83, 2025

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dd0e4a18-9733-4229-b570-dc9ec7d1cc63 · outbound

This paper cites Calvin: A benchmark for language- conditioned policy learning for long-horizon robot manip- ulation tasks.IEEE Robotics and Automation Letters, 7(3): 7327–7334, 2022.

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4291300b-7f8b-49c4-a2ec-2e7e5d431785 · outbound

This paper cites Struc- tured world models from human videos.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Struc- tured world models from human videos

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Source-reported events for the cited work

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Observation 7162bf4f-ba51-4eb7-b278-ec4863ab93ea · outbound

This paper cites Robotwin: Dual-arm robot benchmark with generative digi- tal twins (early version).

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e8016e64-0167-46c4-b1b3-4fb732abbfaa · outbound

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Observation 5ca2bb9f-76df-4146-ae5d-e1b022300281 · outbound

This paper cites Latent action learning requires supervision in the presence of distractors.

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Source-reported events for the cited work

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Observation fc1438ea-4827-47a5-8a27-a5bf2bb2572e · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Representation Learning with Contrastive Predictive Coding

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Source-reported events for the cited work

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Observation e49b0b75-e49c-426a-98da-b2e5372db460 · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning DINOv2: Learning Robust Visual Features without Supervision

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Observation 403e9781-c3ab-46e6-b8ac-a526f42e6337 · outbound

This paper cites Open x-embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Open x-embodiment: Robotic learning datasets and rt-x models: Open x-embodiment collaboration 0

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Observation 20f02a57-d5b0-434b-8332-99e9539a6eda · outbound

This paper cites Scalable diffusion models with transformers.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Scalable diffusion models with transformers

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Observation 132fd4aa-6801-4824-b057-cf858f0030ee · outbound

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Source-reported events for the cited work

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Observation 2150779b-75d6-473c-a549-582a5500ee0a · outbound

This paper cites Improving language understanding by gen- erative pre-training.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Improving language understanding by gen- erative pre-training

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7e1295c6-1dfe-4e3a-a64b-7d6e3b861745 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer.Journal of machine learning research, 21(140):1–67, 2020.

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d429a206-3785-4eba-9fd5-4058e2f94591 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning SAM 2: Segment Anything in Images and Videos

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Source-reported events for the cited work

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Observation ffea3315-c38c-4bc2-b5ef-c2902e437bf7 · outbound

This paper cites Motion before action: Diffusing object mo- tion as manipulation condition.IEEE Robotics and Automa- tion Letters, 2025.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Motion before action: Diffusing object mo- tion as manipulation condition.IEEE Robotics and Automa- tion Letters, 2025

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation da5bdcaf-fb0d-4d2f-bc55-8f2b6902ab6f · outbound

This paper cites Behavioral Cloning from Observation.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Behavioral Cloning from Observation

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Observation 212b802a-5dfc-419d-8d5f-70d5c9340082 · outbound

This paper cites Neural discrete representation learning.Advances in neural information pro- cessing systems, 30, 2017.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Neural discrete representation learning.Advances in neural information pro- cessing systems, 30, 2017

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f3cb3cee-3432-4b29-9d12-c3803e41c8d9 · outbound

This paper cites MimicPlay: Long-Horizon Imitation Learning by Watching Human Play.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning MimicPlay: Long-Horizon Imitation Learning by Watching Human Play

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Source-reported events for the cited work

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Observation 0e1ebdec-0fea-4c11-b809-ce33c88a7903 · outbound

This paper cites Tdn: Temporal difference networks for efficient action recog- nition.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Tdn: Temporal difference networks for efficient action recog- nition

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation eba3de72-db0f-477b-ac34-c9d316dc5fd1 · outbound

This paper cites EgoVid-5M: A Large-Scale Video-Action Dataset for Egocentric Video Generation.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning EgoVid-5M: A Large-Scale Video-Action Dataset for Egocentric Video Generation

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Observation 93929ffa-5587-4763-b82f-b365ee5c494e · outbound

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

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Vq-vla: Improving vision- language-action models via scaling vector-quantized action tokenizers

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 809b10e5-0f56-49df-b2f3-4c54e5a820d1 · outbound

This paper cites Any-point trajectory modeling for policy learning.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Any-point trajectory modeling for policy learning

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 38ddd823-3fd4-46c9-9381-1891ed181075 · outbound

This paper cites Tinyvla: Towards fast, data-efficient vision- language-action models for robotic manipulation.RAL,.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Tinyvla: Towards fast, data-efficient vision- language-action models for robotic manipulation.RAL,

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b2761b91-1784-4d90-a111-4e3178c92092 · outbound

This paper cites Flow as the Cross-Domain Manipulation Interface.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Flow as the Cross-Domain Manipulation Interface

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Source-reported events for the cited work

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Observation b8f439d0-6dd7-44b8-bde8-42a8b0dc0497 · outbound

This paper cites Spatiotemporal Predictive Pre-training for Robotic Motor Control.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Spatiotemporal Predictive Pre-training for Robotic Motor Control

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Source-reported events for the cited work

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Observation c0221f6b-e15c-432a-a62d-c6e879b1df20 · outbound

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CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Transferring foundation models for generalizable robotic manipulation

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d992746c-b945-4f62-992a-34970f393fc3 · outbound

This paper cites Tra-moe: Learning trajectory pre- diction model from multiple domains for adaptive policy conditioning.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Tra-moe: Learning trajectory pre- diction model from multiple domains for adaptive policy conditioning

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 29df59bc-d9fd-4b6d-a80c-b8269c34710f · outbound

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CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning EgoVLA: Learning Vision-Language-Action Models from Egocentric Human Videos

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Source-reported events for the cited work

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Observation 1a45bc75-9667-4dc9-a453-5efb935d7ec5 · outbound

This paper cites Latent action pretraining from videos.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Latent action pretraining from videos

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cdba56e2-5111-4ee8-a30b-44de3eb6b082 · outbound

This paper cites DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge

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Source-reported events for the cited work

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Observation 2c8ad561-3481-4112-965a-8bd66644f316 · outbound

This paper cites Zhao, Vikash Kumar, Sergey Levine, and Chelsea Finn.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Zhao, Vikash Kumar, Sergey Levine, and Chelsea Finn

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d6f515ff-3bb3-4c0f-8819-ccb3a23225c0 · outbound

This paper cites Aether: Geometric-aware unified world modeling.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Aether: Geometric-aware unified world modeling

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a90562a2-a51c-4ed5-b952-f6c52278bd2a · outbound

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CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning Rt-2: Vision-language-action models transfer web knowledge to robotic control

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation b6588c65-327e-4d39-85c5-d9660e10c3ad · outbound

This paper cites 3, 9, 10, 12, 13.

CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning 3, 9, 10, 12, 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Pith citing papers

Observation 35f452a7-6957-459a-b4e1-943cec727dd7 · inbound

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 19f51061-b3a8-4216-a741-c974fe8f40c4 · inbound

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a427a797-0c2d-43fc-9781-c1a7049a7834 · inbound

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 549380b7-d68b-4b0a-8839-732c98d4436f · inbound

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 43183e4e-38a8-4b78-a3d5-e206e4bcabf8 · inbound

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Observation 92e70c91-9fd9-4a23-ac3a-a09ce17febd5 · inbound

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 874a24f2-2312-4959-8be8-c15ee3bce7a9 · inbound

Lifting Unlabeled Internet-level Data for 3D Scene Understanding cites this paper.

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7d4a54cc-9250-4d06-aab5-4d96e1867809 · inbound

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation cce587a7-4eac-42e9-8db9-96e6f3b4f7d9 · inbound

Being-H0.7: A Latent World-Action Model from Egocentric Videos cites this paper.

Being-H0.7: A Latent World-Action Model from Egocentric Videos CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 93a0adec-ef9d-4b4c-b466-8e81a66d6128 · inbound

From Imagined Futures to Executable Actions: Mixture of Latent Actions for Robot Manipulation cites this paper.

From Imagined Futures to Executable Actions: Mixture of Latent Actions for Robot Manipulation CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c073d9dd-2b6b-4df9-ac19-c5d2dfab073f · inbound

RotVLA: Rotational Latent Action for Vision-Language-Action Model cites this paper.

RotVLA: Rotational Latent Action for Vision-Language-Action Model CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e664ebbc-fe12-4a04-9f07-670aef69ff51 · inbound

Mitigating State Aliasing in Vision-Language-Action Models via Inverse Dynamics Learning cites this paper.

Mitigating State Aliasing in Vision-Language-Action Models via Inverse Dynamics Learning CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 25fdcd7d-18ab-453b-b234-cf988e341c1f · inbound

CLAW: Learning Continuous Latent Action World Models via Adversarial Latent Regularization cites this paper.

CLAW: Learning Continuous Latent Action World Models via Adversarial Latent Regularization CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8eeb06f6-8fdf-4ad8-b092-c9302b77841a · inbound

LAFP: Preserving Latent Action Structure in Latent Policy Learning via Flow Matching cites this paper.

LAFP: Preserving Latent Action Structure in Latent Policy Learning via Flow Matching CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning

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Resolution: verified exact; local_arxiv, observed 2026-07-03T04:27:36.266068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8baa9522-1109-4440-8095-57ac4bc1d5e1 · inbound

ShadowDancer: Teaching Video World Models Any Action by Learning Unified Dynamics Representations from a Video and Its Shadow cites this paper.

ShadowDancer: Teaching Video World Models Any Action by Learning Unified Dynamics Representations from a Video and Its Shadow CoMo: Learning Continuous Latent Motion from Internet Videos for Scalable Robot Learning

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