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Paper Citation Record · LEDGER

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation

As of 23 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2608.06374.

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

pith.paper-citation-record.v1
2608.06374 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:08:34.770206Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

32 of 32 outbound references displayed

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  • verified fuzzy2
  • unresolved29
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

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Outbound references

Observation 1649fcac-ca18-4e40-8f10-c7adf07e6430 · outbound

This paper cites Qwen3-VL Technical Report.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Qwen3-VL Technical Report

Reference 1

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source=pdf_text observed=2026-08-07T04:08:30.205321Z digest=sha256:279b08a8207723ef66da11b97effb63e4b00928ee91dd999209c0cc8df046fa3

Observation 2a6b57db-92ad-4772-adb5-67ec67d28af0 · outbound

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

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation GR00T N1: An Open Foundation Model for Generalist Humanoid Robots

Reference 3

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source=pdf_text observed=2026-08-07T04:08:30.467744Z digest=sha256:4abe426ee8efcd49d3d0825eb89ed31dc2f5664b53bfb8cff1cffaee37baed0b

Observation 7bf3de5f-7d1e-49da-a6a3-0549bdefa25f · outbound

This paper cites π0.5: a vision-language-action model with open-world generalization.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation π0.5: a vision-language-action model with open-world generalization

Reference 4

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source=pdf_text observed=2026-08-07T04:08:30.589081Z digest=sha256:6592ce781e4c353b8a74646ca327d2d18802ef7692ec13235b47947e7e33158c

Observation 8cd17faf-f616-489c-84c8-76eb8df3f413 · outbound

This paper cites WorldVLA: Towards Autoregressive Action World Model.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation WorldVLA: Towards Autoregressive Action World Model

Reference 6

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source=pdf_text observed=2026-08-07T04:08:30.854406Z digest=sha256:b30d5d9a7768714965c4ab64f64e4bcd2461fd551cdce4c8f523456a730883bb

Observation 95c66a4c-f7db-42ef-a2cd-ca379b979706 · outbound

This paper cites Unified diffusion vla: Vision-language-action model via joint discrete denosing diffusion process.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Unified diffusion vla: Vision-language-action model via joint discrete denosing diffusion process

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:08:30.980745Z digest=sha256:66d94e4a4a08c011e9ad85e189e726e98ec1bff8eca82cac8ebc26a570fbc879

Observation d8ec08ed-8be9-40d9-9570-3cefb9d7195a · outbound

This paper cites Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer

Reference 10

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source=pdf_text observed=2026-08-07T04:08:31.446237Z digest=sha256:989d14aaef3cc8000c7127f4762d93f3dbb2521031ef029bc5b6767c4b41310d

Observation ca4eac97-f468-4da1-9944-bd469dff7e5d · outbound

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

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation EgoDex: Learning Dexterous Manipulation from Large-Scale Egocentric Video

Reference 11

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source=pdf_text observed=2026-08-07T04:08:31.585050Z digest=sha256:7bb95f9bb52e6d928fadbab481dfbd42af2e3e1307d74ddcd4effa6b5abac47c

Observation 661c8415-e32d-42f7-a21e-379b73e1f64a · outbound

This paper cites X-DiffVLA: X-Embodied Diffusion Action Heads for Vision-Language-Action Models.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation X-DiffVLA: X-Embodied Diffusion Action Heads for Vision-Language-Action Models

Reference 12

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local_arxiv, observed 2026-08-07T04:08:35.494187Z

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:08:31.733430Z digest=sha256:23c438b0446868077d6b382b2a44a354a331b8c4e0d24721b8df53447743a2e6

Observation 6aaeeb94-8408-434b-a01d-86026369bf5d · outbound

This paper cites Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation

Reference 13

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source=pdf_text observed=2026-08-07T04:08:31.904125Z digest=sha256:55af3463803d874f93af35baf6a1d8b0a6d3984aee2cece3d2a290aafef46b30

Observation e890f8c1-332d-4d7d-8640-910bbff428c1 · outbound

This paper cites Flow Matching for Generative Modeling.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Flow Matching for Generative Modeling

Reference 14

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source=pdf_text observed=2026-08-07T04:08:32.026849Z digest=sha256:65d70149f530222a4ca9c64d8c8daa5068a0cbde3fb1745ed9733b4f1230502e

Observation 0627c0d9-437d-46fd-a078-75aa4482b4e3 · outbound

This paper cites RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation

Reference 15

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source=pdf_text observed=2026-08-07T04:08:32.170479Z digest=sha256:c91e4b44fc2cdce08e43fbb9fbd190085a80ca0081806cf39fc77be89b80f284

Observation 9f04f079-c9f0-46b7-aebf-1a9248facb2f · outbound

This paper cites Rdt2: Exploring the scaling limit of umi data towards zero-shot cross- embodiment generalization.arXiv preprint arXiv:2602.03310,.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Rdt2: Exploring the scaling limit of umi data towards zero-shot cross- embodiment generalization.arXiv preprint arXiv:2602.03310,

Reference 16

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source=pdf_text observed=2026-08-07T04:08:32.319686Z digest=sha256:a46328a9f8cb1dd93dab4112630b383a9b7f8cd444ae00f2b3c42c791c1f725e

Observation 36d4981d-d08b-4f6a-85bd-92b8aed13ce4 · outbound

This paper cites Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Being-H0: Vision-Language-Action Pretraining from Large-Scale Human Videos

Reference 17

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source=pdf_text observed=2026-08-07T04:08:32.515534Z digest=sha256:78b6b11b44ac1d057dd5e5b04f19cb0862b2abe91f453578823bfa948f183b70

Observation e3727072-d7ea-42fa-950a-547676b04672 · outbound

This paper cites F1: A Vision-Language-Action Model Bridging Understanding and Generation to Actions.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation F1: A Vision-Language-Action Model Bridging Understanding and Generation to Actions

Reference 18

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source=pdf_text observed=2026-08-07T04:08:32.698704Z digest=sha256:fcbae548e2569c610d17e22e7d531e1f974442b8a9d7f77ea5ecc8dfe5852fe2

Observation 35567722-aa66-41f9-845d-a8cff86b20ef · outbound

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

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation LDA-1B: Scaling Latent Dynamics Action Model via Universal Embodied Data Ingestion

Reference 19

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source=pdf_text observed=2026-08-07T04:08:32.864862Z digest=sha256:98d8ab2dc60af49233804ed296cc31e6bc31173f5ee280e0bfd40a924dae46e7

Observation b48ceb03-990a-46ad-be06-d8aa7137b986 · outbound

This paper cites Dit4dit: Jointly modeling video dynamics and actions for generalizable robot control.arXiv preprint arXiv:2603.10448,.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Dit4dit: Jointly modeling video dynamics and actions for generalizable robot control.arXiv preprint arXiv:2603.10448,

Reference 20

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source=pdf_text observed=2026-08-07T04:08:32.992667Z digest=sha256:e391b6f6ee02e7d7e5b28cf0a2c349a6ccbdc8d5e0e66d44ecc673849aa16201

Observation 1a4e4caf-28b9-4714-937d-997d46cbf171 · outbound

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

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Octo: An Open-Source Generalist Robot Policy

Reference 21

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source=pdf_text observed=2026-08-07T04:08:33.125804Z digest=sha256:d8dc6f9205d46c5d53b1455daf4272cecdc204526140e2a040b96b11786dee77

Observation b565bdd3-d70a-4935-bbdf-87154a678f5e · outbound

This paper cites Open X-Embodiment: Robotic Learning Datasets and RT-X Models.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Open X-Embodiment: Robotic Learning Datasets and RT-X Models

Reference 22

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source=pdf_text observed=2026-08-07T04:08:33.290245Z digest=sha256:df8818ea74d1479a5c5699a855b2143c00e88fe099e6ff23932bb2d9fa71ada1

Observation 0f4dcdf4-c9a5-4a80-97d0-ad9853dd29a7 · outbound

This paper cites Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Qwen-VLA: Unifying Vision-Language-Action Modeling across Tasks, Environments, and Robot Embodiments

Reference 23

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source=pdf_text observed=2026-08-07T04:08:33.495200Z digest=sha256:c7df7698793d08a35b9bda59955500cf79e95367c839935c5845e4b6ac67ef6a

Observation df557ac1-f5ed-4d1c-9085-6a0d1b74d5b8 · outbound

This paper cites SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation SANA: Efficient High-Resolution Image Synthesis with Linear Diffusion Transformers

Reference 24

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source=pdf_text observed=2026-08-07T04:08:33.762140Z digest=sha256:e39c536589afb75e05b3c59c85a44f248cee951e8fed3f50fada3e4c3df688ac

Observation 08c26dfa-6788-40a1-a319-f17e8b986f04 · outbound

This paper cites S-VAM: Shortcut video-action model by self-distilling geometric and semantic foresight.arXiv preprint arXiv:2603.16195,.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation S-VAM: Shortcut video-action model by self-distilling geometric and semantic foresight.arXiv preprint arXiv:2603.16195,

Reference 25

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source=pdf_text observed=2026-08-07T04:08:33.872178Z digest=sha256:64fd8a09262d9c4d0dbea20cd5dcf4ae5f3274239ba89d8dbe702d29de1ae618

Observation 8497af07-401d-4b51-837e-68ca3ab74b7f · outbound

This paper cites EgoVLA: Learning Vision-Language-Action Models from Egocentric Human Videos.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation EgoVLA: Learning Vision-Language-Action Models from Egocentric Human Videos

Reference 26

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source=pdf_text observed=2026-08-07T04:08:33.990715Z digest=sha256:cc02b9e4d013a63ff2e16066981b1e84647bb23604b855e7f32a85c0dd479f98

Observation 4f32dc7b-762f-477d-8103-39e7c570d5d1 · outbound

This paper cites ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning

Reference 27

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source=pdf_text observed=2026-08-07T04:08:34.107020Z digest=sha256:dadc216fcdecb9e6f79351c891726a475bbac7747565d9259f7525dffb377eff

Observation e7098613-4f50-45e8-b1c5-36b68c2c9667 · outbound

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

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Fast-WAM: Do World Action Models Need Test-time Future Imagination?

Reference 28

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source=pdf_text observed=2026-08-07T04:08:34.194886Z digest=sha256:271dfa204273d074550a42fb80b4352f5ab066705575040a925387b40206f66c

Observation f19e7637-c24c-4a27-a3b8-a8b371bd3d28 · outbound

This paper cites X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model

Reference 29

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source=pdf_text observed=2026-08-07T04:08:34.328037Z digest=sha256:4e59096f62da3bd09779d7412adf79edf98a41cb85071046e0690c81576d0847

Observation 9de9e644-1520-4f75-b9a0-4f49416a8123 · outbound

This paper cites Dualcot-vla: Visual-linguistic chain of thought via parallel reasoning for vision-language-action models.arXiv preprint arXiv:2603.22280,.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Dualcot-vla: Visual-linguistic chain of thought via parallel reasoning for vision-language-action models.arXiv preprint arXiv:2603.22280,

Reference 30

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source=pdf_text observed=2026-08-07T04:08:34.454382Z digest=sha256:29f6c0e4726bf06eb73325804338f3985e48e1eb7154b46e8a6b62e81ae27082

Observation dff9f64b-0ab7-4687-b3bf-6ca0ce99c360 · outbound

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

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Unified World Models: Coupling Video and Action Diffusion for Pretraining on Large Robotic Datasets

Reference 31

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source=pdf_text observed=2026-08-07T04:08:34.605130Z digest=sha256:069c79dc28a880d3208cfff1ffa18e26019298ee9668b1ddfd9788cac8c46a9d

Observation 4b1325a6-460c-460c-ae7f-6ddbc9686921 · outbound

This paper cites Pour water from the cup into the bowl.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Pour water from the cup into the bowl

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-07T04:08:35.818773Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-07T04:08:34.770206Z digest=sha256:f8200e1d3ebdb104724441b9ed998494c1373eef173e4e83f9147f57ecc2b495

Observation 8820e162-4e63-4253-a374-b4892f8b70f2 · outbound

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

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation UniVLA: Learning to Act Anywhere with Task-centric Latent Actions

Reference 2023

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source=pdf_text observed=2026-08-07T04:08:30.741535Z digest=sha256:eb88f6c89f68bc0abe34b2dafd0f65606643af6b6e9a8d5b80caa34521184bd8

Observation 007ffccb-8d24-4cf9-b888-6ada2a48fe4c · outbound

This paper cites HiMoE-VLA: Hierarchical Mixture-of-Experts for Generalist Vision-Language-Action Policies.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation HiMoE-VLA: Hierarchical Mixture-of-Experts for Generalist Vision-Language-Action Policies

Reference 2024

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source=pdf_text observed=2026-08-07T04:08:31.338877Z digest=sha256:fe5cdb993577fa53f44adb1c54f2ee5973c56d7223be30889a96858669572dda

Observation d42209f7-9bd3-4862-89a5-bf9b552a7448 · outbound

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

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation Motus: A Unified Latent Action World Model

Reference 2025

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source=pdf_text observed=2026-08-07T04:08:30.343015Z digest=sha256:ee4c47161bc8e471da771e294fd18ef112a2e02d1bca1ec91cda47a2ea5fe15c

Observation 10140715-8be0-4680-87c4-b1fcde1c48f8 · outbound

This paper cites RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation.

DyPES-VLA: Learning Shared Dynamics Priors and Embodiment-Specific Control for Cross-Embodiment Manipulation RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation

Reference 2026

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source=pdf_text observed=2026-08-07T04:08:31.186529Z digest=sha256:8bed0adc376aafe08d196d2a19446025d1c37d86e5ec4c5f93b0b6c2a9749602

Pith citing papers

No inbound Pith citation observations are available.