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Paper Citation Record · LEDGER

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

As of 15 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 2026-08-14T06:32:32.682623+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

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=sha256:00f3fc76e720f055027a1a12de6e4682261a363b55c7df23a124a5649688c5ac

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:f184c6be40175d3dc6c96e612bf1c3cedb1d2879d33184bd7bd49204ebcef968

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=sha256:9d132e803d4b6f12ba35f2e7aa04a28f03996ad20bcfafe981fdba0edb727f30

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:db8b302a316b97efc949163b1b55a2c3fc01e1553e268d4cf1c9f163473de12d

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

source=pdf_text observed=2026-08-07T04:08:30.980745Z digest=sha256:329c9c75bdd67765e611cfd2e9a8df4e26f209c1b760fec32a58781f13906d8f

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=sha256:12dcbc218ccb210f527bb29e799701e9208aa97015d533bb21a36b717d911bf9

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:ad45735ee57ad8f68237f1bf41a661a5b8d52ed23180fe79ad1c4ef3db9a3deb

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

source=pdf_text observed=2026-08-07T04:08:31.733430Z digest=sha256:9e82bb199d28a7ccbbef7dff273e35b699835899825fed6bf89e4a35c8c1b1dd

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:c675cb1b507635666483b2565a3dd45133898b36f9aadcc63c8e51ae76cc6e2e

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=sha256:1accf4da1885fbf9dc618d2510fa4ecf003aa67b7d7cbdff212fc9f410bed5fe

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:ca3159c4a1bb30193037a8100b83c3922751b01b0bda20dde2b8d633187aca8d

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:e3f7093e696afbfe7e7e4bf7f6146fefe8a5954d190ab808fc6e0dca7b3db208

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=sha256:4ded5dcb2bae04feeb4f9658f7fb8985e453e80bbcdb02857df5b063db7e44b7

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:ad0960ac0eb5ccf53aa17022727ba627a79ed1c84b81e0f989eb95587bc80c98

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:d0d3d55883f4d8e63b413a9ff71e51e84d7de4061627773ef6b09526e1c9f5aa

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=sha256:71507f7fbd4199b1a97e405e78dd7b7f969fdb3e705c7ebf906b0af4129ffb9f

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:c189fd8b2f6d5a5ee75968dad24d3d109202362b8ff05e1cc1e42a0bc78979dc

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=sha256:98a07856602fbadfd695d720d637bad9085ae7144903fbfa384e6550ecd2bdea

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:aee20e90736fb4d95656be09d701ed28933de34f24dcc3977162bb2c62c2e392

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=sha256:496a20cf2ec20ca309f90e0247bbf48fa560597ec9ec61051db7d62ca6dc1143

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=sha256:81dd8fbd376353ece6784239c4a4d5deda636e8565828283e82445aaac021d02

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=sha256:9548d1e42f0df2941f437e141f8b9f4e650269986ba10e03a886759ec02b8022

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=sha256:2e120d9ac1aaeaf85920c007c415a565f11702a6d1545f7bb9ec334a6cbe2d2a

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=sha256:55baf4e51c5ec90d8f6114e19beb13c1c369deeaca4081e0305a2302ea4d8400

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=sha256:64fb833e6d09494f0a252e87d5428ce5e738cb0356d61a926a46507f430f5987

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=sha256:6d0215ab0e69602fd416a17139f3ea6ab4b8cda7bcb2f4e4f3228697280f8110

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=sha256:778dec2fd2a3d86b933da997ce0a34cf7a715fded81951880850c2d4ab39cb97

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

source=pdf_text observed=2026-08-07T04:08:34.770206Z digest=sha256:bed6a403350f9cd255dfa7787eea825e46e5b9adfeccfc550c7c9ea6d1bfa4f1

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:f1a277ce4f518dc39e66a194078acf339c257ece1e7cdf388125601a6e807e2d

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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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:31.338877Z digest=sha256:a8a2d89cf2e3ef5e132b5e890cf41091fe23272dd0bc3b54ff264c4bcd5d471b

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=sha256:7a539eeca250a9316c6cf6c3e5000517e48127aaed2c8f4412df8b71c34af9f0

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=sha256:9e18c3eccc9fe10cb21829b11b4a58e3063617fb9dd3bc284a25c563b8f1c2d0

Pith citing papers

No inbound Pith citation observations are available.