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Paper Citation Record · LEDGER

Prediction with Action: Visual Policy Learning via Joint Denoising Process

As of 20 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 6 inbound Pith citation observations for arXiv:2411.18179.

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

pith.paper-citation-record.v1
2411.18179 v1

Coverage vector

measured 59 of 59 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T11:29:20.811592Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T22:13:14.907035Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T18:57:17.161071Z

Reference resolution

59 of 59 outbound references displayed

  • verified exact0
  • verified fuzzy8
  • unresolved51
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 98bec869-122c-4248-9328-9a2914df0f74 · outbound

This paper cites The role of motor contagion in the prediction of action.

Prediction with Action: Visual Policy Learning via Joint Denoising Process The role of motor contagion in the prediction of action

Reference 1

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Observation 59550b03-2c7f-4b99-9d54-e9f1c061b9c3 · outbound

This paper cites Prediction, cognition and the brain.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Prediction, cognition and the brain

Reference 2

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Observation 246fe2c2-10d0-495e-bb1f-8f6a25a70763 · outbound

This paper cites Awareness of action: Inference and prediction.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Awareness of action: Inference and prediction

Reference 3

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Observation 0c1ff756-8edd-4a65-8d58-d032524b7d63 · outbound

This paper cites Denoising diffusion probabilistic models.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Denoising diffusion probabilistic models

Reference 4

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Observation 80087f4d-8dfa-401d-a6d0-3a0520217b21 · outbound

This paper cites Denoising Diffusion Implicit Models.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Denoising Diffusion Implicit Models

Reference 5

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Observation 3704d80d-64e2-4641-a1a5-68db3e2b2514 · outbound

This paper cites Improved denoising diffusion probabilistic models.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Improved denoising diffusion probabilistic models

Reference 6

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Observation 220e4ccc-be6e-4bf4-98e8-7e5cbeb20495 · outbound

This paper cites Imagenet: A large- scale hierarchical image database.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Imagenet: A large- scale hierarchical image database

Reference 7

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Observation a02a181e-c98c-43d0-a90c-8f7cce19a5ae · outbound

This paper cites something something.

Prediction with Action: Visual Policy Learning via Joint Denoising Process something something

Reference 8

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Observation 0d6c6c4d-d844-49f3-a216-8a51b9ea7e8c · outbound

This paper cites Bridgedata v2: A dataset for robot learning at scale.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Bridgedata v2: A dataset for robot learning at scale

Reference 9

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Observation 1459e623-74e4-430e-922e-eb9e29d0827c · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 10

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Observation 88ada21c-1690-4683-ac7d-80a8442e5ab8 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Adding conditional control to text-to-image diffusion models

Reference 11

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Observation c6440b6e-d649-41b7-8814-81fffa8bc20e · outbound

This paper cites Imagic: Text-based real image editing with diffusion models.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Imagic: Text-based real image editing with diffusion models

Reference 12

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Observation d344ad8d-7aad-40f0-ba15-79355a005bd4 · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Imagen Video: High Definition Video Generation with Diffusion Models

Reference 13

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source=pdf_text observed=2026-08-12T11:29:20.630308Z digest=sha256:fd052387fd53d13a0a4cf3b94294b04e710a188c7645220987b7638aea2d6799

Observation 6c06af8f-a645-424f-9a7a-7e6a47acc7b3 · outbound

This paper cites CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers.

Prediction with Action: Visual Policy Learning via Joint Denoising Process CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers

Reference 14

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Observation 923ae2b7-2a1e-4c92-a7e1-bd5ed04e2c17 · outbound

This paper cites Latte: Latent Diffusion Transformer for Video Generation.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Latte: Latent Diffusion Transformer for Video Generation

Reference 15

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Observation b41e90c1-4a05-4e34-994d-2a3fdd625606 · outbound

This paper cites Diffusion Policy: Visuomotor Policy Learning via Action Diffusion.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Diffusion Policy: Visuomotor Policy Learning via Action Diffusion

Reference 16

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Observation 8977ae24-4ab1-4555-9fab-a586347e325a · outbound

This paper cites Learning universal policies via text-guided video generation.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Learning universal policies via text-guided video generation

Reference 17

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Observation da2644d2-1950-40cc-9572-4727db72a04d · outbound

This paper cites Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models

Reference 18

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source=pdf_text observed=2026-08-12T11:29:20.650295Z digest=sha256:d2c4b522c5959f31fa2407b36fdc94c6c5c021696e9a0cdce4d812f02623f5b8

Observation 9c4e3a28-c2f4-4916-8ae1-8f82e4330c81 · outbound

This paper cites Compositional foundation models for hierarchical planning.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Compositional foundation models for hierarchical planning

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation a9186ff0-9d84-4290-ba67-cea540980681 · outbound

This paper cites Scalable diffusion models with transformers.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Scalable diffusion models with transformers

Reference 20

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source=pdf_text observed=2026-08-12T11:29:20.658731Z digest=sha256:3ee161dca460fbbef24207ee38c76ce239422ec311526d622eed17265ea15780

Observation 76a63347-7c1d-47df-99a9-2bdc06169929 · outbound

This paper cites Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Meta-world: A benchmark and evaluation for multi-task and meta reinforcement learning

Reference 21

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Observation df73a117-21b1-42cc-9578-b1b72443ae60 · outbound

This paper cites Classifier-free diffusion guidance, 2022.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Classifier-free diffusion guidance, 2022

Reference 22

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Observation 5e575a87-8760-485c-84e0-f4974b0b9dfd · outbound

This paper cites High- resolution image synthesis with latent diffusion models.

Prediction with Action: Visual Policy Learning via Joint Denoising Process High- resolution image synthesis with latent diffusion models

Reference 23

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Observation 93b8c06e-b057-4a63-a9bf-408c09df038b · outbound

This paper cites Multi layer perceptron.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Multi layer perceptron

Reference 24

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Observation 8c375d52-65ed-4e6a-8425-9b68913506b3 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Learning transferable visual models from natural language supervision

Reference 25

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Observation b16e038f-9316-448d-9657-71b22a904568 · outbound

This paper cites Instructpix2pix: Learning to follow image editing instructions.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Instructpix2pix: Learning to follow image editing instructions

Reference 26

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Observation 1655020a-1f5f-4382-8ab7-52e3e1b95245 · outbound

This paper cites SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning.

Prediction with Action: Visual Policy Learning via Joint Denoising Process SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning

Reference 27

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Observation 45d943bc-e6c9-4f35-827b-b1916bce0044 · outbound

This paper cites FMB: a Functional Manipulation Benchmark for Generalizable Robotic Learning.

Prediction with Action: Visual Policy Learning via Joint Denoising Process FMB: a Functional Manipulation Benchmark for Generalizable Robotic Learning

Reference 28

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Observation c7fc5c3f-138e-414f-bd2c-9b081481cfb3 · outbound

This paper cites Scaling up and distilling down: Language-guided robot skill acquisition, 2023.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Scaling up and distilling down: Language-guided robot skill acquisition, 2023

Reference 29

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Observation bd07d9d1-b4dd-43f8-a1ad-43c1eb579ac5 · outbound

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

Prediction with Action: Visual Policy Learning via Joint Denoising Process RT-1: Robotics Transformer for Real-World Control at Scale

Reference 30

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Observation 15f5f168-337f-47cf-9d6a-adb9edd68878 · outbound

This paper cites Film: Visual reasoning with a general conditioning layer.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Film: Visual reasoning with a general conditioning layer

Reference 31

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Observation 55c943f5-21b1-4500-9e9b-7e9bc9ebf266 · outbound

This paper cites Efficientnet: Rethinking model scaling for convolutional neural networks.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Efficientnet: Rethinking model scaling for convolutional neural networks

Reference 32

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source=pdf_text observed=2026-08-12T11:29:20.705150Z digest=sha256:6d8c4e3043d3ff44f2e4ef34fd1181d27b44b215dd4811d51c2ffd1bcd190690

Observation 41614331-65d7-47e0-8eeb-976ab87d2f51 · outbound

This paper cites RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.

Prediction with Action: Visual Policy Learning via Joint Denoising Process RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Reference 33

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source=pdf_text observed=2026-08-12T11:29:20.708898Z digest=sha256:05af6ced7787c71fdb7b5999f8140d2e956f9269573ea4fd45596d1c2db4e898

Observation 755852d8-1053-40ba-9357-44f6a63d1953 · outbound

This paper cites Palm: Scaling language modeling with pathways.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Palm: Scaling language modeling with pathways

Reference 34

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source=pdf_text observed=2026-08-12T11:29:20.712412Z digest=sha256:cacaaf253a692d398ba70ed2e342460f943ee123a43871dea6fb43a1af04191a

Observation b500d4ec-a4cd-4504-889f-c2dcda23e3f6 · outbound

This paper cites Instructblip: Towards general-purpose vision-language models with instruction tuning.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Instructblip: Towards general-purpose vision-language models with instruction tuning

Reference 35

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source=pdf_text observed=2026-08-12T11:29:20.716083Z digest=sha256:4e2c13ca6f5844ba6810030733b67a260f8ca678bd94aa591ffa95160f5be061

Observation bd838d31-02a8-4f88-81ed-97fcc3245524 · outbound

This paper cites Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Unleashing Large-Scale Video Generative Pre-training for Visual Robot Manipulation

Reference 36

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source=pdf_text observed=2026-08-12T11:29:20.719325Z digest=sha256:e823fef8066e6ce9d6de42912a5d8a7606102d9eebf2402cc2bce56eb920a94e

Observation 48596e04-6537-455d-803f-bb48626b0622 · outbound

This paper cites Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

Reference 37

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source=pdf_text observed=2026-08-12T11:29:20.723008Z digest=sha256:99b0a1d510a4de58659bbf8eea00968ab79d1c39c5135125b6e98841616d7b88

Observation d4584387-b0e2-4f57-8ada-eed853707731 · outbound

This paper cites Code as Policies: Language Model Programs for Embodied Control.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Code as Policies: Language Model Programs for Embodied Control

Reference 38

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source=pdf_text observed=2026-08-12T11:29:20.726889Z digest=sha256:ff20f094cf9085afac64ffa704e1c3b780e3d779ff4213deee7474620208290d

Observation fdbfb695-8ba9-4402-84e4-bce1701536ec · outbound

This paper cites Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language

Reference 39

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source=pdf_text observed=2026-08-12T11:29:20.730616Z digest=sha256:e66224d913693b0361a73e982b2e024699b543f019d3e52316810db114ce3290

Observation b998d062-2710-4df1-bbf7-d80a1be32333 · outbound

This paper cites Inner Monologue: Embodied Reasoning through Planning with Language Models.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Inner Monologue: Embodied Reasoning through Planning with Language Models

Reference 40

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source=pdf_text observed=2026-08-12T11:29:20.734847Z digest=sha256:6ffcda547166a1da3e42daf680498b572b75d0ca9bf7ac538f077c925e4d54c3

Observation 5f0cd23d-b2a8-493b-89b3-3ca98376281d · outbound

This paper cites DoReMi: Grounding Language Model by Detecting and Recovering from Plan-Execution Misalignment.

Prediction with Action: Visual Policy Learning via Joint Denoising Process DoReMi: Grounding Language Model by Detecting and Recovering from Plan-Execution Misalignment

Reference 41

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source=pdf_text observed=2026-08-12T11:29:20.739044Z digest=sha256:e2ba05dd76952c24142b0893934899fa0590e97a53ed36a7bceab3be755a8338

Observation 264fe497-bc54-4a2b-8432-c27a5570a00a · outbound

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

Prediction with Action: Visual Policy Learning via Joint Denoising Process Bc-z: Zero-shot task generalization with robotic imitation learning

Reference 42

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source=pdf_text observed=2026-08-12T11:29:20.742824Z digest=sha256:fa2311e5deccb3e7fea8f52c86fdc370352506ef3f671606658fe66fa3ba64e9

Observation 1931e021-98f0-407a-81c2-8df0a3e07464 · outbound

This paper cites HiRT: Enhancing Robotic Control with Hierarchical Robot Transformers.

Prediction with Action: Visual Policy Learning via Joint Denoising Process HiRT: Enhancing Robotic Control with Hierarchical Robot Transformers

Reference 43

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source=pdf_text observed=2026-08-12T11:29:20.746202Z digest=sha256:0adea1db70098b0364306b22b1c6bf738faafd11543ddc03ec5c419c4292a8b5

Observation 4e81c6ea-fd47-40e0-a278-1aa75d290ea0 · outbound

This paper cites Prompt a Robot to Walk with Large Language Models.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Prompt a Robot to Walk with Large Language Models

Reference 44

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source=pdf_text observed=2026-08-12T11:29:20.749487Z digest=sha256:e057d1d3b05cb8894881509427055ec50c4c705774ad2115633d3421d62ab20f

Observation 279ab893-ed02-40a0-b88f-c5b3ee27c670 · outbound

This paper cites R3M: A Universal Visual Representation for Robot Manipulation.

Prediction with Action: Visual Policy Learning via Joint Denoising Process R3M: A Universal Visual Representation for Robot Manipulation

Reference 45

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source=pdf_text observed=2026-08-12T11:29:20.752928Z digest=sha256:78a6b7917f11cb78864af68cf261490c70287b82a4d42cc2c34a805441b34ce5

Observation 24562973-8938-4d63-8ed1-5de83dc3ded8 · outbound

This paper cites VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training.

Prediction with Action: Visual Policy Learning via Joint Denoising Process VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training

Reference 46

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source=pdf_text observed=2026-08-12T11:29:20.756605Z digest=sha256:888074a6f473e19ca083aac58f96045655c071174b6711fb9ee67eac9f99d999

Observation d7408a31-9210-49bd-ac35-3c83c9ce7e50 · outbound

This paper cites Where are we in the search for an artificial visual cortex for embodied intelligence? Advances in Neural Information Processing Systems, 36, 2024.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Where are we in the search for an artificial visual cortex for embodied intelligence? Advances in Neural Information Processing Systems, 36, 2024

Reference 47

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raw_fallback, observed 2026-08-12T11:29:21.217240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T11:29:20.760265Z digest=sha256:71302759bdd6354647d59ebe445fef25ef6be969b0728cadfa2537f2b432520a

Observation 8e73faa9-cc1f-4579-a4ec-45c958e8d2b5 · outbound

This paper cites Eureka: Human-Level Reward Design via Coding Large Language Models.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Eureka: Human-Level Reward Design via Coding Large Language Models

Reference 48

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source=pdf_text observed=2026-08-12T11:29:20.763668Z digest=sha256:ef86c811a9d923ac29906e2325a38c9cc7c397ef5f72c15651d6fd67140b40ba

Observation 4c39980e-f001-4fd0-9d07-c127bd37f21e · outbound

This paper cites Minedojo: Building open-ended embodied agents with internet-scale knowledge.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Minedojo: Building open-ended embodied agents with internet-scale knowledge

Reference 49

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source=pdf_text observed=2026-08-12T11:29:20.769766Z digest=sha256:30887cfbd7ef4640452c39cce052e3c5e3f4b82217073eaf614c795f4e336614

Observation 6972ca1b-3145-46fd-a1b4-adab25b4be9c · outbound

This paper cites Language Reward Modulation for Pretraining Reinforcement Learning.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Language Reward Modulation for Pretraining Reinforcement Learning

Reference 50

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source=pdf_text observed=2026-08-12T11:29:20.773512Z digest=sha256:5a39fdc8461fb17d3ab9d8f17907a6f6c21cbb20316604ab0a472768e1b514ea

Observation 5b3ff525-6013-4b25-a2ec-54b64858a4d8 · outbound

This paper cites Dall-e-bot: Introducing web-scale diffusion models to robotics.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Dall-e-bot: Introducing web-scale diffusion models to robotics

Reference 51

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T11:29:20.777963Z digest=sha256:ce776d3801f8d62eb4f949af4952c68cec505b9c753f3ab7c715575366ced51a

Observation 29a6ec42-1bf5-42eb-af05-74ca6a065aa5 · outbound

This paper cites Planning with Diffusion for Flexible Behavior Synthesis.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Planning with Diffusion for Flexible Behavior Synthesis

Reference 52

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source=pdf_text observed=2026-08-12T11:29:20.782117Z digest=sha256:982ade83864bbe73b7fa953da421c9fd6ca5405b2bc7a9f44ed3b5c64a61b646

Observation 5280fc94-d74a-4b0d-9e14-d9be48b7783f · outbound

This paper cites Is Conditional Generative Modeling all you need for Decision-Making?.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Is Conditional Generative Modeling all you need for Decision-Making?

Reference 53

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source=pdf_text observed=2026-08-12T11:29:20.786608Z digest=sha256:28b4940bc89359db0f5d11924a47c7f62a5bfe6d0bccefd7249ecc855544c116

Observation 308bab4d-6123-453d-ad4d-a7b1df5dfa8a · outbound

This paper cites Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning

Reference 54

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source=pdf_text observed=2026-08-12T11:29:20.790685Z digest=sha256:84a862ca4c293d152a144aea2ea1f97eccbce91f74ddd16dc63dac88ff87d389

Observation c5c44b8d-d245-4b3b-8f6f-4fd2386b5683 · outbound

This paper cites Se (3)-diffusionfields: Learning smooth cost functions for joint grasp and motion optimization through diffusion.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Se (3)-diffusionfields: Learning smooth cost functions for joint grasp and motion optimization through diffusion

Reference 55

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source=pdf_text observed=2026-08-12T11:29:20.795025Z digest=sha256:10cf563c6a4c718d4d15885fa4c6bde8e7aa1870b12a052976a4168efe13b57a

Observation 07888bb4-5c03-4df2-9754-ef8575783af3 · outbound

This paper cites GenAug: Retargeting behaviors to unseen situations via Generative Augmentation.

Prediction with Action: Visual Policy Learning via Joint Denoising Process GenAug: Retargeting behaviors to unseen situations via Generative Augmentation

Reference 56

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source=pdf_text observed=2026-08-12T11:29:20.798889Z digest=sha256:9374692bd33e3b8ec5f26525858a2f623b4f5880b07926eca11adf14768be5e4

Observation 33204804-9bfb-45b3-b340-e776c7917fb7 · outbound

This paper cites Scaling Robot Learning with Semantically Imagined Experience.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Scaling Robot Learning with Semantically Imagined Experience

Reference 57

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source=pdf_text observed=2026-08-12T11:29:20.803154Z digest=sha256:3c4154a6facc50e6cd2acf39703b0df98dbc7209f25e70e25df5ddcf1ff3e6e8

Observation 54643f13-8b79-4a13-b220-0d959e9544d3 · outbound

This paper cites CACTI: A Framework for Scalable Multi-Task Multi-Scene Visual Imitation Learning.

Prediction with Action: Visual Policy Learning via Joint Denoising Process CACTI: A Framework for Scalable Multi-Task Multi-Scene Visual Imitation Learning

Reference 58

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source=pdf_text observed=2026-08-12T11:29:20.807234Z digest=sha256:c6ce59e80ca1fa41f8bdc36fd28fe58b8eb4b6d180868a1898be74dbe5c5b283

Observation 8b29f73e-c322-42f7-821e-e3add3b30a2f · outbound

This paper cites Output Decoder.

Prediction with Action: Visual Policy Learning via Joint Denoising Process Output Decoder

Reference 59

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verified fuzzy
raw_fallback, observed 2026-08-12T11:29:21.178802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T11:29:20.811592Z digest=sha256:2aac901e1e9d2423cba10a60764ed718dc3e5c7c8fa8864c03aa6c36891d31ed

Pith citing papers

Observation 90af2f4f-1696-482c-84af-1a7fd36358b2 · inbound

UP-VLA: A Unified Understanding and Prediction Model for Embodied Agent cites this paper.

UP-VLA: A Unified Understanding and Prediction Model for Embodied Agent Prediction with Action: Visual Policy Learning via Joint Denoising Process

Reference 13

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source=pdf_text observed=2026-08-09T22:13:14.907035Z digest=sha256:98bb2dc405fc8350834ad3f289abb261a27f2339c2858e8a0f9c42d5564e707f

Observation 1202615c-7b2a-4fb4-ae69-df1faa8315fa · inbound

ReconVLA: Reconstructive Vision-Language-Action Model as Effective Robot Perceiver cites this paper.

ReconVLA: Reconstructive Vision-Language-Action Model as Effective Robot Perceiver Prediction with Action: Visual Policy Learning via Joint Denoising Process

Reference 17

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source=arxiv_source observed=2026-08-05T20:32:43.779814Z digest=sha256:b03504df69eb73b354def4292b524dd19541cf5a329eb5884cc9857bfde31cee

Observation ad23fce4-1b03-4782-a739-fc99ec48abce · inbound

VLM4VLA: Revisiting Vision-Language-Models in Vision-Language-Action Models cites this paper.

VLM4VLA: Revisiting Vision-Language-Models in Vision-Language-Action Models Prediction with Action: Visual Policy Learning via Joint Denoising Process

Reference 9

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source=pdf_text observed=2026-08-03T12:30:33.785468Z digest=sha256:e0a44ddc0c0a6f78bd54445db62f34131b9a3b91403798c48ae35e94fad60984

Observation e34fe61f-4da2-483a-8fa6-89df1dea2c80 · inbound

From Video to Control: A Survey of Learning Manipulation Interfaces from Temporal Visual Data cites this paper.

From Video to Control: A Survey of Learning Manipulation Interfaces from Temporal Visual Data Prediction with Action: Visual Policy Learning via Joint Denoising Process

Reference 39

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arxiv_id, observed 2026-05-13T17:03:01.185237Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-13T17:02:18.358675Z digest=sha256:9d2af590059cfc36a77fb686ac949df8627677ad54547ff7b05dd6080c45300d

Observation 776906c3-a569-4d81-bd73-e67635b3c252 · inbound

World Action Models: The Next Frontier in Embodied AI cites this paper.

World Action Models: The Next Frontier in Embodied AI Prediction with Action: Visual Policy Learning via Joint Denoising Process

Reference 25

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arxiv_id, observed 2026-05-13T05:02:17.923754Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-13T05:01:16.802019Z digest=sha256:caf895f1891681995f6a00d1f65aac1dec51967837e1a03032ab8943690cbfd0

Observation e2a8181f-4b2c-4ba0-b5fb-f79447ce3a85 · inbound

Robotic Policy Adaptation via Weight-Space Meta-Learning cites this paper.

Robotic Policy Adaptation via Weight-Space Meta-Learning Prediction with Action: Visual Policy Learning via Joint Denoising Process

Reference 26

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arxiv_id, observed 2026-07-02T18:57:17.162654Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-27T21:43:30.625293Z digest=sha256:54d3cdb951a89ffee704d9e056ef9f5bccddae07cc69834e223ef4e762c27bad