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Paper Citation Record · LEDGER

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models

As of 8 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2607.25918.

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

pith.paper-citation-record.v1
2607.25918 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T01:11:13.774961Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

18 of 18 outbound references displayed

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  • unresolved18
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 771a6031-95fa-4f67-87e2-a8eb5c7495b8 · outbound

This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control

Reference 1

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source=pdf_text observed=2026-08-01T01:11:12.643801Z digest=sha256:07cbaeec4fadf1fee977268229da6fa49145d6d8d036439424d85512ce77bfef

Observation 44a525a5-6ad8-420d-b7fc-b262cc13ea1f · outbound

This paper cites LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models

Reference 3

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source=pdf_text observed=2026-08-01T01:11:12.724620Z digest=sha256:4e691e0b493ab9153e5729e72de194ffddba1483fb67661aa700414ce1466c00

Observation d1967c02-21fb-4f4a-a094-7401a79f0487 · outbound

This paper cites Point Tracking Improves World Action Models.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models Point Tracking Improves World Action Models

Reference 6

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source=pdf_text observed=2026-08-01T01:11:12.900982Z digest=sha256:bacc6a719fcda1eaeeb90c5b03190873d91711b09062661fca5b17aebcdff5cf

Observation f759cb84-2386-4846-9935-86dbc41f6038 · outbound

This paper cites CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos

Reference 8

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source=pdf_text observed=2026-08-01T01:11:13.043210Z digest=sha256:279de750825be032ea58d5a4b3024a4f1f385636d6c7864b7b0e96a624caa1f4

Observation 4fb3af46-9844-4937-bbcd-b3cbe7f9d656 · outbound

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

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning

Reference 9

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source=pdf_text observed=2026-08-01T01:11:13.085244Z digest=sha256:bddbed11cba72946855e575b2a069a40969264a2585c304866d336d387de297b

Observation 3ffeb904-e736-4326-8b7e-5362dbde740f · outbound

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

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models OpenVLA: An Open-Source Vision-Language-Action Model

Reference 10

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source=pdf_text observed=2026-08-01T01:11:13.146510Z digest=sha256:fa3047a038161d8194c4bf080ccfa227be1c74ef7a03497dd1eb3d62af247089

Observation d6276561-a2c7-4f6a-9c57-cff77e9f39b3 · outbound

This paper cites Segment Anything.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models Segment Anything

Reference 11

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source=pdf_text observed=2026-08-01T01:11:13.205998Z digest=sha256:67fce9791221f62c31e9dee3283d062b4390b3f47d2b82a556e2e42dadbf5841

Observation 540a39a4-a466-4d27-99a4-952f90a3847f · outbound

This paper cites LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning

Reference 12

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source=pdf_text observed=2026-08-01T01:11:13.270955Z digest=sha256:26f2b4ef9eb7ce5ae1aa1bc4700797339d40d719e112b5bd1db76f346f37d8b5

Observation fa6fcbef-54f8-4666-9d98-31859806c2f3 · outbound

This paper cites OA-WAM: Object-Addressable World Action Model for Robust Robot Manipulation.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models OA-WAM: Object-Addressable World Action Model for Robust Robot Manipulation

Reference 13

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source=pdf_text observed=2026-08-01T01:11:13.343957Z digest=sha256:9328edbe406c0dd381f5b70fad09e743ac7c168ec8d2170a497bb907b3c28365

Observation f2564b36-80ca-4f95-9f6f-d7084664454e · outbound

This paper cites Mask World Model: Predicting What Matters for Robust Robot Policy Learning.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models Mask World Model: Predicting What Matters for Robust Robot Policy Learning

Reference 14

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source=pdf_text observed=2026-08-01T01:11:13.411612Z digest=sha256:09a1660c68e69852f194f5eee8f4de0b5bffe57d75db5068e6974a264eb4738e

Observation 9f4848e4-24f5-48d7-a0d5-51431ecda614 · outbound

This paper cites Wan: Open and Advanced Large-Scale Video Generative Models.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models Wan: Open and Advanced Large-Scale Video Generative Models

Reference 15

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source=pdf_text observed=2026-08-01T01:11:13.471242Z digest=sha256:4d05fdc7631c34112167af794b5319485449de784881e6315a2268c32f280b9a

Observation 7e1e5aeb-e2b5-440a-a5cf-0671109db37b · outbound

This paper cites MaskWAM: Unifying Mask Prompting and Prediction for World-Action Models.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models MaskWAM: Unifying Mask Prompting and Prediction for World-Action Models

Reference 16

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source=pdf_text observed=2026-08-01T01:11:13.569491Z digest=sha256:3ad7d391a0303757292480c46d61db80645c2da69e3b1bbcaebdb1eef2f1cc8d

Observation 4107d791-13a4-4417-b56f-a30e272bfcb9 · outbound

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

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models Fast-WAM: Do World Action Models Need Test-time Future Imagination?

Reference 17

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source=pdf_text observed=2026-08-01T01:11:13.658902Z digest=sha256:32dcdb07dad2f10aa7ea6e2a130fc462bea70b0ba992bbbc30c666a47ebea9e6

Observation a82f0af1-b0bb-4f45-8742-5246783b6c53 · outbound

This paper cites TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policies.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models TraceVLA: Visual Trace Prompting Enhances Spatial-Temporal Awareness for Generalist Robotic Policies

Reference 18

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source=pdf_text observed=2026-08-01T01:11:13.774961Z digest=sha256:e1e1f166c381330c782cc0136317c71ace8c41496cc244fd3e002ef2ff1702ef

Observation b66a5f3c-618c-4a2e-8a7c-28c872ae9a23 · outbound

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

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches

Reference 2023

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source=pdf_text observed=2026-08-01T01:11:12.828429Z digest=sha256:594eef7b2d897261e96bc884067bb05a788b1386637b1d0b9c572f133f947e4e

Observation 380c9f7e-a689-4e1b-b48e-1454cc2021e5 · outbound

This paper cites Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representations.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representations

Reference 2024

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source=pdf_text observed=2026-08-01T01:11:12.974759Z digest=sha256:0cbe036ebfea388cbb3f26fd0393d4d84996dd27ddbcc169a0bcf094805651c2

Observation 02db98bc-4928-478c-a500-7ca6b5be480c · outbound

This paper cites AimBot: A Simple Auxiliary Visual Cue to Enhance Spatial Awareness of Visuomotor Policies.

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models AimBot: A Simple Auxiliary Visual Cue to Enhance Spatial Awareness of Visuomotor Policies

Reference 2025

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source=pdf_text observed=2026-08-01T01:11:12.686720Z digest=sha256:a74a392a19cb4a58c420d280182a8aa9c036691eb57e21c58f25007dee61a942

Observation e9fffaa5-02f1-439e-b9c7-55a144751123 · outbound

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

DC-WAM: Dynamic-Centric Visual Supervision and Reasoning for World-Action Models DreamDojo: A Generalist Robot World Model from Large-Scale Human Videos

Reference 2026

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source=pdf_text observed=2026-08-01T01:11:12.794759Z digest=sha256:3c0d2a648250dc53649052487108771491e5c33e9eb114ca1c951d7d449d2b6b

Pith citing papers

No inbound Pith citation observations are available.