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Paper Citation Record · LEDGER

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

As of 23 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 2026-08-23T06:30:58.430688+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:e7ce97ddfcaa16eaa0c1cc26b2d8c1333bac9fda448e91c6acac0579dbd11727

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:ccb2da50cc6eb95631f4812d2ca71b105efd1aa300709eb25fa490695e7aa972

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:d20eb1f291fd1c403629ec59e9de8ac47c153fde49eb0463eb5f19cec7eddd2d

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=sha256:794e3bfb7f73f99e2fa14906b400aafce4061a50d11699acd22fb8028eb5b036

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=sha256:031467571d661cfe3f276a35233a95b380e3dc77d9b5222f1de97fe47269ed31

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=sha256:1a4cafca1586d153472d1f852858cb726e16ccfac62bfe5f95d52791477d2895

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=sha256:218694d039ac1f8b2923cec3e5ae02090429ec2b33d48009629333dddb8b5306

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=sha256:66858e0380906e638e88c28697299d1eafc3af181c392269658db2554d5ac6b3

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=sha256:1fed5e26d88c23dacb02083d9dabab5da3e0fc907908a9a001faf9fb60f45ed9

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:e4db9f0b4c7c602bc61279b2f2ae76a29fe1df4622bea1566ba7a87d8a439236

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:f8fd5e45e39cead00ff7133f9e80c213c8793e3402f3be0df00cd64fae404064

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=sha256:765d9ba7ec885c010e3991ba286d413cf5ec0a7a70d3c0f84bd3f9e1a55a37f8

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=sha256:7b0367db36339b51fdbbc5c8fb103008477c1675cc3b41a4d6d99f0d7005b111

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=sha256:6059c4487a92ede3724fc59141aef8be178c28b4741eeca38e0ccb9778393555

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:ea06865ca2b3b526d4eea49eb5151ae30ad41ab2f89164eb1bdbf7b91139a554

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:f029baf6b4256a919c29ad4e7eef1d44039da774b197549a7a3e4fdc99c74def

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=sha256:86d797a5515917ad8eb2cf0c0193ef3042801d1bee3e414429429c3a6c7952e8

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=sha256:19f7ca58a3a5973182f7a79f5e6d1d1c26c5d0da657893f81d9912a7c0a587ec

Pith citing papers

No inbound Pith citation observations are available.