Paper Citation Record · LEDGER

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models

As of 18 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2607.23602.

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

pith.paper-citation-record.v1
2607.23602 v1

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-30T17:53:37.024253Z

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

19 of 19 outbound references displayed

verified exact0
verified fuzzy0
unresolved15
parse uncertain0
malformed identifier4
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f33b0dcd-8f67-4e8a-a9a4-a336fe4f6359 · outbound

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

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Diffusion Policy: Visuomotor Policy Learning via Action Diffusion

Reference 5

Resolution: malformed identifier; no resolver link, observed 2026-07-30T17:53:36.941633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0dbc7ce-85a7-43ad-acac-5533bc6b8548 · outbound

This paper cites Beyond the Next Step: Variable-Length Latent World Models for Long-Horizon Planning.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Beyond the Next Step: Variable-Length Latent World Models for Long-Horizon Planning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:36.951134Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebfaa93b-0e97-4499-bb20-e106320544cc · outbound

This paper cites Mastering Diverse Domains through World Models.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Mastering Diverse Domains through World Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:36.966377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59cc62fc-d440-4b63-b43c-70f4f8446f16 · outbound

This paper cites Nathan Lambert, Brandon Amos, Omry Yadan, and Roberto Calandra.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Nathan Lambert, Brandon Amos, Omry Yadan, and Roberto Calandra

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:36.978831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 558f84b6-443a-42c9-a09e-b25fb81dcf0e · outbound

This paper cites Vivek Myers, Bill Chunyuan Zheng, Benjamin Eysenbach, andSergeyLevine.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Vivek Myers, Bill Chunyuan Zheng, Benjamin Eysenbach, andSergeyLevine

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:36.987628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc080992-ec57-4d70-9d2d-b5d554fe735b · outbound

This paper cites OGBench: Benchmarking Offline Goal-Conditioned RL.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models OGBench: Benchmarking Offline Goal-Conditioned RL

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:36.995307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47b7adb7-260c-49c9-acb3-3259ce652961 · outbound

This paper cites Cristina Pinneri, Shambhuraj Sawant, Sebastian Blaes, Jan Achterhold, Joerg Stueckler, Michal Rolinek, and Georg Martius.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Cristina Pinneri, Shambhuraj Sawant, Sebastian Blaes, Jan Achterhold, Joerg Stueckler, Michal Rolinek, and Georg Martius

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:36.998994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a737fef-9670-4c79-a2c4-3a8ccf199a87 · outbound

This paper cites DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:37.024253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 26c3e6ac-74b7-490e-92eb-06d9e201092e · outbound

This paper cites Michael Janner, Justin Fu, Marvin Zhang, and Sergey Levine.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Michael Janner, Justin Fu, Marvin Zhang, and Sergey Levine

Reference 1963

Resolution: malformed identifier; no resolver link, observed 2026-07-30T17:53:36.974642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c07d988-da87-48aa-9982-9b674a73c710 · outbound

This paper cites 25 YuhaiWang,JiaweiXia,RongxuanZhou,XiaoHu,Yongliang Shi, Jing Du, and Yang Ye.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models 25 YuhaiWang,JiaweiXia,RongxuanZhou,XiaoHu,Yongliang Shi, Jing Du, and Yang Ye

Reference 2006

Resolution: malformed identifier; no resolver link, observed 2026-07-30T17:53:37.016172Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea0aba75-447f-4368-b8c0-764fdedc077b · outbound

This paper cites an unresolved cited work.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Unresolved cited work

Reference 2017

Resolution: malformed identifier; no resolver link, observed 2026-07-30T17:53:37.020066Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48dc730f-a830-40cf-9751-30069e7d9dbb · outbound

This paper cites Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:36.946650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 561f9d40-10f3-4a9c-976a-1de9f0a3dd31 · outbound

This paper cites Search on the Replay Buffer: Bridging Planning and Reinforcement Learning.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Search on the Replay Buffer: Bridging Planning and Reinforcement Learning

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:36.955824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63c07340-ea9b-413a-8080-f0e02fd592a9 · outbound

This paper cites Beyond Euclidean Proximity: Repairing Latent World Models with Horizon-Matched Trajectory Reachability Metrics.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Beyond Euclidean Proximity: Repairing Latent World Models with Horizon-Matched Trajectory Reachability Metrics

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:36.983691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8ca8ea04-c621-495c-aa30-8bf3705b57a6 · outbound

This paper cites UniZero: Generalized and Efficient Planning with Scalable Latent World Models.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models UniZero: Generalized and Efficient Planning with Scalable Latent World Models

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:37.004079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6e22c49-a04d-4c08-8f03-07d1586a45cc · outbound

This paper cites Nicklas Hansen, Hao Su, and Xiaolong Wang.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Nicklas Hansen, Hao Su, and Xiaolong Wang

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:36.970044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2c29f64-e791-4a0a-a998-6939adb1345b · outbound

This paper cites Goal-Conditioned Reinforcement Learning with Disentanglement-based Reachability Planning.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models Goal-Conditioned Reinforcement Learning with Disentanglement-based Reachability Planning

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:37.012368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eaf8a61c-ca52-469e-b790-80e328a99196 · outbound

This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:36.928883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbdef916-b3c5-457a-82b3-49cc6fd30ddd · outbound

This paper cites SAGE: Subgoal-Conditioned Action Generation for Latent World Model Planning.

Action from Adjacent Set in Physical Space Outperforms the Best Prediction in World Models SAGE: Subgoal-Conditioned Action Generation for Latent World Model Planning

Reference 2026

Resolution: unresolved; no resolver link, observed 2026-07-30T17:53:36.937914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.