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Paper Citation Record · LEDGER

Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 26 inbound Pith citation observations for arXiv:2402.03570.

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

pith.paper-citation-record.v1
2402.03570 v4

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 26 of 26 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 26 of 26 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:06:56.503880Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T18:38:49.868506Z

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Outbound references

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Pith citing papers

Observation eb909b73-411c-4477-a347-0981a386aa69 · inbound

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

DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 12

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arxiv_id, observed 2026-05-17T16:06:09.642012Z

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

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Observation dfe80ac4-ac1b-4b8f-ae54-8c4ecb2dd705 · inbound

SimuDICE: Offline Policy Optimization Through World Model Updates and DICE Estimation cites this paper.

SimuDICE: Offline Policy Optimization Through World Model Updates and DICE Estimation Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 6

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source=pdf_text observed=2026-08-11T19:42:10.215013Z digest=sha256:669400c89c8e620d250bbdac6589410020e2adb368f43abb160002db1b967370

Observation 5481f156-04b8-48e8-a82e-f270de850db1 · inbound

Cosmos World Foundation Model Platform for Physical AI cites this paper.

Cosmos World Foundation Model Platform for Physical AI Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 34

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arxiv_id, observed 2026-05-10T23:38:45.413511Z

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=2026-05-10T23:38:44.933410Z digest=sha256:22173ee02a9b1f932104b8a8ab5b8cee5fede49b4b2558d8d7d02b94a2000a25

Observation 784fb369-0c64-4b7e-b7b7-1910c5878b8a · inbound

From Screens to Scenes: A Survey of Embodied AI in Healthcare cites this paper.

From Screens to Scenes: A Survey of Embodied AI in Healthcare Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 69

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Observation 1d1d9553-6e06-4d27-b252-7ec666c76385 · inbound

GLAM: Global-Local Variation Awareness in Mamba-based World Model cites this paper.

GLAM: Global-Local Variation Awareness in Mamba-based World Model Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 8

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source=arxiv_source observed=2026-08-10T17:46:12.785615Z digest=sha256:850c22a3f8dbfc82da6624a7340f9e369dc2a7f614e2cdd23ceea6853d716ed6

Observation 10015882-0fd2-4026-a555-857b31e032b5 · inbound

Efficient Online Reinforcement Learning for Diffusion Policy cites this paper.

Efficient Online Reinforcement Learning for Diffusion Policy Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 7

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no resolver link, observed 2026-08-09T19:28:41.729656Z

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source=arxiv_source observed=2026-08-09T19:28:41.729656Z digest=sha256:3cb53c30fcf3718e2ccac3ce4338ef36163269cba6258d31af81eedb5b5ed493

Observation 5bc01a3b-00f9-4a54-837c-210713bbf508 · inbound

Exploratory Diffusion Model for Unsupervised Reinforcement Learning cites this paper.

Exploratory Diffusion Model for Unsupervised Reinforcement Learning Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 16

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source=pdf_text observed=2026-08-08T13:21:18.199380Z digest=sha256:b500f85e85eb5d73e62bfbe2e3a3bbc8a5bb0d97064e1224f1280eff2876bba4

Observation 9663e929-9b0a-4cd9-83b4-1766451ae060 · inbound

Pre-Trained Video Generative Models as World Simulators cites this paper.

Pre-Trained Video Generative Models as World Simulators Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 5

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source=pdf_text observed=2026-08-08T15:14:22.320381Z digest=sha256:6e615373f8732f50cdeae4927f8d93020f86c43cbd1580deb87bbcca2dfb0c0d

Observation 2cc82fa3-362c-45a0-b8e8-78bc5f4d8457 · inbound

LaDi-WM: A Latent Diffusion-based World Model for Predictive Manipulation cites this paper.

LaDi-WM: A Latent Diffusion-based World Model for Predictive Manipulation Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 18

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source=pdf_text observed=2026-08-15T22:06:56.503880Z digest=sha256:bc570f896981110c54fd893ce42c036481d6c5ef7f9e0a838a07e7c5601c2607

Observation ec3fd0cf-ccde-487c-b2c0-01cff93c2db5 · inbound

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning cites this paper.

Extremum Flow Matching for Offline Goal Conditioned Reinforcement Learning Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 37

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Observation 0cb9b6c8-8004-4d55-b48b-b5d0826c2b74 · inbound

VRAG: Learning World Models for Interactive Video Generation cites this paper.

VRAG: Learning World Models for Interactive Video Generation Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 42

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arxiv_id, observed 2026-05-19T12:37:17.620469Z

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=2026-05-19T12:35:19.379364Z digest=sha256:19b40e8efc1face7be08f09424db17e2086ad17530a907e7a13659e99ae87f47

Observation ef7dd789-18bb-4b0b-a5b4-6a2de3b1d5e0 · inbound

VRAG: Learning World Models for Interactive Video Generation cites this paper.

VRAG: Learning World Models for Interactive Video Generation Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 42

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source=pdf_text observed=2026-08-07T13:23:22.919274Z digest=sha256:b5283a9aeefcc465b2d27114dd4ed027510447f70d6bcfbc48f64d6852fd2fa9

Observation 5d634853-c61a-4609-811e-75cbe86336d3 · inbound

BiTrajDiff: Bidirectional Trajectory Generation with Diffusion Models for Offline Reinforcement Learning cites this paper.

BiTrajDiff: Bidirectional Trajectory Generation with Diffusion Models for Offline Reinforcement Learning Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 6

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arxiv_id, observed 2026-05-19T10:52:15.288028Z

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 4b6e551b-05d4-48d6-9ad5-cd889e3e0634 · inbound

Bounding Distributional Shifts in World Modeling through Novelty Detection cites this paper.

Bounding Distributional Shifts in World Modeling through Novelty Detection Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 22

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source=pdf_text observed=2026-08-05T22:58:41.901345Z digest=sha256:1ea538676910e051477de7f19a9d372a155d34010e53826fb725ec24ed514726

Observation 9fcd5bae-c54e-4f23-916d-635a7816e6d8 · inbound

Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges cites this paper.

Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 66

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no resolver link, observed 2026-08-05T21:02:04.280949Z

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source=pdf_text observed=2026-08-05T21:02:04.280949Z digest=sha256:000ec88877a1d577a963e48f5fe755754c5558afd45e00b78849edb9e442abcb

Observation f79ed39c-3d7b-45dc-aa7e-cc6d026a75cc · inbound

DAWM: Diffusion Action World Models for Offline Reinforcement Learning via Action-Inferred Transitions cites this paper.

DAWM: Diffusion Action World Models for Offline Reinforcement Learning via Action-Inferred Transitions Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 4

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arxiv_id, observed 2026-05-18T13:56:26.141866Z

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

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Observation d23c6982-26db-4a8d-a36c-16535e846c9d · inbound

Multimodal Diffusion Forcing for Forceful Manipulation cites this paper.

Multimodal Diffusion Forcing for Forceful Manipulation Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 11

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arxiv_id, observed 2026-05-18T00:35:33.011862Z

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

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Observation e4c54d62-d68a-4209-8ddc-c4cc5f2fa3e0 · inbound

CODA: Coordination via On-Policy Diffusion for Multi-Agent Offline Reinforcement Learning cites this paper.

CODA: Coordination via On-Policy Diffusion for Multi-Agent Offline Reinforcement Learning Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 3

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arxiv_id, observed 2026-05-11T20:36:10.177686Z

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

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Observation 4a838672-b84b-4361-aced-a7c8d2a745a9 · inbound

Probing the Impact of Scale on Data-Efficient, Generalist Transformer World Models for Atari cites this paper.

Probing the Impact of Scale on Data-Efficient, Generalist Transformer World Models for Atari Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 43

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arxiv_id, observed 2026-05-12T08:31:23.898223Z

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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=2026-05-12T01:05:51.150857Z digest=sha256:0361cfa1cee40b8b56418233ca43e6d3c47e365d6b3cdbc6c82ccbcea0eb133a

Observation b0cc1fcd-2855-4509-93ce-e1cd00a1bcee · inbound

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

World Action Models: The Next Frontier in Embodied AI Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 294

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arxiv_id, observed 2026-05-13T05:07:18.065838Z

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

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Observation 17f42931-bd9a-40ca-8494-d56df9487fd1 · inbound

JEDI: Joint Embedding Diffusion World Model for Online Model-Based Reinforcement Learning cites this paper.

JEDI: Joint Embedding Diffusion World Model for Online Model-Based Reinforcement Learning Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 65

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arxiv_id, observed 2026-05-14T19:37:51.804028Z

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

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Observation 75b7c2d8-f505-4e35-99a2-9690f7eceef0 · inbound

Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making cites this paper.

Ada-Diffuser: Latent-Aware Adaptive Diffusion for Decision-Making Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 38

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arxiv_id, observed 2026-05-20T20:59:02.011707Z

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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=2026-05-20T20:54:31.025488Z digest=sha256:3596b30a962279441fba5c363fdc9e3a3024f3a0c69f419bb29fcadeb7b9c0a0

Observation 61835007-ee1a-4549-a599-d3dedcfab53f · inbound

Physically Viable World Models: A Case for Query-Conditioned Embodied AI cites this paper.

Physically Viable World Models: A Case for Query-Conditioned Embodied AI Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 20

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arxiv_id, observed 2026-06-29T09:13:16.546503Z

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

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Observation 9809099f-9fca-4134-804c-a3023d64a216 · inbound

World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications cites this paper.

World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 104

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arxiv_id, observed 2026-06-29T08:43:15.690069Z

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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=2026-06-29T08:36:23.776293Z digest=sha256:ec1cb62c5b4bbd8bdbbe6113214dc45e8421333c5824306cc87c46fb39a0b910

Observation 900df9e9-85d6-4ef6-b97c-4d02ea0f3c04 · inbound

Reversal Q-Learning cites this paper.

Reversal Q-Learning Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 3

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arxiv_id, observed 2026-07-03T18:38:49.871595Z

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

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Observation a92db7f6-e671-4a9c-93bb-e59e10127bcf · inbound

Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL cites this paper.

Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning

Reference 28

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