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Paper Citation Record · LEDGER

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models

As of 12 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2608.06799.

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

pith.paper-citation-record.v1
2608.06799 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:41:43.912335Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

29 of 29 outbound references displayed

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External citation measurements

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Outbound references

Observation c0ab036a-f408-45a3-84df-45276b015293 · outbound

This paper cites Ctrl-World: A Controllable Generative World Model for Robot Manipulation.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Ctrl-World: A Controllable Generative World Model for Robot Manipulation

Reference 4

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Observation ff021cfc-2268-44d6-ab40-4170ef71fb38 · outbound

This paper cites World Models.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models World Models

Reference 5

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source=pdf_text observed=2026-08-10T20:41:43.810581Z digest=sha256:ace06545a61070f1792a5fc9d6871fd7c49119df9ac6f04dcf5bfa571fb3bbaf

Observation 3b91ce94-53c9-4e2e-976c-7b955099b888 · outbound

This paper cites World Model for Robot Learning: A Comprehensive Survey.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models World Model for Robot Learning: A Comprehensive Survey

Reference 7

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source=pdf_text observed=2026-08-10T20:41:43.819932Z digest=sha256:5fdd36c31a491595d07cd6a30b363db9f3d98a32d0ebbb6802eada4b2817d5a7

Observation dcd1afdb-0f74-4bc3-9709-a984eff04d8b · outbound

This paper cites GAIA-1: A Generative World Model for Autonomous Driving.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models GAIA-1: A Generative World Model for Autonomous Driving

Reference 8

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source=pdf_text observed=2026-08-10T20:41:43.824533Z digest=sha256:c5b2b70efe073229ffbf19c0fa0e302def86fe28e0d6e2eccaecb8a6d74fe91c

Observation 5f92cb20-abac-4f4a-8b4b-aac060782734 · outbound

This paper cites PAIWorld: A 3D-Consistent World Foundation Model for Robotic Manipulation.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models PAIWorld: A 3D-Consistent World Foundation Model for Robotic Manipulation

Reference 9

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source=pdf_text observed=2026-08-10T20:41:43.829126Z digest=sha256:6000a9c2fd789240fbd1bfb3cbc871d7455326da61588db77255bd98e42fbb7d

Observation 1fc97768-26d9-43a6-be44-ef0a5a4f0c8e · outbound

This paper cites Robots pre-train robots: Manipulation-centric robotic representation from large-scale robot datasets.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Robots pre-train robots: Manipulation-centric robotic representation from large-scale robot datasets

Reference 10

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source=pdf_text observed=2026-08-10T20:41:43.833447Z digest=sha256:65afd24d219d5ec106559cb7a62c32639607c42317c6b8975fa2b8a1fcf38a40

Observation 7ea2f6d8-a26b-4621-8ca7-0e96105cb8e0 · outbound

This paper cites Contrastive Representation Regularization for Vision-Language-Action Models.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Contrastive Representation Regularization for Vision-Language-Action Models

Reference 11

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source=pdf_text observed=2026-08-10T20:41:43.838078Z digest=sha256:4ba46ed13b1e81568e92adbaac4566916c0c5bafcffb848c89bec7fd64160ba5

Observation af3f1281-6c88-4867-b91b-fddb33a74a6e · outbound

This paper cites Predictive but Not Plannable: RC-aux for Latent World Models.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Predictive but Not Plannable: RC-aux for Latent World Models

Reference 12

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source=pdf_text observed=2026-08-10T20:41:43.842384Z digest=sha256:6d379e445678f699d47186a7a315b0712e4115f36d74162283656bda877c78e3

Observation 2bb77745-38f2-4b85-b1d7-189a61b52d8a · outbound

This paper cites Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Genie Envisioner: A Unified World Foundation Platform for Robotic Manipulation

Reference 13

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source=pdf_text observed=2026-08-10T20:41:43.846637Z digest=sha256:0d8f08019e9b8dc5db4a1a13a1f9224faae498fc475fb71513c4bc7de2097a7e

Observation 51beead7-cf0f-4c5a-bc12-9285f117fa83 · outbound

This paper cites LDA-1B: Scaling Latent Dynamics Action Model via Universal Embodied Data Ingestion.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models LDA-1B: Scaling Latent Dynamics Action Model via Universal Embodied Data Ingestion

Reference 14

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source=pdf_text observed=2026-08-10T20:41:43.851098Z digest=sha256:6db77910f998c41e239093406756ec5fbccf8375953c47a157e161836db5054d

Observation aedfe381-ac0e-4ae4-9857-f3162503142e · outbound

This paper cites LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels

Reference 15

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source=pdf_text observed=2026-08-10T20:41:43.855678Z digest=sha256:8037abe4d5c74b8bb1cde4f5bf23950107434a9d1e95d6c86e8b8013d4be9bb4

Observation 643e5636-e55b-4e10-bad6-760151b930b4 · outbound

This paper cites V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning

Reference 16

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source=pdf_text observed=2026-08-10T20:41:43.859391Z digest=sha256:b3f324d22d59def4eaafd68a5ff7846c831787bc9bc440f6e23af35f8a82a1a0

Observation 67a071b4-b42c-4f8a-adcc-b42a81e085d4 · outbound

This paper cites Latent Geometry Beyond Search: Amortizing Planning in World Models.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Latent Geometry Beyond Search: Amortizing Planning in World Models

Reference 17

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local_arxiv, observed 2026-08-10T20:41:44.410479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:41:43.863650Z digest=sha256:5966b1bdfe13eefc143b5381bd583560fe99320e44d9e6875fdc52400e26a959

Observation 10945e6d-0db1-408e-b76b-d182625c2ba1 · outbound

This paper cites LARY: A Latent Action Representation Yielding Benchmark for Generalizable Vision-to-Action Alignment.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models LARY: A Latent Action Representation Yielding Benchmark for Generalizable Vision-to-Action Alignment

Reference 18

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source=pdf_text observed=2026-08-10T20:41:43.867336Z digest=sha256:bec136c078110d51ae9bf117bdd800f3de107a08fc2137725a7b80a49287d9e7

Observation ec375ccf-128a-4bf5-a12b-5cc8b3c77bcf · outbound

This paper cites Reconstruction or Semantics? What Makes a Latent Space Useful for Robotic World Models.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Reconstruction or Semantics? What Makes a Latent Space Useful for Robotic World Models

Reference 19

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Observation 2efa1da1-fa8e-4df0-a553-911bd1a2e13f · outbound

This paper cites OGBench: Benchmarking offline goal-conditioned RL.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models OGBench: Benchmarking offline goal-conditioned RL

Reference 20

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 8c808325-6709-4310-8b71-c8b8d37aec99 · outbound

This paper cites an unresolved cited work.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Unresolved cited work

Reference 21

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source=pdf_text observed=2026-08-10T20:41:43.880350Z digest=sha256:3e87371aabcf861c01c9ce9c110f0ea3c5306f0b6a8005424b3aaa84d710ed2a

Observation 5ab9f07f-3493-4110-82c5-0dec7157c14d · outbound

This paper cites GigaWorld-0: World models as data engine to empower embodied AI.arXiv preprint arXiv:2511.19861,.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models GigaWorld-0: World models as data engine to empower embodied AI.arXiv preprint arXiv:2511.19861,

Reference 22

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Observation fa3a742b-7e23-4cc6-bc98-485f524eae8d · outbound

This paper cites GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models GigaWorld-1: A Roadmap to Build World Models for Robot Policy Evaluation

Reference 23

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T20:41:43.888041Z digest=sha256:f7d2b4846f8d06c2ac2aec8cd1bdb374766bbad0bd3e54c2777b17d377231df4

Observation 100d3085-3228-4b68-934e-1b92b13bcb18 · outbound

This paper cites Beyond language modeling: An exploration of multimodal pretraining.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Beyond language modeling: An exploration of multimodal pretraining

Reference 24

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Observation b2b4d677-4f69-4894-89b2-530598783472 · outbound

This paper cites Open-world hand-object interaction video generation based on structure and contact-aware representation.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Open-world hand-object interaction video generation based on structure and contact-aware representation

Reference 25

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Observation fd1f48ef-37a7-4918-ab92-6647f9a4f302 · outbound

This paper cites UniDriveDreamer: A single-stage multimodal world model for autonomous driving.arXiv preprint arXiv:2602.02002,.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models UniDriveDreamer: A single-stage multimodal world model for autonomous driving.arXiv preprint arXiv:2602.02002,

Reference 26

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source=pdf_text observed=2026-08-10T20:41:43.899958Z digest=sha256:5de00bc8c008d0aa68703be716950837154528179a1a087c07df8fd1ed668b16

Observation a6211a8a-2fbd-4454-aef9-41f3e0c4ef1e · outbound

This paper cites FlowVLA: Visual chain of thought-based motion reasoning for vision-language-action models.arXiv preprint arXiv:2508.18269,.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models FlowVLA: Visual chain of thought-based motion reasoning for vision-language-action models.arXiv preprint arXiv:2508.18269,

Reference 27

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source=pdf_text observed=2026-08-10T20:41:43.904159Z digest=sha256:1422b90c9238d31775479592d3d342df504168eda4033321e18cd4e44d435db7

Observation 4de75839-f51f-4d07-8fc8-2261a689b7ea · outbound

This paper cites DualCoT-VLA: Visual-linguistic chain of thought via parallel reasoning for vision-language-action models.arXiv preprint arXiv:2603.22280,.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models DualCoT-VLA: Visual-linguistic chain of thought via parallel reasoning for vision-language-action models.arXiv preprint arXiv:2603.22280,

Reference 28

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Observation 45e2f42a-1cc4-4f11-9eae-04f23fe607f5 · outbound

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

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning

Reference 29

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source=pdf_text observed=2026-08-10T20:41:43.912335Z digest=sha256:51e5912594267752ef93cdd7b8d89c4d356473f5ebcdaa3707c78a48e11ee5ba

Observation b57a9edb-0419-45a3-ae8c-8411cb48279c · outbound

This paper cites Mastering Diverse Domains through World Models.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Mastering Diverse Domains through World Models

Reference 2019

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source=pdf_text observed=2026-08-10T20:41:43.815090Z digest=sha256:ae336760c87dd961214428d8b3c7636f6e3ca47466966bfef351d0f2e2689ff4

Observation cec43895-c873-4d31-8f07-e2c3850ce7af · outbound

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

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 2023

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source=pdf_text observed=2026-08-10T20:41:43.793178Z digest=sha256:60b4133d53331c3af7bf1196624c0d2c0b4524b2bc2e26bf8837149f837d08ca

Observation bfdf302f-39df-4e2f-a3ec-b7a8a32bc3f2 · outbound

This paper cites Why ai systems don’t learn and what to do about it: Lessons on autonomous learning from cognitive science.arXiv preprint arXiv:2603.15381,.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Why ai systems don’t learn and what to do about it: Lessons on autonomous learning from cognitive science.arXiv preprint arXiv:2603.15381,

Reference 2025

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source=pdf_text observed=2026-08-10T20:41:43.797534Z digest=sha256:841627ecad6fdc8c55ac8f8bcd55112745790e0ae6e4f630bc600d323b08d9c4

Observation faa62ea0-a425-480d-a657-9e928ba511f5 · outbound

This paper cites Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation.

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation

Reference 2026

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Pith citing papers

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