Paper Citation Record · LEDGER

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction

As of 11 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2608.07420.

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

pith.paper-citation-record.v1
2608.07420 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T04:59:30.123195Z

measured 45 of 45 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

45 of 45 outbound references displayed

verified exact2
verified fuzzy9
unresolved34
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 18a55230-a3d0-421e-8626-213ced7f1d97 · outbound

This paper cites DIAMOND: Diffusion for world modeling: Visual details matter in atari.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction DIAMOND: Diffusion for world modeling: Visual details matter in atari

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:59:31.050712Z

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.

Observation bc17e08a-d9e3-4061-b923-471599a71ac0 · outbound

This paper cites Lipschitz Continuity in Model-based Reinforcement Learning.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Lipschitz Continuity in Model-based Reinforcement Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.778982Z

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Observation 8924a219-fff0-48f2-a868-c38026dba62f · outbound

This paper cites Combating the Compounding-Error Problem with a Multi-step Model.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Combating the Compounding-Error Problem with a Multi-step Model

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.801091Z

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Observation ebd0a93a-89f6-4a9e-a688-8d5e9904f08d · outbound

This paper cites an unresolved cited work.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-10T04:59:31.033425Z

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.

Observation 1bf57239-b047-4876-97af-b141bc0ba86b · outbound

This paper cites Multi-timestep models for model-based reinforcement learning, 2024.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Multi-timestep models for model-based reinforcement learning, 2024

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:59:30.920337Z

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.

Observation c9756a44-3dd8-4e7a-b65d-bdea80427dd6 · outbound

This paper cites Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.836826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 509f6108-6320-48dc-97de-017997baafdf · outbound

This paper cites Bengio, P.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Bengio, P

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.842128Z

Source-reported events for the cited work

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Observation c3745dbc-1307-4d3e-8b80-58cec1498792 · outbound

This paper cites Genie: Generative Interactive Environments.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Genie: Generative Interactive Environments

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.852319Z

Source-reported events for the cited work

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Observation c5e39d5e-cb7f-46d8-9686-a160288d0aba · outbound

This paper cites an unresolved cited work.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Unresolved cited work

Reference 9

Resolution: unresolved; raw_fallback, observed 2026-08-10T04:59:30.908698Z

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.

Observation ecf415a8-e5bc-46ec-9d9d-bd1722164bb7 · outbound

This paper cites Diversity is all you need: Learning skills without a reward function, 2018.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Diversity is all you need: Learning skills without a reward function, 2018

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.880604Z

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Observation 8484d6b5-9a5e-4446-807b-24198e626695 · outbound

This paper cites Unsupervised Learning for Physical Interaction through Video Prediction.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Unsupervised Learning for Physical Interaction through Video Prediction

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.907634Z

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Observation 2efd76cf-11c6-4d3f-aa1c-fa2dad9e4eeb · outbound

This paper cites Professor forcing: a new algorithm for training recurrent networks.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Professor forcing: a new algorithm for training recurrent networks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:59:30.892786Z

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

Observation eb109124-017c-4354-bbe8-85b802985da1 · outbound

This paper cites an unresolved cited work.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-10T04:59:30.882635Z

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.

Observation 7ecb51a3-1aed-4ab5-9597-832a27ff0e9e · outbound

This paper cites World Models.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction World Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.931514Z

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Observation b6c6053b-d93f-4d82-a187-7dda275cde1f · outbound

This paper cites Dream to Control: Learning Behaviors by Latent Imagination.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Dream to Control: Learning Behaviors by Latent Imagination

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.945091Z

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Observation 51dbb2c8-847d-467c-ae8a-962a3d5465ea · outbound

This paper cites Learning latent dynamics for planning from pixels.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Learning latent dynamics for planning from pixels

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:59:30.873165Z

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.

Observation 7c28e615-7198-4377-8890-398d25d81af6 · outbound

This paper cites Mastering Atari with Discrete World Models.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Mastering Atari with Discrete World Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.953241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7274d489-584c-40c0-bfbd-c42f85c0de6a · outbound

This paper cites Mastering diverse control tasks through world models.Nature, pages 1–7, 2025.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Mastering diverse control tasks through world models.Nature, pages 1–7, 2025

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.958235Z

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Observation ebd9d996-4f3e-46b1-92c9-ddf6cc0476fb · outbound

This paper cites Temporal Difference Learning for Model Predictive Control.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Temporal Difference Learning for Model Predictive Control

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.962056Z

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Observation 72721181-b42e-46c8-99ea-441da93f5856 · outbound

This paper cites TD-MPC2: Scalable, Robust World Models for Continuous Control.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction TD-MPC2: Scalable, Robust World Models for Continuous Control

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.965750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abff9003-dd0a-4bde-a219-9f6b7aa5e784 · outbound

This paper cites Neural motion simulator pushing the limit of world models in reinforcement learning.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Neural motion simulator pushing the limit of world models in reinforcement learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:59:30.857939Z

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.

Observation 9d8d26ea-6baf-49e8-8124-620a905db362 · outbound

This paper cites Model-Based Planning with Discrete and Continuous Actions.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Model-Based Planning with Discrete and Continuous Actions

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.974197Z

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Unavailable: canonical work link unavailable.

Observation 7f691b9c-6c79-4130-946d-43ddc1ee227f · outbound

This paper cites Efros, and Sergey Levine.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Efros, and Sergey Levine

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:59:30.847048Z

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.

Observation 9c4fb1de-afc7-41ea-8918-e250a9ddf26f · outbound

This paper cites How Far is Video Generation from World Model: A Physical Law Perspective.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction How Far is Video Generation from World Model: A Physical Law Perspective

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.983053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b7357ab-847c-43cf-8f44-66073d45d155 · outbound

This paper cites A path towards autonomous machine intelligence version 0.9.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction A path towards autonomous machine intelligence version 0.9

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.994748Z

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Observation 23986565-173e-4354-ba80-9534289887bd · outbound

This paper cites Smallworlds: Assessing dynamics understanding of world models in isolated environments, 2025.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Smallworlds: Assessing dynamics understanding of world models in isolated environments, 2025

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.006373Z

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Observation ed6be7a9-5a88-49ed-9cb5-05cfc077e36e · outbound

This paper cites Any-step dynamics model improves future predictions for online and offline reinforcement learning.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Any-step dynamics model improves future predictions for online and offline reinforcement learning

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:59:30.830802Z

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.

Observation 2ec7ce6e-adeb-48f1-924e-acc3c9fe2900 · outbound

This paper cites Adm-v2: Pursuing full-horizon roll-out in dynamics models for offline policy learning and evaluation.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Adm-v2: Pursuing full-horizon roll-out in dynamics models for offline policy learning and evaluation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:59:30.819902Z

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.

Observation 040b0d5a-f667-4ab8-bf43-19d833ca7ea7 · outbound

This paper cites From kepler to newton: Inductive biases guide learned world models in transformers.ArXiv, abs/2602.06923, 2026.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction From kepler to newton: Inductive biases guide learned world models in transformers.ArXiv, abs/2602.06923, 2026

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.044258Z

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Unavailable: canonical work link unavailable.

Observation cabdb706-c5ba-4a3b-8755-0ef54ca2c5f3 · outbound

This paper cites Temporal Abstraction in Reinforcement Learning with the Successor Representation.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Temporal Abstraction in Reinforcement Learning with the Successor Representation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.049297Z

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Unavailable: canonical work link unavailable.

Observation 1b3a1c66-b37e-4734-9a9c-7773efe6e0c6 · outbound

This paper cites Transformers are sample-efficient world models.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Transformers are sample-efficient world models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.053548Z

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Observation ba1f3809-9950-45a9-9ba8-fbd27856e298 · outbound

This paper cites On the difficulty of training recurrent neural networks.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction On the difficulty of training recurrent neural networks

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T04:59:30.803658Z

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.

Observation 70d19c9a-ffe3-4741-9a06-b413dd1958bb · outbound

This paper cites FiLM: Visual Reasoning with a General Conditioning Layer.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction FiLM: Visual Reasoning with a General Conditioning Layer

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.061059Z

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Observation 7da57128-7daf-4edd-841f-644a5b705db7 · outbound

This paper cites RoFormer: Enhanced Transformer with Rotary Position Embedding.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction RoFormer: Enhanced Transformer with Rotary Position Embedding

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.067738Z

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Observation 514c3c40-f568-47a9-9d94-a69c2936babe · outbound

This paper cites Dyna, an integrated architecture for learning, planning, and reacting.ACM Sigart Bulletin, 2(4):160–163, 1991.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Dyna, an integrated architecture for learning, planning, and reacting.ACM Sigart Bulletin, 2(4):160–163, 1991

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.071735Z

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Observation 1cefa4cd-3179-4da4-b099-35c19afcc944 · outbound

This paper cites Self-Correcting Models for Model-Based Reinforcement Learning.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Self-Correcting Models for Model-Based Reinforcement Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.075418Z

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Observation c0a12810-1087-447e-8ecc-2f3b50ba2502 · outbound

This paper cites dm_control: Software and tasks for continuous control.Software Impacts, 6:100022, 2020.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction dm_control: Software and tasks for continuous control.Software Impacts, 6:100022, 2020

Reference 37

Resolution: verified exact; arxiv_id_nonexistent, observed 2026-08-10T04:59:30.410235Z

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.

Observation ace92813-913a-4b2f-9108-7604b61f49b8 · outbound

This paper cites Chang, Ashesh Rambachan, and Sendhil Mullainathan.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Chang, Ashesh Rambachan, and Sendhil Mullainathan

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.097929Z

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Observation 3dbc8750-b62b-4341-a41e-fa5a637ac7a4 · outbound

This paper cites Attention Is All You Need.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Attention Is All You Need

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.107081Z

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Observation 00e1ab39-4f77-49cf-88fc-d7169a220c7d · outbound

This paper cites Cloning Deterministic Worlds: The Critical Role of Latent Geometry in Long-Horizon World Models.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Cloning Deterministic Worlds: The Critical Role of Latent Geometry in Long-Horizon World Models

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-08-10T04:59:30.209152Z

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.

Observation 808b15e9-03b9-4a16-a966-7f99c3c59e1a · outbound

This paper cites Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.115031Z

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Observation d7cfc94c-c10d-40a2-9978-d9584051322a · outbound

This paper cites Hierarchical Planning with Latent World Models.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Hierarchical Planning with Latent World Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.119375Z

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Observation 402418ff-d869-4e2e-a0c2-589f9658b771 · outbound

This paper cites Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:30.123195Z

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Observation 9064f369-0960-4a8a-aac1-34655adb0efa · outbound

This paper cites doi: 10.1613/jair.3912.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction doi: 10.1613/jair.3912

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-10T04:59:29.826523Z

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Observation 3ca24311-a5b0-4c36-874a-e56b581dd810 · outbound

This paper cites an unresolved cited work.

Beyond Myopic World Models: Long-Horizon End-to-End Training for Direct Future Prediction Unresolved cited work

Reference 2025

Resolution: unresolved; raw_fallback, observed 2026-08-10T04:59:30.787424Z

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

Pith citing papers

No inbound Pith citation observations are available.