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Paper Citation Record · LEDGER

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander

As of 19 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 1 inbound Pith citation observation for arXiv:2607.01736.

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

pith.paper-citation-record.v1
2607.01736 v2

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T08:38:45.648794Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T11:36:48.726957Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-10T11:36:51.676038Z

Reference resolution

14 of 14 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved14
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 21ce87ee-30ed-4130-92f4-4131ce4f139c · outbound

This paper cites Machado, Pablo Samuel Castro, and Marc G.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander Machado, Pablo Samuel Castro, and Marc G

Reference 1

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:02d25c2e95b5d05ac1c3efb7791b2b2e7a79589491c5478de2ffcbdb67202093

Observation 051d253a-d598-4357-ae44-b5adb984698b · outbound

This paper cites Deep reinforcement learning in a handful of trials using probabilistic dynamics models.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander Deep reinforcement learning in a handful of trials using probabilistic dynamics models

Reference 2

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:a9e03edb0b3669c638e31035e5d3be00b7de8a1ce35ea585a4f52dc8379f1d66

Observation 23f7a23b-00c0-41c6-b0f4-de1e52b78a47 · outbound

This paper cites Bellemare.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander Bellemare

Reference 3

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:4d3376eeab9f2f39015308dc18ef8f41090eaa8a4d8ba83689487e053a6ee1b1

Observation e07dd83b-05d0-45c5-8159-22b8e5449e54 · outbound

This paper cites Dream to control: Learning behaviors by latent imagination.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander Dream to control: Learning behaviors by latent imagination

Reference 4

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:310db68041e30bb7b81cc9463a9e6b2480473b1ecb53bfe79941ecd117a1d699

Observation 74a1bbb2-93bd-4658-ac01-c0ae1b68ad1a · outbound

This paper cites Learning latent dynamics for planning from pixels.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander Learning latent dynamics for planning from pixels

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:fadb76f03be03c4f913ce8717bfc8b1f866295b12f1b94b372ccd9fcbf88c0b8

Reference 6

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:95cd810014f1d73bd3a820cfb414725a50855b5ce55b68433046c1940edf3f4d

Observation 20d7c5d7-bfe7-4cf0-ae02-ba538ec18ab7 · outbound

This paper cites an unresolved cited work.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander Unresolved cited work

Reference 7

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:88fc0a36021123bd6db96901612fb2affd16c7934787edf0ab6f69b5e5ca0647

Observation 8e8ef13e-e55f-43be-8405-112f50d16101 · outbound

This paper cites Objective mismatch in model-based reinforcement learning.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander Objective mismatch in model-based reinforcement learning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:7f08b7e05d815d2d0b97543cd4b3b9827ad794d44a7e0d4006208fb92cb8ecd9

Observation 03fd11c6-c570-4b62-aac1-da44c254a51a · outbound

This paper cites an unresolved cited work.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander Unresolved cited work

Reference 9

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:c370c4af8ab82a1597d27c89dc15ccb7ef93d3edfecefc18beb370c2dcba19dc

Observation d496d021-ed7d-4df1-9c37-837b28b88181 · outbound

This paper cites Ng, Daishi Harada, and Stuart Russell.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander Ng, Daishi Harada, and Stuart Russell

Reference 10

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:8f3a307d5b9e6f2368156b6306e1450b495895776edbf0ac0cb1e73bbe05e606

Observation 5a82d51c-6318-4cec-80c6-0a3b90c59316 · outbound

This paper cites Rubinstein.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander Rubinstein

Reference 11

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:30faeb27fd023418279c1268cc99aaf6dacb1b6c6ad88507e761e263ca37ef5f

Observation cd967854-56bf-46be-8285-18976c98015f · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:009df35d84338235dcc643062f6eabac624c05fe41a35c766664afb7862e8b4f

Observation 2031dafe-9ebd-4732-afb3-4671ba18291b · outbound

This paper cites Opening the black box: Low-dimensional dynamics in high- dimensional recurrent neural networks.Neural Computation, 25(3):626–649, 2013.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander Opening the black box: Low-dimensional dynamics in high- dimensional recurrent neural networks.Neural Computation, 25(3):626–649, 2013

Reference 13

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:6b94578d3d08453e22c469a020dd4cbf78260bfbd24db6ab8f3e8ef9dc4207d1

Observation a84b1c51-bb7e-4bb4-b695-c97d1faef26f · outbound

This paper cites Johnson, and Sergey Levine.

Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander Johnson, and Sergey Levine

Reference 14

Resolution
unresolved
no resolver link, observed 2026-07-12T08:38:45.648794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T08:38:45.648794Z digest=sha256:cb8f0471b69c9405382ae09d64b4400a5b6e2f2b5ada5d476233940261b76f5c

Pith citing papers

Observation 008d4441-791d-42f3-b497-c5153057757f · inbound

Metric Non-Collapse in Learned World Models for Control: Approximation Theory, Finite-Sample Geometric Guarantees, and Deterministic Planning Transfer cites this paper.

Metric Non-Collapse in Learned World Models for Control: Approximation Theory, Finite-Sample Geometric Guarantees, and Deterministic Planning Transfer Predicting Closed-Loop Performance of Latent World Models: Offline Checkpoint Selection for MPC and Model-Based RL Under Non-Markovian Rewards in LunarLander

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-10T11:36:51.684756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-10T11:36:48.726957Z digest=sha256:6386eaaa32cbc345aee77dfce5038abb233a1db4c92eadba7cd2f0c8591e7c85