Paper Citation Record · LEDGER

Fully Offline Reinforcement Learning

As of 20 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 2 inbound Pith citation observations for arXiv:2505.22442.

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

pith.paper-citation-record.v1
2505.22442 v3

Coverage vector

measured 83 of 83 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:16:05.159203Z

measured 85 of 85 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:25:39.829506Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T01:48:51.121586Z

Reference resolution

83 of 83 outbound references displayed

verified exact11
verified fuzzy41
unresolved28
parse uncertain0
malformed identifier2
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7f4fa7dd-2576-4833-918f-082dad491144 · outbound

This paper cites Aitchison.

Fully Offline Reinforcement Learning Aitchison

Reference 1

Resolution: verified exact; raw_fallback, observed 2026-08-07T13:16:09.424246Z

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Observation aa23fa33-78ea-43be-ad09-ec04a2ec318a · outbound

This paper cites Alaa and Mihaela van der Schaar.

Fully Offline Reinforcement Learning Alaa and Mihaela van der Schaar

Reference 2

Resolution: metadata mismatch; raw_fallback, observed 2026-08-07T13:16:09.081121Z

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Observation faa3004a-74fb-466a-b59d-28e8b50b6332 · outbound

This paper cites Uncertainty-based offline reinforcement learning with diversified q-ensemble.

Fully Offline Reinforcement Learning Uncertainty-based offline reinforcement learning with diversified q-ensemble

Reference 3

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Source-reported events for the cited work

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Observation 3ad69933-f655-4d69-8dee-5f498d7ff47c · outbound

This paper cites Asymptotically minimax bayes predictive densities.The Annals of Statistics, 34(6):2921–2938, 2006.

Fully Offline Reinforcement Learning Asymptotically minimax bayes predictive densities.The Annals of Statistics, 34(6):2921–2938, 2006

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T13:15:57.474090Z

Source-reported events for the cited work

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Observation 02430707-3cef-41eb-acea-41eedfcd62cc · outbound

This paper cites Augmented world models facilitate zero-shot dynamics generalization from a single offline environment.

Fully Offline Reinforcement Learning Augmented world models facilitate zero-shot dynamics generalization from a single offline environment

Reference 5

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Source-reported events for the cited work

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Observation b48111ec-9df1-470f-b256-4122791e1c06 · outbound

This paper cites Information-theoretic characterization of bayes performance and the choice of priors in parametric and nonparametric problems.

Fully Offline Reinforcement Learning Information-theoretic characterization of bayes performance and the choice of priors in parametric and nonparametric problems

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:21.255216Z

Source-reported events for the cited work

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Observation ab150b87-375f-4aca-b853-765cb9f73e2f · outbound

This paper cites Barron.The Exponential Convergence of Posterior Probabilities with Implications for Bayes Estimators of Density Functions.

Fully Offline Reinforcement Learning Barron.The Exponential Convergence of Posterior Probabilities with Implications for Bayes Estimators of Density Functions

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:20.989180Z

Source-reported events for the cited work

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Observation d16ea67a-4b7d-4dcf-83cb-b64d4ddd1675 · outbound

This paper cites Bass.Real Analysis for Graduate Students, chapter 21.

Fully Offline Reinforcement Learning Bass.Real Analysis for Graduate Students, chapter 21

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:20.820274Z

Source-reported events for the cited work

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Observation 14fff60b-933b-4eff-8483-c0f9dc237f61 · outbound

This paper cites A Tutorial on Meta-Reinforcement Learning.

Fully Offline Reinforcement Learning A Tutorial on Meta-Reinforcement Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T13:15:57.942175Z

Source-reported events for the cited work

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Observation c275b9b1-b9bd-4ad5-a6de-e2c89d65fe86 · outbound

This paper cites A problem in the sequential design of experiments.Sankhy ¯a: The Indian Journal of Statistics (1933-1960), 16(3/4):221–229, 1956.

Fully Offline Reinforcement Learning A problem in the sequential design of experiments.Sankhy ¯a: The Indian Journal of Statistics (1933-1960), 16(3/4):221–229, 1956

Reference 10

Resolution: verified exact; raw_fallback, observed 2026-08-07T13:16:08.501815Z

Source-reported events for the cited work

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Observation 53dbe3be-d34e-4b8f-b8c4-eeae6d108a02 · outbound

This paper cites Dynamic programming and stochastic control processes.Information and Control, 1(3):228–239, 1958.

Fully Offline Reinforcement Learning Dynamic programming and stochastic control processes.Information and Control, 1(3):228–239, 1958

Reference 11

Resolution: malformed identifier; no resolver link, observed 2026-08-07T13:15:58.052512Z

Source-reported events for the cited work

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Observation ad5273c6-cfb0-4297-8b5b-d36395eea30e · outbound

This paper cites Foster, and Daniel M.

Fully Offline Reinforcement Learning Foster, and Daniel M

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:20.427736Z

Source-reported events for the cited work

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Observation 3f3dade5-de7b-468d-8deb-ae49eabbfc43 · outbound

This paper cites On the foundations of statistical inference.Journal of the American Statistical Association, 57(298):269–306, 1962.

Fully Offline Reinforcement Learning On the foundations of statistical inference.Journal of the American Statistical Association, 57(298):269–306, 1962

Reference 13

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Observation 50ccbea6-642b-4c41-abfb-6ccd7d75f62c · outbound

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Fully Offline Reinforcement Learning Unresolved cited work

Reference 14

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Observation de0a4ee4-4b43-46b8-9c14-1c86432ce338 · outbound

This paper cites Bayes adaptive monte carlo tree search for of- fline model-based reinforcement learning, 2024.

Fully Offline Reinforcement Learning Bayes adaptive monte carlo tree search for of- fline model-based reinforcement learning, 2024

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:20.135149Z

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Observation cfe50663-3e99-4113-815f-551afb1c29ee · outbound

This paper cites Conser- vative uncertainty estimation by fitting prior networks.

Fully Offline Reinforcement Learning Conser- vative uncertainty estimation by fitting prior networks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:19.983352Z

Source-reported events for the cited work

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Observation 016295ea-6bda-4420-99f2-2c9d7ae85950 · outbound

This paper cites Clarke and A.R.

Fully Offline Reinforcement Learning Clarke and A.R

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:19.743980Z

Source-reported events for the cited work

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Observation 4ba4c40f-40e6-47f5-a44a-23eb99b56a5f · outbound

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Fully Offline Reinforcement Learning Unresolved cited work

Reference 18

Resolution: verified exact; raw_fallback, observed 2026-08-07T13:16:07.959162Z

Source-reported events for the cited work

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Observation 54158c56-5f57-431f-be73-7a763611224d · outbound

This paper cites Observation of a markov process through a noisy channel.PhD Thesis, 1962.

Fully Offline Reinforcement Learning Observation of a markov process through a noisy channel.PhD Thesis, 1962

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:19.551859Z

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.

Observation d5475ef1-f8d4-4265-9802-3e75ba2d6176 · outbound

This paper cites Fast reinforcement learning via slow reinforcement learning.

Fully Offline Reinforcement Learning Fast reinforcement learning via slow reinforcement learning

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:19.341391Z

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Observation fd95ba64-4cef-4f53-a399-142fcde22945 · outbound

This paper cites PhD thesis, 2002.

Fully Offline Reinforcement Learning PhD thesis, 2002

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:19.101212Z

Source-reported events for the cited work

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Observation b34d3302-8720-46c0-88bf-8404861c1c57 · outbound

This paper cites Bayesian exploration networks.

Fully Offline Reinforcement Learning Bayesian exploration networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:18.931137Z

Source-reported events for the cited work

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Observation af8f42f6-eebf-41e4-a8ed-29b0c9113c05 · outbound

This paper cites D4rl: Datasets for deep data-driven reinforcement learning, 2020.

Fully Offline Reinforcement Learning D4rl: Datasets for deep data-driven reinforcement learning, 2020

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:18.703635Z

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Observation 37eca544-1166-4b74-b6d2-90890599c766 · outbound

This paper cites A minimalist approach to offline reinforcement learn- ing.

Fully Offline Reinforcement Learning A minimalist approach to offline reinforcement learn- ing

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:18.497264Z

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Observation b819815a-87ac-40bc-8d62-8771f3c71ef1 · outbound

This paper cites A new proof of the likelihood principle.The British Journal for the Philosophy of Science, 66(3):475–503, 2015.

Fully Offline Reinforcement Learning A new proof of the likelihood principle.The British Journal for the Philosophy of Science, 66(3):475–503, 2015

Reference 25

Resolution: verified exact; doi, observed 2026-08-07T13:16:06.339819Z

Source-reported events for the cited work

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Observation ef74a39f-c140-461e-9299-238a9cacd29d · outbound

This paper cites Efficient bayes-adaptive reinforcement learn- ing using sample-based search.

Fully Offline Reinforcement Learning Efficient bayes-adaptive reinforcement learn- ing using sample-based search

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:18.234691Z

Source-reported events for the cited work

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Observation 66c454f4-a472-49ce-9f75-be6bfcf5830a · outbound

This paper cites Scalable and efficient bayes-adaptive reinforcement learning based on monte-carlo tree search.Journal of Artificial Intelligence Research, 48:841– 883, 10 2013.

Fully Offline Reinforcement Learning Scalable and efficient bayes-adaptive reinforcement learning based on monte-carlo tree search.Journal of Artificial Intelligence Research, 48:841– 883, 10 2013

Reference 27

Resolution: verified exact; doi, observed 2026-08-07T13:16:06.134303Z

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Observation 5ae9635e-e761-4966-9f5c-475929cbdaa3 · outbound

This paper cites Bayes-adaptive simulation-based search with value function approximation.

Fully Offline Reinforcement Learning Bayes-adaptive simulation-based search with value function approximation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:18.029970Z

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Observation 0bf909f1-3bb1-4868-9454-17edfad43c83 · outbound

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Fully Offline Reinforcement Learning Unresolved cited work

Reference 29

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Observation 9d4a2e4d-9dec-438c-8374-ef6516ec5cf1 · outbound

This paper cites A Clean Slate for Offline Reinforcement Learning.

Fully Offline Reinforcement Learning A Clean Slate for Offline Reinforcement Learning

Reference 30

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Observation cea3e1a3-04be-4a0e-b586-9593314cd513 · outbound

This paper cites Relu to the rescue: Improve your on-policy actor-critic with positive advantages.

Fully Offline Reinforcement Learning Relu to the rescue: Improve your on-policy actor-critic with positive advantages

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:17.425672Z

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Observation 3d7c401b-dbee-484d-97e6-317c68901b68 · outbound

This paper cites Littman, and Anthony R.

Fully Offline Reinforcement Learning Littman, and Anthony R

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:17.259390Z

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Observation c8b21251-6035-4794-b409-1b41bf81643a · outbound

This paper cites The validity of posterior expansions based on laplace’s method.Bayesian and Likelihood Methods in Statistics and Economics, pages 473–488, 1990.

Fully Offline Reinforcement Learning The validity of posterior expansions based on laplace’s method.Bayesian and Likelihood Methods in Statistics and Economics, pages 473–488, 1990

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:17.095540Z

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Observation 5f93167a-8333-4b84-9aa6-02e28e1791d0 · outbound

This paper cites Morel: Model-based offline reinforcement learning.

Fully Offline Reinforcement Learning Morel: Model-based offline reinforcement learning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:16.938047Z

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Observation b1048332-956b-40ae-97f3-948b0f060334 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Fully Offline Reinforcement Learning Adam: A Method for Stochastic Optimization

Reference 35

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Observation 07d239ca-ddc3-4b44-bd0a-7fa83874c750 · outbound

This paper cites Kleijn and A.W.

Fully Offline Reinforcement Learning Kleijn and A.W

Reference 36

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Observation 60336ccb-c3d8-410e-b70c-1f30de21c1e6 · outbound

This paper cites On asymptotic properties of predictive distributions.Biometrika, 83(2):299–313, 06 1996.

Fully Offline Reinforcement Learning On asymptotic properties of predictive distributions.Biometrika, 83(2):299–313, 06 1996

Reference 37

Resolution: verified exact; doi, observed 2026-08-07T13:16:05.898060Z

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Observation 5a7d85c1-7902-4a0e-b581-c368ca353447 · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

Fully Offline Reinforcement Learning Offline Reinforcement Learning with Implicit Q-Learning

Reference 38

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Observation 30ecba1b-69b7-4d9b-858a-2f4e7484e894 · outbound

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Fully Offline Reinforcement Learning Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:16:16.756648Z

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Observation ffe6b090-67c1-4b10-80c7-98f457a65e28 · outbound

This paper cites Conserva- tive q-learning for offline reinforcement learning.

Fully Offline Reinforcement Learning Conserva- tive q-learning for offline reinforcement learning

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:16.535991Z

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Observation ca65e117-c96a-4482-946a-1488ab71b6ce · outbound

This paper cites Springer Berlin Heidelberg, Berlin, Heidelberg, 2012.

Fully Offline Reinforcement Learning Springer Berlin Heidelberg, Berlin, Heidelberg, 2012

Reference 41

Resolution: verified exact; doi, observed 2026-08-07T13:16:05.713211Z

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Observation 59003146-ce29-4e1a-b6de-9a5eeb746557 · outbound

This paper cites On some asymptotic properties of maximum likelihood estimates and related bayes’ estimates.

Fully Offline Reinforcement Learning On some asymptotic properties of maximum likelihood estimates and related bayes’ estimates

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:16.367331Z

Source-reported events for the cited work

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Observation c3b51491-c4f4-492e-853b-98679cf6c568 · outbound

This paper cites Efficient backprop.

Fully Offline Reinforcement Learning Efficient backprop

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:16.174298Z

Source-reported events for the cited work

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Observation f588b94a-fc8f-49ea-8df6-56381841e2ab · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Fully Offline Reinforcement Learning Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 44

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Observation 763cabbd-dca8-4f36-9bd2-80503a8a572c · outbound

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Fully Offline Reinforcement Learning Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:16:15.993087Z

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Observation 7f2bc730-51c6-4fd0-bd3b-dfa8cec553e6 · outbound

This paper cites Discovered policy optimisation.Advances in Neural Information Processing Systems, 35:16455–16468, 2022.

Fully Offline Reinforcement Learning Discovered policy optimisation.Advances in Neural Information Processing Systems, 35:16455–16468, 2022

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:15.846851Z

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Observation c8edee02-d5e4-4aca-8ff9-e8d4973c8c16 · outbound

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Fully Offline Reinforcement Learning Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:16:15.734238Z

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Observation 0efa23b4-2053-4f0e-bc2e-4046f7604aa4 · outbound

This paper cites an unresolved cited work.

Fully Offline Reinforcement Learning Unresolved cited work

Reference 48

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:16:15.552146Z

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Observation 109b40e2-9355-43a8-919c-180a8a979deb · outbound

This paper cites Reinforcement learning: An overview, 2024.

Fully Offline Reinforcement Learning Reinforcement learning: An overview, 2024

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:01.713071Z

Source-reported events for the cited work

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Observation faa5c574-0182-4877-94e7-37959d84b22d · outbound

This paper cites an unresolved cited work.

Fully Offline Reinforcement Learning Unresolved cited work

Reference 50

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:16:15.280859Z

Source-reported events for the cited work

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Observation 5ad12ac9-c509-4e25-b824-4f25a4667b3f · outbound

This paper cites Randomized prior functions for deep reinforcement learning.

Fully Offline Reinforcement Learning Randomized prior functions for deep reinforcement learning

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:15.019714Z

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Observation 3f69e0b2-8fea-4d05-92fa-65b796d5717b · outbound

This paper cites Hyperparameter Selection for Offline Reinforcement Learning.

Fully Offline Reinforcement Learning Hyperparameter Selection for Offline Reinforcement Learning

Reference 52

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Observation 3cdb724d-205c-4577-bfcf-229b3a585e22 · outbound

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Fully Offline Reinforcement Learning Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:16:14.501296Z

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Observation 01135a97-f1f5-4186-8595-cbb430cf666a · outbound

This paper cites Puterman.Markov Decision Processes: Discrete Stochastic Dynamic Programming.

Fully Offline Reinforcement Learning Puterman.Markov Decision Processes: Discrete Stochastic Dynamic Programming

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:14.254455Z

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.

Observation d3db7484-5096-47a1-8f1d-99d7ad8a2b2e · outbound

This paper cites an unresolved cited work.

Fully Offline Reinforcement Learning Unresolved cited work

Reference 55

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:16:13.976552Z

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.

Observation a6c1a408-8b9c-43d6-aae5-a7adf262494e · outbound

This paper cites Roberts and Jeffrey S.

Fully Offline Reinforcement Learning Roberts and Jeffrey S

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:02.646018Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6548a700-b2b2-4587-8ecf-bf30c365eb12 · outbound

This paper cites Proximal Policy Optimization Algorithms.

Fully Offline Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:02.763290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9630eac-592d-458e-962e-7de77b2b2c11 · outbound

This paper cites The edge-of-reach problem in offline model-based reinforcement learning.

Fully Offline Reinforcement Learning The edge-of-reach problem in offline model-based reinforcement learning

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:13.702817Z

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.

Observation a4892ae3-3add-4651-956c-4ebe72a9e2f7 · outbound

This paper cites Smallwood and Edward J.

Fully Offline Reinforcement Learning Smallwood and Edward J

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:13.474924Z

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.

Observation 3dbaf9de-ba74-42ea-a427-5573b308c687 · outbound

This paper cites A Strong Baseline for Batch Imitation Learning.

Fully Offline Reinforcement Learning A Strong Baseline for Batch Imitation Learning

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-08-07T13:16:07.261939Z

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.

Observation 47b7cc56-f8b3-4513-a944-01b1baf5d6da · outbound

This paper cites Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Scholkopf, and Gert R.

Fully Offline Reinforcement Learning Sriperumbudur, Kenji Fukumizu, Arthur Gretton, Bernhard Scholkopf, and Gert R

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:13.245354Z

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.

Observation 9d4ce3f3-a4e3-43ae-9e00-b4997b3e5697 · outbound

This paper cites Model-Bellman inconsistency for model-based offline reinforcement learning.

Fully Offline Reinforcement Learning Model-Bellman inconsistency for model-based offline reinforcement learning

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:13.080447Z

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.

Observation 6f3323e5-478d-4efc-99b4-5fca93c0204d · outbound

This paper cites Sutton and Andrew G.

Fully Offline Reinforcement Learning Sutton and Andrew G

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:12.860042Z

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.

Observation 00410bc4-e85a-44a8-81b3-59f65070875b · outbound

This paper cites Algorithms for Reinforcement Learning.Synthesis Lectures on Artificial Intelligence and Machine Learning, 4(1):1–103, 2010.

Fully Offline Reinforcement Learning Algorithms for Reinforcement Learning.Synthesis Lectures on Artificial Intelligence and Machine Learning, 4(1):1–103, 2010

Reference 64

Resolution: verified exact; doi, observed 2026-08-07T13:16:05.532252Z

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.

Observation 148591fc-2b94-4a6b-95e3-f4149d0dd418 · outbound

This paper cites Revisiting the minimalist approach to offline reinforcement learning.

Fully Offline Reinforcement Learning Revisiting the minimalist approach to offline reinforcement learning

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:12.677528Z

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.

Observation 3f1d74b1-20f4-4f2d-b848-9d4d2ddcc294 · outbound

This paper cites an unresolved cited work.

Fully Offline Reinforcement Learning Unresolved cited work

Reference 66

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:16:12.382724Z

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.

Observation 2c8874e2-5f69-48de-8f6f-a726461790cb · outbound

This paper cites Kass, and Joseph B.

Fully Offline Reinforcement Learning Kass, and Joseph B

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:12.102869Z

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.

Observation 52eacba7-dd3b-435e-9019-4de3411263b5 · outbound

This paper cites an unresolved cited work.

Fully Offline Reinforcement Learning Unresolved cited work

Reference 68

Resolution: verified exact; doi, observed 2026-08-07T13:16:05.370696Z

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.

Observation 200ba08e-31ef-46ab-9499-8a18109ff2ee · outbound

This paper cites Information rates of nonparametric gaussian process methods.J.

Fully Offline Reinforcement Learning Information rates of nonparametric gaussian process methods.J

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:11.719273Z

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.

Observation a5ff4e8f-5141-4868-a201-40cd77bbf3f9 · outbound

This paper cites No more pesky hyperparameters: Offline hyperparameter tuning for RL.Transactions on Machine Learning Research, 2022.

Fully Offline Reinforcement Learning No more pesky hyperparameters: Offline hyperparameter tuning for RL.Transactions on Machine Learning Research, 2022

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:11.312056Z

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.

Observation 6db256f6-ee66-49ff-94bc-74333915930d · outbound

This paper cites Foster, and Sham M.

Fully Offline Reinforcement Learning Foster, and Sham M

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:10.928204Z

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.

Observation 377f2112-f27e-47e5-b138-44b928cd80b0 · outbound

This paper cites Differential-space.Journal of Mathematics and Physics, 2(1-4):131–174, 1923.

Fully Offline Reinforcement Learning Differential-space.Journal of Mathematics and Physics, 2(1-4):131–174, 1923

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:04.598127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1f9866b-e8e5-4644-b4b1-5d10a190d644 · outbound

This paper cites Information-theoretic determination of minimax rates of convergence.The Annals of Statistics, 27(5):1564 – 1599, 1999.

Fully Offline Reinforcement Learning Information-theoretic determination of minimax rates of convergence.The Annals of Statistics, 27(5):1564 – 1599, 1999

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T13:16:04.682823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32d5bb05-0908-42bb-9fad-fc95a8b99a71 · outbound

This paper cites Mopo: Model-based offline policy optimization.

Fully Offline Reinforcement Learning Mopo: Model-based offline policy optimization

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:10.584652Z

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.

Observation c848b3c1-b773-4246-9597-50e98808cd6f · outbound

This paper cites Combo: Conservative offline model-based policy optimization.

Fully Offline Reinforcement Learning Combo: Conservative offline model-based policy optimization

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:10.295053Z

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.

Observation d95966f2-0215-4863-a16c-934f6f31a520 · outbound

This paper cites On the importance of hyperparameter optimization for model-based reinforcement learning.

Fully Offline Reinforcement Learning On the importance of hyperparameter optimization for model-based reinforcement learning

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:09.953911Z

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.

Observation 01f6eb3b-010c-4d61-ab64-ee67d6026ba2 · outbound

This paper cites Varibad: A very good method for bayes-adaptive deep rl via meta- learning.

Fully Offline Reinforcement Learning Varibad: A very good method for bayes-adaptive deep rl via meta- learning

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:09.714445Z

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.

Observation e4a4b1c3-7783-4bf3-86a2-7dba28d76125 · outbound

This paper cites N−1X i=0 1 N D 2 log(2π) + 1 2 D−1X d=0 logσ 2 θd (xi) + (yid −µ θd (xi))2 σ2 θd (xi) !!# , =Ei∼UN.

Fully Offline Reinforcement Learning N−1X i=0 1 N D 2 log(2π) + 1 2 D−1X d=0 logσ 2 θd (xi) + (yid −µ θd (xi))2 σ2 θd (xi) !!# , =Ei∼UN

Reference 78

Resolution: verified exact; raw_fallback, observed 2026-08-07T13:16:06.856195Z

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.

Observation 584f4e18-5a1d-4826-9888-eb69dfcfea54 · outbound

This paper cites Eθ∼PΘ(DN ).

Fully Offline Reinforcement Learning Eθ∼PΘ(DN )

Reference 83

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T13:16:06.605584Z

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.

Observation d995e4c3-886c-44f7-9c7a-9ca3fbf81918 · outbound

This paper cites doi: 10.1093/oso/9780198504856.003.0002.

Fully Offline Reinforcement Learning doi: 10.1093/oso/9780198504856.003.0002

Reference 1999

Resolution: unresolved; no resolver link, observed 2026-08-07T13:15:57.660083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa4e3f11-d59b-4bd4-a552-fd3592fb27fd · outbound

This paper cites URL https://books.google.co.uk/books?id= s6mVlgEACAAJ.

Fully Offline Reinforcement Learning URL https://books.google.co.uk/books?id= s6mVlgEACAAJ

Reference 2013

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:20.621497Z

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.

Observation 1e434d6f-04c0-42fb-b1dc-edaa8c4dbd63 · outbound

This paper cites an unresolved cited work.

Fully Offline Reinforcement Learning Unresolved cited work

Reference 2025

Resolution: unresolved; raw_fallback, observed 2026-08-07T13:16:17.599212Z

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.

Observation 8c85133c-fff4-4179-b7a6-273632e7103f · outbound

This paper cites URL http://papers.nips.cc/paper/8080- randomized-prior-functions-for-deep-reinforcement-learning.pdf.

Fully Offline Reinforcement Learning URL http://papers.nips.cc/paper/8080- randomized-prior-functions-for-deep-reinforcement-learning.pdf

Reference 8629

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:16:14.762978Z

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.

Pith citing papers

Observation 7a38f31e-998b-44d0-a06c-e8f6a48dbd1e · inbound

Long-Horizon Model-Based Offline Reinforcement Learning Without Explicit Conservatism cites this paper.

Long-Horizon Model-Based Offline Reinforcement Learning Without Explicit Conservatism Fully Offline Reinforcement Learning

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-17T00:20:38.764461Z

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.

Observation 00b3f2c1-259b-40d1-9384-9e49144431e9 · inbound

Is Inter-Seed Cross-Play Enough? Evaluating the Robustness of Zero-Shot Coordination Algorithms to Implementation Details cites this paper.

Is Inter-Seed Cross-Play Enough? Evaluating the Robustness of Zero-Shot Coordination Algorithms to Implementation Details Fully Offline Reinforcement Learning

Reference 117

Resolution: unresolved; no resolver link, observed 2026-08-05T15:25:39.829506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.