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Paper Citation Record · LEDGER

Information-Based Exploration via Random Features for Reinforcement Learning

As of 7 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 0 inbound Pith citation observations for arXiv:2607.17981.

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

pith.paper-citation-record.v1
2607.17981 v1

Coverage vector

measured 67 of 67 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-01T16:35:03.105674Z

measured 67 of 67 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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

67 of 67 outbound references displayed

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External citation measurements

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Outbound references

Observation 8b973569-0a9d-4645-a0ad-adfc14c6d9b5 · outbound

This paper cites 135 , author=.

Information-Based Exploration via Random Features for Reinforcement Learning 135 , author=

Reference 1

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source=arxiv_source observed=2026-08-01T16:35:00.023272Z digest=sha256:3450acaaf65a6116007441bc493f80aee61c2456f2f02518826819701680f06b

Observation 5ff7be74-6677-4a88-afac-5dde6002e931 · outbound

This paper cites 2009 , publisher=.

Information-Based Exploration via Random Features for Reinforcement Learning 2009 , publisher=

Reference 2

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Observation ccee3aef-b1a1-47b1-b373-17ec9e754585 · outbound

This paper cites Journal of Computer and System Sciences , volume=.

Information-Based Exploration via Random Features for Reinforcement Learning Journal of Computer and System Sciences , volume=

Reference 3

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Information-Based Exploration via Random Features for Reinforcement Learning Machine learning , volume=

Reference 4

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Observation 3d2dd2bc-bbef-48d0-9379-66832c6048cb · outbound

This paper cites Proceedings of the 26th annual international conference on machine learning , pages=.

Information-Based Exploration via Random Features for Reinforcement Learning Proceedings of the 26th annual international conference on machine learning , pages=

Reference 5

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This paper cites Advances in neural information processing systems , pages=.

Information-Based Exploration via Random Features for Reinforcement Learning Advances in neural information processing systems , pages=

Reference 6

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Observation 7bc7a6d1-12cc-476c-b165-c3998f3b9203 · outbound

This paper cites International conference on machine learning , pages=.

Information-Based Exploration via Random Features for Reinforcement Learning International conference on machine learning , pages=

Reference 7

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Observation e294e5f7-8778-474d-9d8a-49704e2ca071 · outbound

This paper cites Never Give Up: Learning Directed Exploration Strategies.

Information-Based Exploration via Random Features for Reinforcement Learning Never Give Up: Learning Directed Exploration Strategies

Reference 8

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Observation c3ea4a7d-e3d7-4cfb-b2da-7feecdbb0090 · outbound

This paper cites Exploration by Random Network Distillation.

Information-Based Exploration via Random Features for Reinforcement Learning Exploration by Random Network Distillation

Reference 9

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This paper cites Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design.

Information-Based Exploration via Random Features for Reinforcement Learning Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design

Reference 10

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This paper cites International Conference on Artificial Intelligence and Statistics , pages=.

Information-Based Exploration via Random Features for Reinforcement Learning International Conference on Artificial Intelligence and Statistics , pages=

Reference 11

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Observation 1c42df4b-2cb7-47b0-97e7-83361c7f8ca0 · outbound

This paper cites Finite-Time Analysis of Kernelised Contextual Bandits.

Information-Based Exploration via Random Features for Reinforcement Learning Finite-Time Analysis of Kernelised Contextual Bandits

Reference 12

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Observation b896fdc3-37fe-4d77-a477-f9ea565398e7 · outbound

This paper cites Advances in neural information processing systems , volume=.

Information-Based Exploration via Random Features for Reinforcement Learning Advances in neural information processing systems , volume=

Reference 13

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Observation 69aeca25-a4c2-404c-852b-63b2675f9ada · outbound

This paper cites Biometrika , volume=.

Information-Based Exploration via Random Features for Reinforcement Learning Biometrika , volume=

Reference 14

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Information-Based Exploration via Random Features for Reinforcement Learning Advances in neural information processing systems , volume=

Reference 15

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Information-Based Exploration via Random Features for Reinforcement Learning Advances in neural information processing systems , volume=

Reference 16

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Observation d32d174f-ac38-4d20-822f-57ca451461ad · outbound

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Information-Based Exploration via Random Features for Reinforcement Learning , author=

Reference 17

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This paper cites Advances in neural information processing systems , volume=.

Information-Based Exploration via Random Features for Reinforcement Learning Advances in neural information processing systems , volume=

Reference 18

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Observation 0a5a3956-6f64-4731-9908-85a01827412e · outbound

This paper cites Advances in neural information processing systems , volume=.

Information-Based Exploration via Random Features for Reinforcement Learning Advances in neural information processing systems , volume=

Reference 19

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Observation 05cde62f-5c91-4897-af23-c9c74785d838 · outbound

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Information-Based Exploration via Random Features for Reinforcement Learning 2018 Information Theory and Applications Workshop (ITA) , pages=

Reference 20

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Information-Based Exploration via Random Features for Reinforcement Learning International conference on machine learning , pages=

Reference 21

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Information-Based Exploration via Random Features for Reinforcement Learning Advances in neural information processing systems , volume=

Reference 22

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Observation 6d0d0be8-2b84-40f4-a650-31a938adcc53 · outbound

This paper cites Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning.

Information-Based Exploration via Random Features for Reinforcement Learning Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning

Reference 23

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Observation c5a96ead-c3ef-4b8c-8e2b-fbbe31bc5c2b · outbound

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Information-Based Exploration via Random Features for Reinforcement Learning Bayesian Curiosity for Efficient Exploration in Reinforcement Learning

Reference 24

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Information-Based Exploration via Random Features for Reinforcement Learning Bayesian

Reference 25

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Information-Based Exploration via Random Features for Reinforcement Learning International conference on computational learning theory , pages=

Reference 26

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Observation 84e5d018-740b-43e3-98ba-8a47a1c10756 · outbound

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Information-Based Exploration via Random Features for Reinforcement Learning Transactions of the American mathematical society , volume=

Reference 27

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Information-Based Exploration via Random Features for Reinforcement Learning 1999 , publisher=

Reference 28

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Information-Based Exploration via Random Features for Reinforcement Learning Unresolved cited work

Reference 29

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Information-Based Exploration via Random Features for Reinforcement Learning Seventh International Workshop on Artificial Intelligence and Statistics , year=

Reference 30

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Information-Based Exploration via Random Features for Reinforcement Learning Advances in neural information processing systems , volume=

Reference 31

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Information-Based Exploration via Random Features for Reinforcement Learning 1950 , publisher=

Reference 32

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Information-Based Exploration via Random Features for Reinforcement Learning Advances in neural information processing systems , volume=

Reference 33

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Observation 947f7b1f-c05f-4a22-876a-9f4c4ac29e27 · outbound

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Information-Based Exploration via Random Features for Reinforcement Learning On the Error of Random Fourier Features

Reference 34

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Information-Based Exploration via Random Features for Reinforcement Learning Vanilla Bayesian Optimization Performs Great in High Dimensions

Reference 35

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Information-Based Exploration via Random Features for Reinforcement Learning ZAMM-Journal of Applied Mathematics and Mechanics/Zeitschrift f

Reference 36

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Information-Based Exploration via Random Features for Reinforcement Learning RLeXplore: Accelerating Research in Intrinsically-Motivated Reinforcement Learning

Reference 37

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Information-Based Exploration via Random Features for Reinforcement Learning Proximal Policy Optimization Algorithms

Reference 38

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This paper cites Daniel Freeman and Erik Frey and Anton Raichuk and Sertan Girgin and Igor Mordatch and Olivier Bachem , title =.

Information-Based Exploration via Random Features for Reinforcement Learning Daniel Freeman and Erik Frey and Anton Raichuk and Sertan Girgin and Igor Mordatch and Olivier Bachem , title =

Reference 39

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Information-Based Exploration via Random Features for Reinforcement Learning Unresolved cited work

Reference 40

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source=arxiv_source observed=2026-08-01T16:35:02.781517Z digest=sha256:582aed6e6f636c6ac3efe0844459179eaa089fe52cf2c835f484726f4fdfa9f2

Observation 3bdfbfa2-0fdf-4c3a-af13-3aeaf461fd07 · outbound

This paper cites NAVIX: Scaling MiniGrid Environments with JAX.

Information-Based Exploration via Random Features for Reinforcement Learning NAVIX: Scaling MiniGrid Environments with JAX

Reference 41

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source=arxiv_source observed=2026-08-01T16:35:02.893641Z digest=sha256:62686f1b5a01354615cd29a02780c73ca2857b8e0a19f382336be29c6e993ceb

Observation bc458cce-5a2c-491f-8fa9-397615687046 · outbound

This paper cites OGBench: Benchmarking Offline Goal-Conditioned RL.

Information-Based Exploration via Random Features for Reinforcement Learning OGBench: Benchmarking Offline Goal-Conditioned RL

Reference 42

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no resolver link, observed 2026-08-01T16:35:02.963644Z

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source=arxiv_source observed=2026-08-01T16:35:02.963644Z digest=sha256:ab145f48c4efdea9c93b7f997fc606dc346ff84e76b847fd8f32608e8e3105a1

Observation 30f7e6b8-0bb5-40c2-b407-071f6c682141 · outbound

This paper cites 1992 , publisher=.

Information-Based Exploration via Random Features for Reinforcement Learning 1992 , publisher=

Reference 43

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source=arxiv_source observed=2026-08-01T16:35:02.979143Z digest=sha256:dee310d1f8908f7f5e2fda645e55afac198325c421e425cc5a24616bbfa19b97

Observation c56c4b39-b4c2-4214-ad1c-db46574050c7 · outbound

This paper cites an unresolved cited work.

Information-Based Exploration via Random Features for Reinforcement Learning Unresolved cited work

Reference 44

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no resolver link, observed 2026-08-01T16:35:02.983748Z

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source=arxiv_source observed=2026-08-01T16:35:02.983748Z digest=sha256:3bb20537eced4de4ffc1e376130e923fff27b8276fdbd500f0d094a38d2f2625

Observation 035993e8-4204-4e8e-a8f1-0c3b7b4507ef · outbound

This paper cites Fast active learning for pure exploration in reinforcement learning.

Information-Based Exploration via Random Features for Reinforcement Learning Fast active learning for pure exploration in reinforcement learning

Reference 45

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no resolver link, observed 2026-08-01T16:35:02.988914Z

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source=arxiv_source observed=2026-08-01T16:35:02.988914Z digest=sha256:2eea1e81d9959e62782d235ff672b0be71fd49d8ff1b5fdd875b4e4380398106

Observation 46ef35de-414c-4528-85d4-5b7ef6cb300d · outbound

This paper cites 1959 , publisher=.

Information-Based Exploration via Random Features for Reinforcement Learning 1959 , publisher=

Reference 46

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source=arxiv_source observed=2026-08-01T16:35:02.993830Z digest=sha256:257164254e23cc106a646f7188c30b0d03f7ebc065b5bb66abac45a489bc0e1d

Observation ea495b36-ca70-44ae-9bdd-b65c6bf83cc4 · outbound

This paper cites MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization.

Information-Based Exploration via Random Features for Reinforcement Learning MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Reference 47

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no resolver link, observed 2026-08-01T16:35:02.998242Z

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source=arxiv_source observed=2026-08-01T16:35:02.998242Z digest=sha256:a476b03cc305aebed44c1cef6c9dc52727714604e40f61cf957471cdfe2c98ab

Observation a829bd1e-7725-470e-8a1b-c99e25046d09 · outbound

This paper cites Proceedings of the thiry-fourth annual ACM symposium on Theory of computing , pages=.

Information-Based Exploration via Random Features for Reinforcement Learning Proceedings of the thiry-fourth annual ACM symposium on Theory of computing , pages=

Reference 48

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no resolver link, observed 2026-08-01T16:35:03.005226Z

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source=arxiv_source observed=2026-08-01T16:35:03.005226Z digest=sha256:345bd5bbf492818ac8f1ea22c011011ac41f5fb3b0369f3c10a2da579086f55c

Observation 2f2ad1df-0407-4f89-b406-80c789388b4b · outbound

This paper cites Communications of the ACM , volume=.

Information-Based Exploration via Random Features for Reinforcement Learning Communications of the ACM , volume=

Reference 49

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source=arxiv_source observed=2026-08-01T16:35:03.009874Z digest=sha256:c078dffd17aba78346a670e608c74a7596405ce2efa3879be27ab3934223e495

Observation cce06467-27f8-4fea-b403-c81ef45a05e7 · outbound

This paper cites Exploration and Anti-Exploration with Distributional Random Network Distillation.

Information-Based Exploration via Random Features for Reinforcement Learning Exploration and Anti-Exploration with Distributional Random Network Distillation

Reference 50

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source=arxiv_source observed=2026-08-01T16:35:03.014320Z digest=sha256:b618b29d4c490b8978d6427529af699b3ae9459b14b5a048061406b59e82c84d

Observation 9a1110cb-6c27-42e2-b93f-09c9bcb16735 · outbound

This paper cites Advances in neural information processing systems , volume=.

Information-Based Exploration via Random Features for Reinforcement Learning Advances in neural information processing systems , volume=

Reference 51

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source=arxiv_source observed=2026-08-01T16:35:03.019313Z digest=sha256:562e22bdc46d7e325570ac08efdd7f13f5980e57b732445b3d1e902eb2b67ab5

Observation 0047f38b-7c14-4406-a9a1-48df8e771acc · outbound

This paper cites Proceedings of the thirteenth international conference on artificial intelligence and statistics , pages=.

Information-Based Exploration via Random Features for Reinforcement Learning Proceedings of the thirteenth international conference on artificial intelligence and statistics , pages=

Reference 52

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no resolver link, observed 2026-08-01T16:35:03.024120Z

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source=arxiv_source observed=2026-08-01T16:35:03.024120Z digest=sha256:eea1e25e85f23fda675061a7ed62f338ae497b5f7521b866a0379a2d475c933b

Observation bb40ae7b-d1c8-4e68-b005-5f36833b460e · outbound

This paper cites 2013 IEEE international conference on acoustics, speech and signal processing , pages=.

Information-Based Exploration via Random Features for Reinforcement Learning 2013 IEEE international conference on acoustics, speech and signal processing , pages=

Reference 53

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no resolver link, observed 2026-08-01T16:35:03.028713Z

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source=arxiv_source observed=2026-08-01T16:35:03.028713Z digest=sha256:d52f6764fdce4b745f89250baec2d6a9fff0edd1e158c3fbc423949d0edef983

Observation 81048ba0-c328-4518-b5cf-4721974783d2 · outbound

This paper cites Proceedings of the AAAI conference on artificial intelligence , volume=.

Information-Based Exploration via Random Features for Reinforcement Learning Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 54

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no resolver link, observed 2026-08-01T16:35:03.033452Z

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source=arxiv_source observed=2026-08-01T16:35:03.033452Z digest=sha256:2bc0e1c5a9a87c6718c0d0e533c313a86cce16d8d6a5a4b3ba516fe814574966

Observation ce924073-8b45-424d-a698-0b09164c43bf · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Information-Based Exploration via Random Features for Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 55

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no resolver link, observed 2026-08-01T16:35:03.038083Z

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source=arxiv_source observed=2026-08-01T16:35:03.038083Z digest=sha256:27843599115313f0960609d682390b29048138cb87d846673f1e654e49421398

Observation e8161798-75d3-49ce-86bf-b208c72aeb6d · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Information-Based Exploration via Random Features for Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 56

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no resolver link, observed 2026-08-01T16:35:03.044744Z

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source=arxiv_source observed=2026-08-01T16:35:03.044744Z digest=sha256:3dab597068450fcf313aaeefeb7165bf071d2cf3ef37cdf52bf15c064750d2eb

Observation 4d8f4c89-2a70-4dd1-9c7c-72a8c50eb06f · outbound

This paper cites International conference on machine learning , pages=.

Information-Based Exploration via Random Features for Reinforcement Learning International conference on machine learning , pages=

Reference 57

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source=arxiv_source observed=2026-08-01T16:35:03.050102Z digest=sha256:d6de1166263023e3941c145a8cc0f28f3264becffe8cb4d6dc40eadf608c6f06

Observation ea99dd02-77b8-4b97-9e43-e4774606d8eb · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

Information-Based Exploration via Random Features for Reinforcement Learning Playing Atari with Deep Reinforcement Learning

Reference 58

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no resolver link, observed 2026-08-01T16:35:03.055676Z

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source=arxiv_source observed=2026-08-01T16:35:03.055676Z digest=sha256:16a83e22f3ca67d697e1fcddb5f64632a08681dbbc78a8039bc71f065a20dff9

Observation 2c773051-c34d-47d3-9237-574deae29320 · outbound

This paper cites The Thirteenth International Conference on Learning Representations , year=.

Information-Based Exploration via Random Features for Reinforcement Learning The Thirteenth International Conference on Learning Representations , year=

Reference 59

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no resolver link, observed 2026-08-01T16:35:03.063483Z

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source=arxiv_source observed=2026-08-01T16:35:03.063483Z digest=sha256:6acb1fea8dbb9690bb2b817853829a4251cc9c450f3eae00d1694afea4514eee

Observation d6187c0d-fe27-4e62-912a-f1f42b24d349 · outbound

This paper cites an unresolved cited work.

Information-Based Exploration via Random Features for Reinforcement Learning Unresolved cited work

Reference 60

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source=arxiv_source observed=2026-08-01T16:35:03.068760Z digest=sha256:4db4aae6e2bcd4614077826d0f5f0f8d3e080259785678d7e581d3acac857147

Observation c34302fa-49fd-43c9-a8e3-41f4a8cb2c78 · outbound

This paper cites 2025 , url=.

Information-Based Exploration via Random Features for Reinforcement Learning 2025 , url=

Reference 61

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no resolver link, observed 2026-08-01T16:35:03.073197Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-01T16:35:03.073197Z digest=sha256:88ee37fb4d731dce1d54b380c41b1c7b88b10311752e9b011da9d24182448a74

Observation 2b797d36-0ea6-49ef-bc94-e9f6ff9a7121 · outbound

This paper cites an unresolved cited work.

Information-Based Exploration via Random Features for Reinforcement Learning Unresolved cited work

Reference 62

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no resolver link, observed 2026-08-01T16:35:03.078594Z

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source=arxiv_source observed=2026-08-01T16:35:03.078594Z digest=sha256:80cf64e6f6ecaae8548506d84203eb7ae8ca34ad2a549f97d02987132e0eb437

Observation 7f77f602-e6d3-42a7-b63c-ec34e0b31f80 · outbound

This paper cites Information-Directed Exploration for Deep Reinforcement Learning.

Information-Based Exploration via Random Features for Reinforcement Learning Information-Directed Exploration for Deep Reinforcement Learning

Reference 63

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source=arxiv_source observed=2026-08-01T16:35:03.083430Z digest=sha256:e17024eb29da3aa0192fbd6f641e0490b50729ad177cd7bf6310f7900a15f98d

Observation 1c4d53e1-85d0-4a44-99f0-aa3fea385a7a · outbound

This paper cites The 22nd International Conference on Artificial Intelligence and Statistics , pages=.

Information-Based Exploration via Random Features for Reinforcement Learning The 22nd International Conference on Artificial Intelligence and Statistics , pages=

Reference 64

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source=arxiv_source observed=2026-08-01T16:35:03.088609Z digest=sha256:c7575c654fe6892e0fee4ddf44dbc8b1f70c8d0675d80bb37e7d19ee4260dee3

Observation 1004c505-1412-4fdd-9f6e-5605bf18ef5c · outbound

This paper cites Kernel-Based Reinforcement Learning in Robust.

Information-Based Exploration via Random Features for Reinforcement Learning Kernel-Based Reinforcement Learning in Robust

Reference 65

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source=arxiv_source observed=2026-08-01T16:35:03.094105Z digest=sha256:137c130b10b9a09a7d264957e6f77c49c172743af22f58540672ea78623d14ec

Observation ca6874f9-2771-4cbd-a264-7b03b88348b6 · outbound

This paper cites International Conference on Artificial Intelligence and Statistics , pages=.

Information-Based Exploration via Random Features for Reinforcement Learning International Conference on Artificial Intelligence and Statistics , pages=

Reference 66

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no resolver link, observed 2026-08-01T16:35:03.100960Z

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source=arxiv_source observed=2026-08-01T16:35:03.100960Z digest=sha256:a01d04f91ac4ae9d1f1709363d49c8ec22b21925b992210b5044bac3b046891b

Observation 10594c79-e643-4e99-a1e6-44f4aa3d066c · outbound

This paper cites Cognitive Neuroscience , volume=.

Information-Based Exploration via Random Features for Reinforcement Learning Cognitive Neuroscience , volume=

Reference 67

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source=arxiv_source observed=2026-08-01T16:35:03.105674Z digest=sha256:8e2bcf94467e0dd072f18ec11b56967be271893d53e75e6cb338426617a48728

Pith citing papers

No inbound Pith citation observations are available.