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Paper Citation Record · LEDGER

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning

As of 8 August 2026, this Paper Citation Record lists 100 of 169 outbound references and 0 inbound Pith citation observations for arXiv:2607.25123.

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

pith.paper-citation-record.v1
2607.25123 v1

Coverage vector

measured 100 of 169 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T00:47:51.407786Z

measured 100 of 100 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

100 of 169 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved100
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 45234cf9-4400-42a6-8821-8512608626ea · outbound

This paper cites Neural computation , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Neural computation , volume=

Reference 2

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Observation 1fd74ced-a3ac-4b3b-a147-d65ebda6e86c · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 3

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Observation 93ef2e0c-f033-4b11-b653-6cbe8bb1d275 · outbound

This paper cites an unresolved cited work.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Unresolved cited work

Reference 5

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source=arxiv_source observed=2026-07-31T00:47:51.121976Z digest=sha256:4efd548855910dbc506baddddb80178a800f3654204fc428ad3ecd9b77b27151

Observation 68ac1859-130b-4acb-a992-8bcd2a9d1b8a · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Learning Representations , year=

Reference 6

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Observation a6f473d3-ebb1-4bfe-bad6-7e719396f40d · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 7

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source=arxiv_source observed=2026-07-31T00:47:51.128562Z digest=sha256:fd2cad00a24bbe95cd270bf3ba3035cf581535532dee38218d53d859a4d1fc08

Observation a877f7e8-0ca0-4faa-b352-c7079cfabfe4 · outbound

This paper cites arXiv preprint arXiv:2507.09087 , year=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning arXiv preprint arXiv:2507.09087 , year=

Reference 8

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source=arxiv_source observed=2026-07-31T00:47:51.131816Z digest=sha256:dddfa51a51491b951396873a34cbf27291b43f798cb938eba4d90da2e2ff55d6

Observation a5a32b0a-1693-4b19-bebe-c27e87f25728 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 9

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Observation 30da7685-0c0d-4ba9-a491-4990b6241dac · outbound

This paper cites ArXiv , year=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning ArXiv , year=

Reference 10

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Observation b9154672-8d24-4cae-aaf3-4e9672dbd946 · outbound

This paper cites International Conference on Machine Learning , year=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Machine Learning , year=

Reference 11

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Observation 052e6342-faed-4a20-8882-f179c54a7352 · outbound

This paper cites IEEE Transactions on Signal Processing , year=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning IEEE Transactions on Signal Processing , year=

Reference 12

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Observation de9b2c58-6796-459f-b9b9-48c941f43d6f · outbound

This paper cites Journal of Machine Learning Research , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Journal of Machine Learning Research , volume=

Reference 13

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Observation 06a82a7a-6023-4766-b772-daddea8070b3 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning The Thirteenth International Conference on Learning Representations , year=

Reference 14

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Observation 6d1826ba-e9a2-4216-b9b0-f58483869b36 · outbound

This paper cites International Conference on Machine Learning , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Machine Learning , pages=

Reference 15

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Observation 364f8049-682c-46b1-b13f-deb716d0b695 · outbound

This paper cites Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence , pages=

Reference 16

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Observation c57c539b-75cc-4319-8775-d90ddce8ccab · outbound

This paper cites IEEE Transactions on Signal Processing , year=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning IEEE Transactions on Signal Processing , year=

Reference 17

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Observation 1c6db84b-f4e8-4f8a-a943-dff6ca0e9ce5 · outbound

This paper cites AAAI Conference on Artificial Intelligence , year=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning AAAI Conference on Artificial Intelligence , year=

Reference 18

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Observation 6d6c9627-02e8-4f84-8ef8-ce4b0ef15126 · outbound

This paper cites 2022 , journaltitle =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning 2022 , journaltitle =

Reference 19

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source=arxiv_source observed=2026-07-31T00:47:51.163545Z digest=sha256:2f5c063ab54c0214be56e31d39cd5a02742ef0a6dafedb638a5fdbc1db3bb6ad

Observation 94ba4c67-951f-434d-99db-bc5024a64d97 · outbound

This paper cites nature , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning nature , volume=

Reference 20

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Observation ee8f269d-7982-4879-9c83-bcb337cf3a44 · outbound

This paper cites Proceedings of the Ninth National Conference on Artificial Intelligence - Volume 2 , pages =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the Ninth National Conference on Artificial Intelligence - Volume 2 , pages =

Reference 21

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Observation 8ed5cba1-d7d0-4092-880f-7b3b055961dd · outbound

This paper cites and Barto, Andrew G.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning and Barto, Andrew G

Reference 23

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Observation 8991ba46-585d-4be0-8792-51ccae132442 · outbound

This paper cites an unresolved cited work.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Unresolved cited work

Reference 24

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Observation 4290ba54-16a3-4e8a-b74e-1f022e2284a0 · outbound

This paper cites an unresolved cited work.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Unresolved cited work

Reference 25

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Observation 3035b10c-15d1-4142-b1dc-e24e58407a20 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Learning Representations , year=

Reference 26

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Observation cf9b20f5-f067-4f4d-9f4a-4119f4a4e0b9 · outbound

This paper cites , title =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning , title =

Reference 27

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Observation b5f9b704-8fc0-4f05-b8df-8f4fb63d2ae9 · outbound

This paper cites Journal of Machine Learning Research (JMLR) , volume =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Journal of Machine Learning Research (JMLR) , volume =

Reference 28

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Observation 0996666c-7731-4ced-bdab-f238178969dc · outbound

This paper cites International Conference on Machine Learning (ICML) , year =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Machine Learning (ICML) , year =

Reference 29

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Observation de98b11a-8451-4c7e-a19f-147e9bd8aadf · outbound

This paper cites International Conference on Learning Representations (ICLR) , year =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Learning Representations (ICLR) , year =

Reference 30

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Observation c6ee6037-4406-4abc-aaa1-d6607998309b · outbound

This paper cites 3rd International Conference on Learning Representations (ICLR) , year=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning 3rd International Conference on Learning Representations (ICLR) , year=

Reference 31

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Observation 0e8a92a9-3db2-41a6-8cc9-887e1dc50353 · outbound

This paper cites Sutton , title =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Sutton , title =

Reference 32

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Observation 9d1a75ae-2d2e-420e-89ef-78f727f8cfd2 · outbound

This paper cites The Reinforcement Learning Journal , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning The Reinforcement Learning Journal , volume=

Reference 33

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Observation dd2c011d-125a-426f-add8-325669ecc021 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 34

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Observation 6610599a-54fe-4e5c-b1e2-67b362e369b6 · outbound

This paper cites International Conference on Machine Learning , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Machine Learning , pages=

Reference 35

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Observation 27bc263d-1542-408c-b535-9bc22a559e6d · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in neural information processing systems , volume=

Reference 36

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Observation 22239a38-d20f-482b-adc0-0c46d0f5a30f · outbound

This paper cites International Conference on Machine Learning , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Machine Learning , pages=

Reference 37

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Observation 3a53ca67-1c1e-4a00-a8c6-74945484f6ac · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Dream to Control: Learning Behaviors by Latent Imagination

Reference 38

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Observation b2c4c851-7f80-4d88-9d86-5eb636633f27 · outbound

This paper cites Model-Based Reinforcement Learning for Atari.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Model-Based Reinforcement Learning for Atari

Reference 39

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Observation 5a1426ba-c0e4-45b2-a565-c8159b12a24e · outbound

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Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Medical Imaging with Deep Learning , pages =

Reference 40

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Observation 4fc92b92-5381-4178-8e59-a4bb4730aaf0 · outbound

This paper cites Proceedings of the 40th International Conference on Machine Learning , pages =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the 40th International Conference on Machine Learning , pages =

Reference 41

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Observation ef3d9843-8ed9-41c3-9910-6dc5903fba91 · outbound

This paper cites an unresolved cited work.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Unresolved cited work

Reference 42

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Observation 657360cc-ff7e-491f-915a-d8775078402f · outbound

This paper cites Artificial intelligence , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Artificial intelligence , volume=

Reference 43

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Observation 1f587b7b-3c35-4bea-945a-89fe0c854464 · outbound

This paper cites Artificial Intelligence , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Artificial Intelligence , volume=

Reference 44

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Observation 6de3314b-0a8f-4bce-ac2d-7fe4b9e83672 · outbound

This paper cites Journal of Machine Learning Research , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Journal of Machine Learning Research , volume=

Reference 45

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source=arxiv_source observed=2026-07-31T00:47:51.241263Z digest=sha256:f58fafb8b888f552c10521a328a0d0ea591ed59d76f62aa135cff23cfa0674e6

Observation 3102fc96-cbfc-4e9f-b593-9004e8608ea0 · outbound

This paper cites Journal of Artificial Intelligence Research , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Journal of Artificial Intelligence Research , volume=

Reference 46

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source=arxiv_source observed=2026-07-31T00:47:51.244001Z digest=sha256:3f300529c36606d905b4298e5884fa2551af90bc910c2e6940049207dc2d219d

Observation 019fca96-1ba5-4cfd-8084-20817e61d0c3 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 47

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source=arxiv_source observed=2026-07-31T00:47:51.246884Z digest=sha256:56a0596520b73c6cc0a48e583653520322d4f995e9d6f314789e0053df7db7bf

Observation f6750aa9-b94c-46c9-b1e1-e511b49b6fce · outbound

This paper cites Machine learning , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Machine learning , volume=

Reference 48

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source=arxiv_source observed=2026-07-31T00:47:51.249797Z digest=sha256:2ad3de242c1e53bb108f5f3440ca67501e295828c5efd2b7418fd4e62a7efdac

Observation 9ade702c-f0ea-4369-a303-8682bc4d447a · outbound

This paper cites and Naddaf, Yavar and Veness, Joel and Bowling, Michael , journal =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning and Naddaf, Yavar and Veness, Joel and Bowling, Michael , journal =

Reference 49

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source=arxiv_source observed=2026-07-31T00:47:51.253109Z digest=sha256:d7fa5aa3b3a1d075012d7368c94f99d245a52c3b8ae5a9614655c6b6225ebdb0

Observation 524fdad9-ecdf-49ff-a4ad-f611752f920d · outbound

This paper cites International Conference on Machine Learning , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Machine Learning , pages=

Reference 50

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source=arxiv_source observed=2026-07-31T00:47:51.256027Z digest=sha256:4d99bd149f766f2dee27f1df6c0bc119e90279c1a58ab09a619b86d39c10945c

Observation 0f7c7488-6157-44ed-ae85-ec0899b82ca3 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 51

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source=arxiv_source observed=2026-07-31T00:47:51.258986Z digest=sha256:7c66e6af44678dd66b8e4ad04bfa7d1a292a6d5ef00b9fbc5944ac7f127873a3

Observation 4dbe46aa-cb07-4e65-8aaf-982d79dc582b · outbound

This paper cites International Conference on Machine Learning , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Machine Learning , pages=

Reference 52

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source=arxiv_source observed=2026-07-31T00:47:51.261685Z digest=sha256:124abfdf3eb5091c8d69ee940cc9b3dcb60f8db4855b41fed62ad8033f1eb333

Observation 3ef28edf-4514-40b1-a3f1-8375add670d8 · outbound

This paper cites Proceedings of the 27th International Joint Conference on Artificial Intelligence , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the 27th International Joint Conference on Artificial Intelligence , pages=

Reference 53

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source=arxiv_source observed=2026-07-31T00:47:51.264576Z digest=sha256:de1954363e624bfafc9ed7ac71b24433fe11bca05083d44e0d3970462a70f580

Observation de1e8f5a-3b0a-456a-a002-75b51345f4bf · outbound

This paper cites Proceedings of the 37th International Conference on Machine Learning , pages =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the 37th International Conference on Machine Learning , pages =

Reference 54

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source=arxiv_source observed=2026-07-31T00:47:51.267536Z digest=sha256:7eac4b36a879e47481c6da1fb8289c304e9d6f9daf6e8844e491d80d376fa6f0

Observation b64dd735-12b1-484b-a0be-9fb0f8902b18 · outbound

This paper cites Experience Selection in Deep Reinforcement Learning for Control , journal =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Experience Selection in Deep Reinforcement Learning for Control , journal =

Reference 55

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source=arxiv_source observed=2026-07-31T00:47:51.270401Z digest=sha256:c7a6c37feded16d6dbdffeef8f8d2d8fdbafa169c19b68d53d8cad524407c621

Observation cc5ee217-eb50-419e-88d4-9e84a64239a6 · outbound

This paper cites an unresolved cited work.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Unresolved cited work

Reference 56

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source=arxiv_source observed=2026-07-31T00:47:51.273121Z digest=sha256:fb8f7389d82161558bbc8871f603d7c92925c90e77588905a70e2dc015a39a4e

Observation ef3f48f9-fc69-4e5a-9369-155390bc2a1d · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International conference on machine learning , pages=

Reference 57

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source=arxiv_source observed=2026-07-31T00:47:51.276164Z digest=sha256:52fda11d3dde9745ea16d074e0b0df55dbc70fe5d7eb91755b767664e5cb94b5

Observation b2f01ea4-e143-4332-8afc-2266d79db41d · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Learning Representations , year=

Reference 58

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source=arxiv_source observed=2026-07-31T00:47:51.278888Z digest=sha256:97e1356986228d26cdb5937ebd12919ada803e59bd6d183f57628db9039b945d

Observation 92163691-dd61-4f87-ad44-c8674771b19c · outbound

This paper cites Proceedings of the 40th International Conference on Machine Learning , pages =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the 40th International Conference on Machine Learning , pages =

Reference 59

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source=arxiv_source observed=2026-07-31T00:47:51.281512Z digest=sha256:a3f47f0ef88a845002a658d34da258ba7e7f9772fa395536fabe23b267b3a6c8

Observation aa3bd543-ceff-4859-ab3c-4dca1ca96051 · outbound

This paper cites Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence,.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence,

Reference 60

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source=arxiv_source observed=2026-07-31T00:47:51.284198Z digest=sha256:5c75f2f986e15e9b6fe3d8541412dd3fdeec4da053da426db7d6cd3668a04971

Observation aab31cad-ddde-4d0c-8a3d-c50a62bc7f9c · outbound

This paper cites No More Pesky Hyperparameters: Offline Hyperparameter Tuning for.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning No More Pesky Hyperparameters: Offline Hyperparameter Tuning for

Reference 61

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source=arxiv_source observed=2026-07-31T00:47:51.287072Z digest=sha256:cf2902dbe5436375d450c663c6a5dbc5582b7c5d74f2d122e5e7c0e2d4fd2107

Observation 0fdaedc8-5b1c-4a17-bc99-cf280463634a · outbound

This paper cites 2013 , journal=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning 2013 , journal=

Reference 62

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source=arxiv_source observed=2026-07-31T00:47:51.289768Z digest=sha256:9fb1a4596a4e96c7af6eedc4b429c864f1f0648a39fab9a34041c6ddf2f149bb

Observation 4a179583-7bca-4919-b4f7-e9f76f28ee6c · outbound

This paper cites International Conference on Learning Representations (ICLR) , year=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Learning Representations (ICLR) , year=

Reference 63

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source=arxiv_source observed=2026-07-31T00:47:51.292570Z digest=sha256:76baf2600cb4a66dbad08405032a0021f32ac8ba4fff82da1d2f890254a01b53

Observation 472f768a-6a7d-46db-b550-52c84a8cef89 · outbound

This paper cites Reinforcement Learning Conference , year =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Reinforcement Learning Conference , year =

Reference 64

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source=arxiv_source observed=2026-07-31T00:47:51.295192Z digest=sha256:4cc35fd543696684954003f97526bac784b0a0461878ac76bce099fc5a835834

Observation a4a7b849-4ea0-489a-9464-01d7f2c23a90 · outbound

This paper cites Reachability-Aware.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Reachability-Aware

Reference 65

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source=arxiv_source observed=2026-07-31T00:47:51.298022Z digest=sha256:9627cbf52ec8b193c65a9fc2285ce14f9f7d78bb52f4f0fce27b75178ed975e9

Observation 2726796e-27b9-4575-be55-851f0bd5ffa6 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in neural information processing systems , volume=

Reference 66

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source=arxiv_source observed=2026-07-31T00:47:51.300664Z digest=sha256:b45dd7605833d1465bee8018299ff225e1c7df0dbe6886000bb9b6c4b3a30e53

Observation d5a84089-6fd9-47f9-9bfa-d70c82916903 · outbound

This paper cites A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning , volume =.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning A Method for Evaluating Hyperparameter Sensitivity in Reinforcement Learning , volume =

Reference 67

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source=arxiv_source observed=2026-07-31T00:47:51.303398Z digest=sha256:035cf53f55c1a358889ff8827dd55ebb319136dc1307dc60f79ea84553fde181

Observation 8482040a-f0ff-4aaf-8260-a51378459d47 · outbound

This paper cites Medical Imaging with Deep Learning , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Medical Imaging with Deep Learning , pages=

Reference 69

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source=arxiv_source observed=2026-07-31T00:47:51.309217Z digest=sha256:d71d0fcb9ff9f96dc09238154cc80ea25c6a67bf0258cfcf3d6747b9e160ba34

Observation c604cdb3-0947-4294-a8c8-22a5e0e13178 · outbound

This paper cites SIAM Journal on Computing , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning SIAM Journal on Computing , volume=

Reference 70

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source=arxiv_source observed=2026-07-31T00:47:51.311905Z digest=sha256:c6748ba8f9f2f2790c1c478de903e1d614322585629ff2c0089c222bc16bec1d

Observation a545f962-8ae8-4130-945b-efb23160e31e · outbound

This paper cites an unresolved cited work.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Unresolved cited work

Reference 71

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source=arxiv_source observed=2026-07-31T00:47:51.314567Z digest=sha256:4d4886a691eb39bd8289eebdf2e289abb8c2addea9a99b1cfb5e59e75b605338

Observation 4946b300-bf26-4f3d-8f74-4d57b945c354 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 72

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source=arxiv_source observed=2026-07-31T00:47:51.317250Z digest=sha256:c439e40e074b2e3c44dda75b31eb4fdbb1002e5f041ac1f58d4c5f024782ddd5

Observation bbb72193-0d8e-4b17-ad4e-8de4f08a0db7 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International conference on machine learning , pages=

Reference 73

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source=arxiv_source observed=2026-07-31T00:47:51.320066Z digest=sha256:df7ed9ca8bb0e54955e52ed28577ed2bd36cd603a7d71bb80e993d364ca663a2

Observation f0e3eae7-ca3b-40f0-9aa5-620b17a19120 · outbound

This paper cites International Conference on Machine Learning , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Machine Learning , pages=

Reference 74

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source=arxiv_source observed=2026-07-31T00:47:51.322729Z digest=sha256:4125938e49cb6092f40ac012080e3cc5846cc211dadec8ad50da07862f6acacf

Observation 244772cd-4ba7-445a-8421-b06d152ca903 · outbound

This paper cites Machine learning , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Machine learning , volume=

Reference 75

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source=arxiv_source observed=2026-07-31T00:47:51.325559Z digest=sha256:3c2ca2f1adc35d81a9d86c03e2a2b557b2623bac24419d330197fab632843ec3

Observation 7fa5ac10-b90e-4571-a35b-0560ef8296e0 · outbound

This paper cites arXiv preprint arXiv:2509.15032 , year=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning arXiv preprint arXiv:2509.15032 , year=

Reference 76

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source=arxiv_source observed=2026-07-31T00:47:51.328272Z digest=sha256:26bc61c7bb4652865323b21108b728886b1755022ec9a9e0c55b1dd6a9af8eff

Observation eec46e78-c114-454d-b710-c99d8307723e · outbound

This paper cites Transactions on Machine Learning Research , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Transactions on Machine Learning Research , volume=

Reference 77

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source=arxiv_source observed=2026-07-31T00:47:51.330972Z digest=sha256:70683f109b2fdae692ad2ba6c3bb1d7bf65017aa0293f4dbd49ef8840f372dfe

Observation 9e476605-e3a3-4e92-bc3e-ba4eba5d651a · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 78

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source=arxiv_source observed=2026-07-31T00:47:51.333596Z digest=sha256:00b660fa13c51e0ea5f39864e73843f7e103f5c06986e4aa1bd40d82d532d956

Observation 8af38a6f-ab00-4a50-af06-e623c110c2db · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 81

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source=arxiv_source observed=2026-07-31T00:47:51.342233Z digest=sha256:17be49704e3644df11ca38b1485b0ee63777fb32e680ce95ccc58fff7897c766

Observation 2b487743-2185-4893-942b-0ad214f17e23 · outbound

This paper cites 2023 IEEE/CVF International Conference on Computer Vision (ICCV) , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning 2023 IEEE/CVF International Conference on Computer Vision (ICCV) , pages=

Reference 82

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source=arxiv_source observed=2026-07-31T00:47:51.344831Z digest=sha256:0e46e14e64bdc8a0c762f45163c62e29e7b53759afa698d782daaff28dd55bd2

Observation dd04982c-3034-4831-8c51-ca9cb281a5ce · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 83

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source=arxiv_source observed=2026-07-31T00:47:51.347580Z digest=sha256:edbaddfc42cac3bddfe39c15d055d8734bc1dfb04eda72abc5795e81450b0782

Observation daa60760-9818-4002-9edd-5692ec8c5564 · outbound

This paper cites Proceedings of the 28th International Joint Conference on Artificial Intelligence , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the 28th International Joint Conference on Artificial Intelligence , pages=

Reference 84

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source=arxiv_source observed=2026-07-31T00:47:51.350201Z digest=sha256:ef55b3d17d754fe4adbf6fa09d9bc259bc123e0bdb7b841e87c70d9152863e9e

Observation efec67d3-ec0a-4038-8ecf-d06171a1503f · outbound

This paper cites Frontiers in neurorobotics , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Frontiers in neurorobotics , volume=

Reference 85

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source=arxiv_source observed=2026-07-31T00:47:51.352696Z digest=sha256:614367d08720456de4d94cac9113447ab70f450109fb100dc789d41d76ebbc71

Observation b11b6407-79e6-483a-b699-65b223780e4d · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 86

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source=arxiv_source observed=2026-07-31T00:47:51.355082Z digest=sha256:53beee975a1aa960a541dbffeb437e0ce1b516997fa27b59d018f94ed1ee513f

Observation 15573386-0f9b-4571-a83b-74c0b0859388 · outbound

This paper cites Proceedings of the National Academy of Sciences of the United States of America , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the National Academy of Sciences of the United States of America , volume=

Reference 87

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no resolver link, observed 2026-07-31T00:47:51.357604Z

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source=arxiv_source observed=2026-07-31T00:47:51.357604Z digest=sha256:18a3ff0b4f17ad68c9c2bf2bc1389c816d66e9995c76c615da0c5aa39433b1de

Observation 00871f67-1c0f-458a-a823-68718eff5e04 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 88

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source=arxiv_source observed=2026-07-31T00:47:51.360203Z digest=sha256:fcf81285012be86bb828d82ff6c07d2fe99c5265310886da500117440ba093e7

Observation 39757fc9-691e-45c1-a3fe-1855e039e383 · outbound

This paper cites Transactions on Machine Learning Research , year=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Transactions on Machine Learning Research , year=

Reference 89

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source=arxiv_source observed=2026-07-31T00:47:51.362948Z digest=sha256:d1810b1ba969b8442e296f76ac4967224e0075da7a59bd20be29bf12b3ac768a

Observation dcd26718-28dc-436d-b57c-3c2b61721b6b · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Learning Representations , year=

Reference 90

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source=arxiv_source observed=2026-07-31T00:47:51.365558Z digest=sha256:41bde0aac4256c3855633c3f331fe00859dcb6913d492ce9873edf362adfbde8

Observation 330cf8da-5b93-4cf3-915d-7586212b4abd · outbound

This paper cites Applied Intelligence , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Applied Intelligence , volume=

Reference 91

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source=arxiv_source observed=2026-07-31T00:47:51.368111Z digest=sha256:1abaa3cb000cb4f2e3d55b26f845bd75de6f460b76d0204866ca8632ce4a403e

Observation 856b57c7-831e-4f62-9276-f22232da9ded · outbound

This paper cites Revisiting Prioritized Experience Replay: A Value Perspective.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Revisiting Prioritized Experience Replay: A Value Perspective

Reference 92

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source=arxiv_source observed=2026-07-31T00:47:51.370566Z digest=sha256:40ba31dc9a4adbdec4b03771ee161e96f9ab2d0cb89d41516786c14be3c6e5a1

Observation 915533a3-bcc4-4e8c-abbd-daaf99b7c917 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning The Eleventh International Conference on Learning Representations , year =

Reference 93

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source=arxiv_source observed=2026-07-31T00:47:51.373254Z digest=sha256:493265a1d18ee5c166cf2ae6e523dc741291af3ed25433ce80b7093829f9b7ef

Observation 4e18accf-f607-4f74-a613-1aea240238e9 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning The Twelfth International Conference on Learning Representations , year=

Reference 94

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source=arxiv_source observed=2026-07-31T00:47:51.375829Z digest=sha256:271ef2a33b880de767450873f5933356bf34602b4e2f1d68ead2960d58801774

Observation dc451ad3-3562-4bfc-b6bc-562f96f248ea · outbound

This paper cites International Conference on Machine Learning , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Machine Learning , pages=

Reference 95

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source=arxiv_source observed=2026-07-31T00:47:51.378509Z digest=sha256:265c8b7e83f995752b420e266efc67df1c9e519b9548d238f5e19fcf7d8fc2af

Observation bbc4f46d-6b72-4304-9e8c-f2f9587423a0 · outbound

This paper cites arXiv preprint arXiv:2512.01034 , year=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning arXiv preprint arXiv:2512.01034 , year=

Reference 96

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source=arxiv_source observed=2026-07-31T00:47:51.381407Z digest=sha256:23242862298fe70a8b7f369601c15466eafd02a27e206a7fc04b31f11d392dc3

Observation f70dd361-dff2-4e6c-809d-1e17df3933c4 · outbound

This paper cites Transactions on Machine Learning Research , issn=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Transactions on Machine Learning Research , issn=

Reference 97

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source=arxiv_source observed=2026-07-31T00:47:51.384157Z digest=sha256:f883bd04bf863f8508eb9012126fd9a14d6e969b893cd305bdef201eb19c05b9

Observation 626b81c8-0970-4776-bb6a-0fe1d17cb799 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 98

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source=arxiv_source observed=2026-07-31T00:47:51.386754Z digest=sha256:ac47872ea2b2ad73badbf65607c596ec7c51cd2481301299ceb5574fb7ca4cdc

Observation d5d41d7e-04b5-43e3-b086-55826a945dc5 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 99

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source=arxiv_source observed=2026-07-31T00:47:51.389250Z digest=sha256:68071696cb9e83e54ca4d3c3ae6f489d3b15ade78545494468eda596935b61b0

Observation 8cf99441-2b28-4475-a473-429642c36da7 · outbound

This paper cites International Conference on Machine Learning , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Machine Learning , pages=

Reference 100

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source=arxiv_source observed=2026-07-31T00:47:51.391764Z digest=sha256:ec58b05c248a9be7705343a650b9b268173f90f2a222781f9d3575d7593800db

Observation 6bf92801-822b-4fd9-8752-ff5bf75fdbf7 · outbound

This paper cites , booktitle=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning , booktitle=

Reference 101

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source=arxiv_source observed=2026-07-31T00:47:51.394303Z digest=sha256:b43c64c403983bfaeb7652f3942344ec0f10033e88da8e921bff957a1ca156c8

Observation 63350b18-2b1a-4012-87a0-42a88e1d2368 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in Neural Information Processing Systems , volume=

Reference 102

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source=arxiv_source observed=2026-07-31T00:47:51.397231Z digest=sha256:b48646e9ebecf68e74343a5b2303b59a559566a23e9516dc1f80f22dc7741d05

Observation 4c7b00cf-41f7-4e6c-af00-b945dc0df27d · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning International Conference on Learning Representations , year=

Reference 103

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source=arxiv_source observed=2026-07-31T00:47:51.399786Z digest=sha256:7341a46d83acb6c304b3bd390f0f1301c75127addbc3bd37180886b9243a4836

Observation 18a175fa-d86f-4fa3-aca7-51dccbcf15b5 · outbound

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

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Advances in neural information processing systems , volume=

Reference 104

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source=arxiv_source observed=2026-07-31T00:47:51.402403Z digest=sha256:3e6345c5c4afc74da5f7286315bd98a2d8dd64343ce1d9b920cdf345fa845ab2

Observation 6b3ceb3d-0553-4e19-a783-c58c5069abdf · outbound

This paper cites Learning for Dynamics and Control Conference , pages=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Learning for Dynamics and Control Conference , pages=

Reference 105

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source=arxiv_source observed=2026-07-31T00:47:51.405209Z digest=sha256:8017941716acf047d15b08d3ae909c322fbf4fdc85d9c53e7554487aaf4df9ef

Observation 3f4a6595-fa27-4cfa-812d-ca052af6dd47 · outbound

This paper cites Nature , volume=.

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning Nature , volume=

Reference 106

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source=arxiv_source observed=2026-07-31T00:47:51.407786Z digest=sha256:8440a94d842ab49ad40accc8a3ab1d38741630104a440ca9d155489c2dbb3140

Pith citing papers

No inbound Pith citation observations are available.