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Paper Citation Record · LEDGER

Endpoint Replay: Compressing the Recency Buffer in Deep Reinforcement Learning

As of 7 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 2026-08-07T06:34:17.273281+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

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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source=arxiv_source observed=2026-07-31T00:47:51.111968Z digest=sha256:3eb2df7a88bd26b2a54a62163934e199ce1ab1db448b963d8fb05fb5b4a4abc6

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=sha256:2e35c5f86769ec48df25b22ac2fb3eaaab91a85ffeab3b9555aba4a5dea729eb

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:b1f69a9e04bb99ba21742a772dcb1b20af41f723ba1cd902264871e281af541c

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=sha256:1b65aedd0fb262fe2e38861d333767701ece2b25e56ef5ae6c467ad4d8fde74d

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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source=arxiv_source observed=2026-07-31T00:47:51.134917Z digest=sha256:2d1edf1ebd7eb6f9acb8999f444a4c3aaa9ba296dc1c7c71da160552bc9c29e8

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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source=arxiv_source observed=2026-07-31T00:47:51.143802Z digest=sha256:522cb914dcb20c1d91c1a3e1a843c73073393c27a0c4e1e4ea47c1d57bb21228

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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source=arxiv_source observed=2026-07-31T00:47:51.160903Z digest=sha256:99aed7458de1115724275742a6937593ab5313ca389f55bacac2aa656694989d

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:e8b9546c9a7a3fb7c317e9652913192014ce78fad3064f62b41f4a603644602c

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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source=arxiv_source observed=2026-07-31T00:47:51.210879Z digest=sha256:d0a88a6065a01bf33b4de009e95551cd40910e20118a277cd36cf524dfdfad25

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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source=arxiv_source observed=2026-07-31T00:47:51.235131Z digest=sha256:6d09736d8f6f811cb16817bf3af19fcaf55048dd146ce3245cddc3cc9e03fd1a

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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source=arxiv_source observed=2026-07-31T00:47:51.238145Z digest=sha256:49436b3c36267416fc7c0c552a6eda3d0902e4ac5420ff19c2a17f7be697000b

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=sha256:2bcfeaf2dc1957632ffe1b7e1e03f056d77d1ed4b32aa16ffbcd2144f493c881

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=sha256:5416d15e7f54e1a2a6f58163e47a5a16f5757a540a57447d001420cfdbef7205

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:e20e3825f952522f3db6ceb148342811124f5c07ff12585dec1c238a147b0014

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=sha256:88069bbe42550c965b33002fa8bf7852c0100162b03bc30ad1df95c99a04b4bf

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:b1b2f4c171150232a9f2cac6ae4cd189d752f95f520d11eb1c22ecbf10b96b1b

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:ba3be48c175ed8a91f2cf6aef7ddc4fae9505610347d68bc755d488b470c3da5

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=sha256:00ac2c55d07fea1d6718d920eae7e269edff4a809cbb145f85beb081f2cd9dac

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:dde88e4451c4b71b274a765d8a399fedfabc28d3de8be3f9660ea0c730551d3c

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=sha256:3af0220f361bf372dadaadd13cd70a7baa765791352d1e6f1763078cc7189f59

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=sha256:367da0d1d89fc12a22e263a6cdbe079f6aa61defd8586ff954b10deb8d23ee27

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=sha256:860a78e3ab1551648ffea7cc0aea4565bd5aedc468451e6ebf11d09ac36da837

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=sha256:41d22189fa89f1e20f2d79537f7ec22517d0dea03adbc94aa9d716d45dd25d62

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=sha256:7f3f1f039aa29b43b9e9679c1996084ceb127e2b3738f333a15aad2245825c35

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=sha256:8b5d3c208f840387638a5c8c9e46f4c56c4b0bac8dfb237d12e9be4c8f9c35b8

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=sha256:0085049d6cdd2b57854a151ff2f4e30756a8adb4372bcdee0b295ca458d14d7c

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=sha256:4776ba9c6e829d32d884dc68b40c70ba953504d27678feec0aadc0e7402f5506

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:a9ba395ae46a567573a7a11bdd0dfe2e15771be0838e78f148d9aa9f19e3ebb0

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:b18ab4aa3b6da3b35b6053d78aa05b04cb496e381f346b4516a78ead18dd1cc3

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=sha256:7af4ac4c9d90af624bb095b2004b42cbe5a6154b3d5865ca70855be2e43aefe2

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=sha256:2a0b2b5f05b3efa00c69650d0cf45d82dc0217dd6e52c6fe5f282e8e4706b3ce

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:fa4743d1d9767e0e2f1845acdf3c41dca6916d00bd894ea0feec60b52d52ea4a

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:ce89d239c95eeea55db9878c250990d84ab61b41c92258207a92c7878378e5fc

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=sha256:40c8872bc0c59bc6c8edf1783ea68e6fc3e93468e4afe574afe7c65d02a726c5

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=sha256:71f11e6e9d0f73a74b4f6a865d21b0f19f56ce4fd32f154004b04cae6ef3a82b

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=sha256:7b51c1820ac3b73b5cfd7527c426ac224cb2ac3894f2f5f6136e340cf2add503

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:a988b7116f3db59369b2ae72b0e0c0e5d5d39d1f683f4d90422452984e05a42d

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=sha256:2b2ede49b0a1c81355733b181804cd635d6b59e40e18280274f0b1c73cb6877d

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=sha256:0146ec6e84fdf1f5e1b24917835053e6386f9fd90f7e4d0a708c47a1e3f8bb6f

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=sha256:22568a7ac4800baa0cbe6a8590ae9ba70ab3e4579bd7930318107ef126871cfd

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:f35ef1232d689bf978b646f90bb9d1524b8c50c1c74af07b14febcad9a3f6b00

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=sha256:3c9c356f04870077dde6612b1b4413c5e611451176a7b920038af7d0dc7c4a32

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:cde85a22719c4c0e0e722509db7d096c114ccca2d3a07e1c397b091088079283

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:b2c0790c8df68f9522aecb06922789515ad06d505b3933a7d6741e32e8cf48be

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=sha256:089b0ed312eb506503c5c988be9090959438b10fc7b46fa2177da56b2e714905

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:bfcd4acefaf47ffce14d43b75d9f4c9d6e44d15190e3c3913c263327a2a6b7f7

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=sha256:7e4a4344e45665960ee21f6bae23c4924c23d69719dd3b5b767b49bdd491ad05

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=sha256:722ac09f1a7f7fb40c94b591635fe8f1fb7b99bcab6c0df3238c4a097b8d6807

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:c7a10f71c1cf64350c46db2441fd6754358839028bf9fa130266aeeccb5fbec3

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:c96631c388ead0dfe3fcbe2cad036de30badcecf8f1784728efe1412bb8ed18e

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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source=arxiv_source observed=2026-07-31T00:47:51.357604Z digest=sha256:f5dcb5d2d6f1e1142d6adcf3b44e1832c23e3624923b8b5e1e9712b79273926e

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:d96e7c825159da81d7e29b8649d8d78351ade09cdd7885ee9877fa1580fe0fc9

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:df7655ecf0aafc8cd439cd71d164171c5435b8ab41124e4f159131fab4847166

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=sha256:0cbd9066b1d45a7d8bde1ccce41c38aa0ba056d6d9a67ffb25c43adf849ceb39

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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no resolver link, observed 2026-07-31T00:47:51.368111Z

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source=arxiv_source observed=2026-07-31T00:47:51.368111Z digest=sha256:0cb8cf7e683f47f7c6969a9fe3e0ff1ca8be20fd58082adc87045c01805c9d29

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=sha256:6fbddbef2d0b33209ee1b572ddccdeaa6511df0cdb8dfa9e3463343f02ebe4e6

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:f53109874f8b54e452604cc3f509ed358c7f4aa5c3d5ee6cedcaef5323c65f3a

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=sha256:0d90a2ef673ddc1d7e41a317e12c168bc4d6982dde9e6b261db0d817b34cabf5

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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no resolver link, observed 2026-07-31T00:47:51.378509Z

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source=arxiv_source observed=2026-07-31T00:47:51.378509Z digest=sha256:22656579c095279308e8d5f830f02a7793425b3ee5cf4c0a74a28961e85ed102

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=sha256:22c93ee58a1e319b146b57864a49a7fc686fe4bbd8f90fc2ac685cf64bfffbd8

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=sha256:6838041802e3c98eadaed286d06af0c4c8ae4f137627dca4e0d1b364b283618b

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=sha256:2958d3ec6af00c62d9b6e94099b6161c217222a5a03716d556d845b9432d69ca

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=sha256:1d0c34f01591ca0aa05271c6419e5ab7c744f94807d17d6f3f245123bf457df6

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=sha256:286e663d2dab24054a57fe7880aad85d761ea424134d0e4b9c4c98ad6360e0a5

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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no resolver link, observed 2026-07-31T00:47:51.394303Z

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source=arxiv_source observed=2026-07-31T00:47:51.394303Z digest=sha256:cf14f397f138b8e7575a6cd6738e60c1d6ce0014890662aef7b49d511b3e3f3d

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=sha256:409fee255e8809312c8cdaa0150fffd4d8cb569107e56b9e2d83cea7363c9573

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=sha256:544d82c47e4b2ce5fbff951d2cb575f789debb9cd74a6b9f7b59744ba255d340

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:ad4cc2b149a1d3c514622186cfa171ab221ea1ff012165411709318b9f74b3d2

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=sha256:4a61f09e9a3decd5e8cf12bbac7a0f90564a874d5ee51ad8374bb8bb746fb465

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=sha256:9ae0b8d67d32d805d7f1a25eb51c9eea50d78bd3e6b020be66227104d87c836b

Pith citing papers

No inbound Pith citation observations are available.