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Paper Citation Record · LEDGER

Rulebook: bringing co-routines to reinforcement learning environments

As of 18 August 2026, this Paper Citation Record lists 20 of 20 outbound references and 0 inbound Pith citation observations for arXiv:2504.19625.

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

pith.paper-citation-record.v1
2504.19625 v1

Coverage vector

measured 20 of 20 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:52:19.140298Z

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

20 of 20 outbound references displayed

  • verified exact0
  • verified fuzzy14
  • unresolved6
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 13cd5ea2-3b18-4a68-b3b6-d2a272aaf7ae · outbound

This paper cites Retargetable compiler case studies.

Rulebook: bringing co-routines to reinforcement learning environments Retargetable compiler case studies

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.532409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.033140Z digest=sha256:0acec791b70a849881111d23e7d2f7deba07c7a1ddd8aa660d811392dd0dfc47

Observation d64f8c6c-ffdc-4bae-97e0-a4b31fa4c1ed · outbound

This paper cites MLIR: A Compiler Infrastructure for the End of Moore's Law.

Rulebook: bringing co-routines to reinforcement learning environments MLIR: A Compiler Infrastructure for the End of Moore's Law

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-16T05:52:19.039407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:52:19.039407Z digest=sha256:9f34ee4568c8d585ae1fc63b44ba06fb2ed7413857c211d9d4fb5f749f54db2c

Observation e898757b-3198-4b31-8a82-f111159ab967 · outbound

This paper cites Compiling ONNX Neural Network Models Using MLIR.

Rulebook: bringing co-routines to reinforcement learning environments Compiling ONNX Neural Network Models Using MLIR

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-16T05:52:19.045608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:52:19.045608Z digest=sha256:256df09c5ea36af627e9778ca86a7f665163cac537f909ec901c3f708fa77de9

Observation b16b2f18-3409-4ead-9678-f83e4fd71295 · outbound

This paper cites Aiwarek: Compiling pytorch model for ai processor usi ng mlir framework.

Rulebook: bringing co-routines to reinforcement learning environments Aiwarek: Compiling pytorch model for ai processor usi ng mlir framework

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.515510Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.053053Z digest=sha256:8da824e94054b24da83f80b0ac2a947dc5af086714d3b87e5d367ca51318c6a3

Observation ae433534-50bc-41b6-82f4-02ccd4a8e0e3 · outbound

This paper cites Mlir: Scaling compiler infrastructure for domain specific computation.

Rulebook: bringing co-routines to reinforcement learning environments Mlir: Scaling compiler infrastructure for domain specific computation

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.499169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.061657Z digest=sha256:d1140d5b3bfbb36cc0d0a4ec218730084dd812ef7f80e09e7dca0abe67a91454

Observation 0f5526a6-6563-4e07-9503-07c473e9cf4d · outbound

This paper cites an unresolved cited work.

Rulebook: bringing co-routines to reinforcement learning environments Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-16T05:52:19.482948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.067672Z digest=sha256:d72232cbbf23ca941c6caddad69e6be07e44cc5b432a445d842a7c489996d328

Observation 5b88585a-b984-45ae-af30-7c2d75e674a0 · outbound

This paper cites A review of safe reinforcement learning: Methods, theory an d applications, 2024.

Rulebook: bringing co-routines to reinforcement learning environments A review of safe reinforcement learning: Methods, theory an d applications, 2024

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.466342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.074173Z digest=sha256:f7fa3f3094abfc461ec2cbb99e4002e9518c9205cb058710df6ab94f788b396c

Observation 2da5bab9-9357-48fc-8fec-177db1675e83 · outbound

This paper cites Openai gym, 2016.

Rulebook: bringing co-routines to reinforcement learning environments Openai gym, 2016

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.450094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.079324Z digest=sha256:550183df442c03f67ee0e0e9ba800b8d5029a2d69e170f8afb2b1f4214917ead

Observation c00f7750-0430-4c21-ad1b-784daf7394a5 · outbound

This paper cites Gymnasium: A Standard Interface for Reinforcement Learning Environments.

Rulebook: bringing co-routines to reinforcement learning environments Gymnasium: A Standard Interface for Reinforcement Learning Environments

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-16T05:52:19.084839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:52:19.084839Z digest=sha256:e468c5a621be7b7b722d30c9ecb5173576107619bb75fe43c265d36089430a5d

Observation 68e8df57-7a85-4f3a-a9f8-c1f52112bb84 · outbound

This paper cites Pgx: Hardware-accelerated parallel game si mulators for reinforcement learning.

Rulebook: bringing co-routines to reinforcement learning environments Pgx: Hardware-accelerated parallel game si mulators for reinforcement learning

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.427556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.090232Z digest=sha256:2ca8ad9aab06d9f7377b1b865949f7f34cb31b678215c5fbeeaf9fd420346a6c

Observation 3ca857cc-52d7-4104-83b7-a8615cbac22b · outbound

This paper cites OpenSpiel: A Framework for Reinforcement Learning in Games.

Rulebook: bringing co-routines to reinforcement learning environments OpenSpiel: A Framework for Reinforcement Learning in Games

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-16T05:52:19.095236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:52:19.095236Z digest=sha256:660e691824071b78b1a38bfdbe2be0a9fb00287a225cc6166897b48ca99e50bf

Observation b33276b5-d26c-4739-9b83-47624e6b42ca · outbound

This paper cites Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model.

Rulebook: bringing co-routines to reinforcement learning environments Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-16T05:52:19.100671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:52:19.100671Z digest=sha256:2fba362122f0559068e5a3e85ce98ac9f665fc54a1e1012b4a5ad13f174d58da

Observation d6f2fb3b-d118-4676-bcb0-4c08796bcf22 · outbound

This paper cites Muzero general: Open rei mplementation of muzero.

Rulebook: bringing co-routines to reinforcement learning environments Muzero general: Open rei mplementation of muzero

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.409794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.106195Z digest=sha256:f44f35b3dff52b3cf5f292470aaf1b9727937541f0db27efab58d8fba66f9a68

Observation 00972493-bedf-42d5-b4b4-64950c7e6a62 · outbound

This paper cites Mastering atari games with limited data.

Rulebook: bringing co-routines to reinforcement learning environments Mastering atari games with limited data

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.391003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.110797Z digest=sha256:05d412fb6c7a6ed18a186edebfd220017e6e837b633f8ac8ed58e7946debbe98

Observation 2a1ddf41-ec57-4331-9b19-b0d4f338c51b · outbound

This paper cites Dijkstra.

Rulebook: bringing co-routines to reinforcement learning environments Dijkstra

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.371213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.115993Z digest=sha256:ab66d3f05a4a44fb4cff8f9b9e31c6ad5d1f3af186d022d3af67d8768a79b02f

Observation bc485c1b-fac0-498d-8485-380a0122da90 · outbound

This paper cites The Art of Computer Programming, 3rd edition.

Rulebook: bringing co-routines to reinforcement learning environments The Art of Computer Programming, 3rd edition

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.352270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.120773Z digest=sha256:50235d91b69f33da594ca6ed02ba44cd7e75edd446277eaefeecc8b3d680476e

Observation 424a0a67-5708-4549-943e-cc1bb502c5ca · outbound

This paper cites Hopcroft, Rajeev Motwani, and Jeffrey D.

Rulebook: bringing co-routines to reinforcement learning environments Hopcroft, Rajeev Motwani, and Jeffrey D

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.334852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.125711Z digest=sha256:317f4b3de788f0ab051713601ab168dd7ca48833b5aecb8107cb9a9bdcb208ca

Observation f8d7563f-dd2e-4264-8871-36959da1b070 · outbound

This paper cites Hanabi learning environment.

Rulebook: bringing co-routines to reinforcement learning environments Hanabi learning environment

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.315161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.130505Z digest=sha256:c27d1b34c4f6f82e9b8f26b92c76b13817e152d023c9517b66c22520f378a531

Observation fc5baf2d-c947-4007-93ed-21a3c4e6a44d · outbound

This paper cites google-benchmark.

Rulebook: bringing co-routines to reinforcement learning environments google-benchmark

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.297703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.135141Z digest=sha256:2f1d00886a937eff34ae2fa67b764fb454d1451320db72da7829cccca0da8e4e

Observation 8b240f89-7095-42d7-b17f-17728c36c1b6 · outbound

This paper cites Warhammer 40.000, 10th edition.

Rulebook: bringing co-routines to reinforcement learning environments Warhammer 40.000, 10th edition

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T05:52:19.279682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-16T05:52:19.140298Z digest=sha256:e677c2d4d831c98237f3339910f83bc3afd0aa0b4ffd4e296048f66a86037da4

Pith citing papers

No inbound Pith citation observations are available.