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Paper Citation Record · LEDGER

PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2406.12905.

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

pith.paper-citation-record.v1
2406.12905 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:57:40.035699Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T01:29:22.376416Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 7f1aee20-8479-4610-9cc4-a576405ad418 · inbound

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

Gymnasium: A Standard Interface for Reinforcement Learning Environments PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:29:49.500000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-11T17:29:49.186565Z digest=sha256:ae3eba08076c0c7dd660c80df9a9a7444a73800db5c6c5937f7fdaf707f1f227

Observation db7404eb-e5c0-4b34-a830-334337701ea0 · inbound

The challenge of hidden gifts in multi-agent reinforcement learning cites this paper.

The challenge of hidden gifts in multi-agent reinforcement learning PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T13:57:40.035699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:57:40.035699Z digest=sha256:c054298199e4775aac614171657ba1df811cac0a0de0d88d48544f879be47ecc

Observation 45f8d382-7bb5-44ef-a732-8d09c8df9a06 · inbound

Combining Pre-Trained Models for Enhanced Feature Representation in Reinforcement Learning cites this paper.

Combining Pre-Trained Models for Enhanced Feature Representation in Reinforcement Learning PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T18:51:58.571631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:51:58.571631Z digest=sha256:29720ac72c8c9ac95656d078f1d6a447059ade1a2e7724486a56054945e15718

Observation 90f46c78-a691-4335-bd15-fac083517cec · inbound

Scalable Option Learning in High-Throughput Environments cites this paper.

Scalable Option Learning in High-Throughput Environments PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-18T20:06:49.697339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-05-18T20:04:58.064472Z digest=sha256:74a4871142457224b35cc9bdd6e6eb484dce0db02333d53329b4248c55f514aa

Observation 5c6bc485-9575-4ff9-a1c2-f3c46bd62297 · inbound

Automatic Generation of High-Performance RL Environments cites this paper.

Automatic Generation of High-Performance RL Environments PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 20

Resolution
verified exact
arxiv_id, observed 2026-05-21T11:05:01.485239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-21T11:04:11.718672Z digest=sha256:3c33ed89fd2912491a99181304dc819f3a36222dd43e0fc023d5d129367877e7

Observation b466de6e-450e-468d-a3ca-1e3a786ffa26 · inbound

A High-Throughput Compute-Efficient POMDP Hide-And-Seek-Engine (HASE) for Multi-Agent Operations cites this paper.

A High-Throughput Compute-Efficient POMDP Hide-And-Seek-Engine (HASE) for Multi-Agent Operations PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:36:26.191830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-07T10:27:55.337253Z digest=sha256:8a979041282fed4151ffa663adb158dcc98be74e92c68023bb1dcfafbc050586

Observation e27902df-9854-42bf-b392-d4d79a8775cb · inbound

Equivariant Reinforcement Learning for Clifford Quantum Circuit Synthesis cites this paper.

Equivariant Reinforcement Learning for Clifford Quantum Circuit Synthesis PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:46:43.941390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-12T03:58:55.389930Z digest=sha256:a73106e906f851be297e06f75c31c32eed72fce7e1b33de1f84766e65b32a301

Observation 6d542ba8-78fd-4013-b0d6-b2849523dfb5 · inbound

CoPark: Learning Reactive Parking via Self-Play cites this paper.

CoPark: Learning Reactive Parking via Self-Play PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-07-02T03:36:29.819429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-28T09:52:45.407210Z digest=sha256:8f882784fc5bffd362dd5c962819334f01c349198f1f95b2d8f3b859b9e3777c

Observation dd39ac08-8dad-49d4-b895-5cff951c3f25 · inbound

TerraTransfer: Learning End-to-End Driving Policies Without Expert Demonstrations cites this paper.

TerraTransfer: Learning End-to-End Driving Policies Without Expert Demonstrations PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-07-03T18:38:49.989093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-27T02:27:51.946679Z digest=sha256:8a883c07a07f0e3a72f509858e0fe3be35eff5209d74269999b1b372ef05cb70

Observation 657f0e52-a255-41b6-acb8-7a6c76044372 · inbound

TerraTransfer: Learning End-to-End Driving Policies Without Expert Demonstrations cites this paper.

TerraTransfer: Learning End-to-End Driving Policies Without Expert Demonstrations PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-02T11:08:37.763307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:08:37.763307Z digest=sha256:1735ef25038512ac5bfa9434283cbec073de12695c60041ff891c1791528e31f

Observation 2ac989f6-7aa7-46f5-a8dc-7aae20cf8587 · inbound

Human-like autonomy emerges from self-play and a pinch of human data cites this paper.

Human-like autonomy emerges from self-play and a pinch of human data PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-03T14:28:32.004591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-27T07:01:12.737217Z digest=sha256:0be85dd2c2cfd0b479b6357bac05577f463106f5f7fb7e110e88d9fd2de78d6a

Observation dc75fd39-b52b-4269-83a7-da6589ea4b09 · inbound

Scaling Self-Play for End-to-End Driving cites this paper.

Scaling Self-Play for End-to-End Driving PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 100

Resolution
verified exact
arxiv_id, observed 2026-07-04T01:29:22.377860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-06-26T20:22:03.938518Z digest=sha256:15c68a6bdde36d8883022b357638aed5a04caf8613072d1e1647145edc54e220

Observation 6db98e29-7bfb-4f56-a6fb-1af29c203139 · inbound

Pictura: Perspective-View Self-Play at Scale for Driving cites this paper.

Pictura: Perspective-View Self-Play at Scale for Driving PufferLib: Making Reinforcement Learning Libraries and Environments Play Nice

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-01T00:58:58.420429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T00:58:58.420429Z digest=sha256:cfba7b268916f667ea53d131371dbac0e31986019d2aff3324cc8b0994ceaa0f