Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:1903.03176.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-14T04:26:46.686445Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-09T21:36:34.225692Z
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 b918eef3-a7da-4d4f-b861-6ee4a0c7baba · inbound
Gymnasium: A Standard Interface for Reinforcement Learning Environments cites this paper.
Gymnasium: A Standard Interface for Reinforcement Learning Environments MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T17:29:49.654592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ef038293-fdcc-45c4-82bc-f97c3cd34239 · inbound
Reinforcement Learning with Discrete Diffusion Policies for Combinatorial Action Spaces cites this paper.
Reinforcement Learning with Discrete Diffusion Policies for Combinatorial Action Spaces MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 67
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T21:15:38.644092Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0cf72884-7100-409c-863b-6d2a3d944c03 · inbound
Intentional Updates for Streaming Reinforcement Learning cites this paper.
Intentional Updates for Streaming Reinforcement Learning MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 45
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T12:21:06.679791Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c8fcc11d-03cd-48e7-9a9a-65a8931db6ed · inbound
Extending Differential Temporal Difference Methods for Episodic Problems cites this paper.
Extending Differential Temporal Difference Methods for Episodic Problems MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T06:35:38.858398Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 40f185c2-cde6-4f7c-b6f5-009fe319950c · inbound
Revisiting Adam for Streaming Reinforcement Learning cites this paper.
Revisiting Adam for Streaming Reinforcement Learning MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T04:40:58.208525Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b5405a6d-775e-45da-8970-2d2897b6e8da · inbound
Discrete Flow Matching for Offline-to-Online Reinforcement Learning cites this paper.
Discrete Flow Matching for Offline-to-Online Reinforcement Learning MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 29
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-13T05:52:22.624571Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fb053806-a33c-47bb-beab-c950073b87cb · inbound
OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation cites this paper.
OrderGrad: Optimizing Beyond the Mean with Order-Statistic Policy Gradient Estimation MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 107
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T12:16:57.040883Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5e616642-1be8-46f7-ac8a-6a398df0787d · inbound
Preserving Plasticity in Continual Learning via Dynamical Isometry cites this paper.
Preserving Plasticity in Continual Learning via Dynamical Isometry MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 16
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-03T00:07:28.501091Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 83a77ba6-2bd8-42d8-9f44-3f48855ce044 · inbound
Learning the ARTS of Search for Automated Discovery cites this paper.
Learning the ARTS of Search for Automated Discovery MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 59
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T08:09:41.769209Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 00e35e0e-3e44-48d6-8502-86f8459397d7 · inbound
Heuresis: Search Strategies for Autonomous AI Research Agents Across Quality, Diversity and Novelty cites this paper.
Heuresis: Search Strategies for Autonomous AI Research Agents Across Quality, Diversity and Novelty MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 68
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T18:40:02.664185Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 916e2a4b-4c82-4d38-9077-0452b1bf43de · inbound
Heuresis: Search Strategies for Autonomous AI Research Agents Across Quality, Diversity and Novelty cites this paper.
Heuresis: Search Strategies for Autonomous AI Research Agents Across Quality, Diversity and Novelty MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 69
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T21:17:23.792386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c81a9206-8b9f-4fdd-b341-ba47ea3ea026 · inbound
Position: RL Researchers Need to Distinguish Between Solving Simulators and Using Simulators as a Proxy cites this paper.
Position: RL Researchers Need to Distinguish Between Solving Simulators and Using Simulators as a Proxy MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T15:25:48.462270Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8bf67191-4491-4e86-bf54-e32852da6ae5 · inbound
Gimitest: A Comprehensive Tool for Testing Reinforcement Learning Policies cites this paper.
Gimitest: A Comprehensive Tool for Testing Reinforcement Learning Policies MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 34
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-09T21:36:34.228213Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f4c43d8d-61d7-4da8-acf0-13d5560d9f91 · inbound
Auditing the Risk Claims of Distributional Reinforcement Learning cites this paper.
Auditing the Risk Claims of Distributional Reinforcement Learning MinAtar: An Atari-Inspired Testbed for Thorough and Reproducible Reinforcement Learning Experiments
Reference 86
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T04:26:46.686445Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.