Paper Citation Record · LEDGER

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch

As of 14 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 2 inbound Pith citation observations for arXiv:1909.01500.

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

pith.paper-citation-record.v1
1909.01500 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:19:09.239168Z

measured 38 of 38 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:22:09.716785Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T13:25:20.593899Z

Reference resolution

36 of 36 outbound references displayed

verified exact0
verified fuzzy10
unresolved26
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ee727af1-0c2d-4cf6-8fd0-270121f07507 · outbound

This paper cites Playing Atari with Deep Reinforcement Learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Playing Atari with Deep Reinforcement Learning

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.072128Z

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Observation 4c79b4e0-7a25-4270-98e1-6f6823e0cc88 · outbound

This paper cites Trust region policy optimization.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Trust region policy optimization

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.078409Z

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Observation 40dfdb77-ff30-4630-9d08-5721f4fe8af0 · outbound

This paper cites Automatic differentiation in PyTorch.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Automatic differentiation in PyTorch

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.083402Z

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Observation 0ce29919-2576-4037-89bd-dfdadb2617f1 · outbound

This paper cites Alphastar.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Alphastar

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:19:09.774152Z

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.

Observation 7341aaff-8341-4d70-a4f8-7a0501821e62 · outbound

This paper cites Openai ﬁve.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Openai ﬁve

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.093052Z

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Observation 532c3c91-0ed4-417b-8fda-182bfec2589a · outbound

This paper cites Recurrent experience replay in distributed reinforcement learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Recurrent experience replay in distributed reinforcement learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:19:09.747802Z

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.

Observation 05be1ce0-186d-4ea7-8abd-cdabb46eced9 · outbound

This paper cites Openai gym, 2016.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Openai gym, 2016

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.102296Z

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Observation 91b2453c-1b24-42e0-bb52-358795a52a8f · outbound

This paper cites Asynchronous methods for deep reinforcement learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Asynchronous methods for deep reinforcement learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.106629Z

Source-reported events for the cited work

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Observation 433f9895-e312-4791-b09f-f74779a9cc46 · outbound

This paper cites Proximal Policy Optimization Algorithms.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Proximal Policy Optimization Algorithms

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.111092Z

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Observation 31e71905-a7b0-4fc4-ad7d-06ce1bd82dec · outbound

This paper cites Deep reinforcement learning with double q-learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Deep reinforcement learning with double q-learning

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:19:09.712516Z

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.

Observation ac7a8f62-c5ea-4d1e-9fe4-c26c5c789f60 · outbound

This paper cites Dueling Network Architectures for Deep Reinforcement Learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Dueling Network Architectures for Deep Reinforcement Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.121127Z

Source-reported events for the cited work

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Observation 8067a7a9-2fed-4f15-b86b-375b2c35d75b · outbound

This paper cites A distributional perspective on reinforce- ment learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch A distributional perspective on reinforce- ment learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:19:09.697643Z

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.

Observation 2cb9aac9-b65d-4d20-a1f5-711632c8cb6d · outbound

This paper cites Rainbow: Combining improvements in deep reinforcement learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Rainbow: Combining improvements in deep reinforcement learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:19:09.680384Z

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.

Observation 20c04ee0-549f-4d4d-93a7-531168ba3ab4 · outbound

This paper cites Distributed Prioritized Experience Replay.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Distributed Prioritized Experience Replay

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.134917Z

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Observation d8e12ed6-839e-455c-a176-fc0925a7dd36 · outbound

This paper cites Implicit Quantile Networks for Distributional Reinforcement Learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Implicit Quantile Networks for Distributional Reinforcement Learning

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.139219Z

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Observation db2b5157-2bbd-472a-a24d-654f0c7d5180 · outbound

This paper cites Continuous deep q-learning with model-based acceleration.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Continuous deep q-learning with model-based acceleration

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.144002Z

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Observation 9753ee44-b572-4930-9919-d3b185e347d4 · outbound

This paper cites Addressing Function Approximation Error in Actor-Critic Methods.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Addressing Function Approximation Error in Actor-Critic Methods

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.148298Z

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Observation 42ad99cc-37ac-44f4-808c-feb29af19c4b · outbound

This paper cites Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.153918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd02575e-29ed-425d-a429-d737560c5d33 · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Soft Actor-Critic Algorithms and Applications

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.159727Z

Source-reported events for the cited work

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Observation c8413eae-e346-4bcd-8e46-3e269d1fa5cb · outbound

This paper cites Distributed Distributional Deterministic Policy Gradients.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Distributed Distributional Deterministic Policy Gradients

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.165087Z

Source-reported events for the cited work

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Observation 7bc417dd-f7dc-4eaa-9d4a-58301850b34d · outbound

This paper cites Prioritized Experience Replay.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Prioritized Experience Replay

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.170057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8db25fa9-0c94-4297-919e-579686a8bd8e · outbound

This paper cites The arcade learning environment: An evaluation platform for general agents.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch The arcade learning environment: An evaluation platform for general agents

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.174352Z

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Observation 98c0d123-7b6c-40aa-98f9-fa478a6dd09d · outbound

This paper cites Mujoco: A physics engine for model-based control.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Mujoco: A physics engine for model-based control

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.178979Z

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Observation 2b9a4144-fef1-4762-9cb8-74f30c148890 · outbound

This paper cites Accelerated Methods for Deep Reinforcement Learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Accelerated Methods for Deep Reinforcement Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.183570Z

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Observation 4f22f19d-c9e5-4953-802e-27a8fea1562f · outbound

This paper cites Openai spinning up.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Openai spinning up

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:19:09.635508Z

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.

Observation 89e8521c-c76f-4522-a235-5b25ad259f33 · outbound

This paper cites Theano: new features and speed improvements.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Theano: new features and speed improvements

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.193455Z

Source-reported events for the cited work

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Observation 608edfe3-7719-4b08-bf07-bfc6426c76be · outbound

This paper cites An Empirical Model of Large-Batch Training.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch An Empirical Model of Large-Batch Training

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.198199Z

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Observation 1ebe22d1-d061-47ae-9489-d88134d99935 · outbound

This paper cites Benchmarking deep reinforcement learning for continuous control.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Benchmarking deep reinforcement learning for continuous control

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.202760Z

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Observation 0de24811-f854-4f53-8642-34621f9224a2 · outbound

This paper cites Openai baselines.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Openai baselines

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:19:09.609831Z

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.

Observation 79b021e3-4ea5-4886-b20f-e5b9d1ff7f70 · outbound

This paper cites Dopamine: A Research Framework for Deep Reinforcement Learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Dopamine: A Research Framework for Deep Reinforcement Learning

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.211753Z

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Observation b0761670-d21a-4574-b7d2-54a1d3ef2a3c · outbound

This paper cites Tensorﬂow: A system for large-scale machine learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Tensorﬂow: A system for large-scale machine learning

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:19:09.594816Z

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.

Observation 723cded4-26b8-4ade-a27c-b71d298e3f7f · outbound

This paper cites RLlib: Abstractions for Distributed Reinforcement Learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch RLlib: Abstractions for Distributed Reinforcement Learning

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.220509Z

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Observation 19b4a751-53ef-4531-8ffc-363a2908f03a · outbound

This paper cites Ray: A distributed framework for emerging{AI} applications.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Ray: A distributed framework for emerging{AI} applications

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:19:09.580166Z

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.

Observation 3f75761d-a2b1-46fb-8592-5ef783c64fe5 · outbound

This paper cites Horizon: Facebook's Open Source Applied Reinforcement Learning Platform.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Horizon: Facebook's Open Source Applied Reinforcement Learning Platform

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.230237Z

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Observation 21dae2e6-90c6-4ae4-b291-86cce34f19dd · outbound

This paper cites Hogwild: A lock-free approach to parallelizing stochastic gradient descent.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch Hogwild: A lock-free approach to parallelizing stochastic gradient descent

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T05:19:09.563270Z

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.

Observation 0ce2a332-97e6-4e8b-a248-e6440d32b5c1 · outbound

This paper cites cuDNN: Efficient Primitives for Deep Learning.

rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch cuDNN: Efficient Primitives for Deep Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-14T05:19:09.239168Z

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Pith citing papers

Observation 5130b66b-b7bf-41fc-a2e8-19851e9801e3 · inbound

Towards Fault Tolerance in Multi-Agent Reinforcement Learning cites this paper.

Towards Fault Tolerance in Multi-Agent Reinforcement Learning rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-12T05:22:09.716785Z

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Observation b0bd5300-83ce-46a4-98d1-076dbd8826fe · inbound

Tilted Quantile Gradient Updates for Quantile-Constrained Reinforcement Learning cites this paper.

Tilted Quantile Gradient Updates for Quantile-Constrained Reinforcement Learning rlpyt: A Research Code Base for Deep Reinforcement Learning in PyTorch

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-11T13:25:20.601321Z

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.