Paper Citation Record · LEDGER

RLBenchNet: The Right Network for the Right Reinforcement Learning Task

As of 7 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 1 inbound Pith citation observation for arXiv:2505.15040.

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

pith.paper-citation-record.v1
2505.15040 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:28:36.790121Z

measured 31 of 31 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:05:07.831643Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T05:05:07.890229Z

Reference resolution

30 of 30 outbound references displayed

verified exact0
verified fuzzy16
unresolved13
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c6106fea-1de2-43bd-88c1-f064a50f103d · outbound

This paper cites What matters in on-policy reinforcement learning? a large-scale empirical study, 2020.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task What matters in on-policy reinforcement learning? a large-scale empirical study, 2020

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:41.938153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f99f2355-1bc8-4c2c-af04-2fad1097b93c · outbound

This paper cites an unresolved cited work.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T15:28:33.282105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 959058a0-368f-4807-9fe7-87f25a6ef6e0 · outbound

This paper cites an unresolved cited work.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:28:41.670666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0af9d966-68b8-4da4-9841-1f4664e5c7dc · outbound

This paper cites Kovalev, and Aleksandr I.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Kovalev, and Aleksandr I

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:41.438864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f4302e45-ad40-4aaa-bf2f-d0656927aaa6 · outbound

This paper cites Minigrid & miniworld: Modular & customizable reinforcement learning environments for goal-oriented tasks, 2023.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Minigrid & miniworld: Modular & customizable reinforcement learning environments for goal-oriented tasks, 2023

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:41.211628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 79cc64d2-2fff-4366-90b6-451c7b92622b · outbound

This paper cites Empirical evaluation of gated recurrent neural networks on sequence modeling, 2014.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Empirical evaluation of gated recurrent neural networks on sequence modeling, 2014

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T15:28:33.788457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cad80d92-8636-4b54-a4c6-8c27093eac20 · outbound

This paper cites Le, and Ruslan Salakhutdinov.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Le, and Ruslan Salakhutdinov

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T15:28:33.909597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 25f3b796-ca9d-475f-b969-3f42124e8064 · outbound

This paper cites Transformers are ssms: Generalized models and efficient algorithms through structured state space duality, 2024.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Transformers are ssms: Generalized models and efficient algorithms through structured state space duality, 2024

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:40.997531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ac5bf077-82ac-44d3-b52d-d5b77df93f78 · outbound

This paper cites Addressing function approximation error in actor-critic methods.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Addressing function approximation error in actor-critic methods

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:40.719291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3cb30f82-13a3-476f-8bef-461584aee8f8 · outbound

This paper cites Mamba: Linear-time sequence modeling with selective state spaces, 2024.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Mamba: Linear-time sequence modeling with selective state spaces, 2024

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T15:28:34.339686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79fc7973-4af8-420d-9a92-4a68c75c8cb0 · outbound

This paper cites Safe multi-agent reinforcement learning for multi-robot control.Artificial Intelligence, 319:103905, 2023.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Safe multi-agent reinforcement learning for multi-robot control.Artificial Intelligence, 319:103905, 2023

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T15:28:34.462727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83232638-4bd6-41a4-84fc-00c1b75aece6 · outbound

This paper cites Safe and balanced: A framework for constrained multi-objective reinforcement learning.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Safe and balanced: A framework for constrained multi-objective reinforcement learning.IEEE Transactions on Pattern Analysis and Machine Intelligence, 2025

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:40.474550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e4aa36a4-8f82-44c3-9459-8e32a412ba21 · outbound

This paper cites Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor, 2018.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor, 2018

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T15:28:34.737787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bba726a9-a79f-4f66-936a-e9f0be26ca87 · outbound

This paper cites Long short-term memory.Neural computation, 9(8):1735–1780, 1997.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Long short-term memory.Neural computation, 9(8):1735–1780, 1997

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T15:28:34.828624Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3e2b146-19c2-4334-954b-2e5eb1e22cff · outbound

This paper cites The 37 implementation details of proximal policy optimization.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task The 37 implementation details of proximal policy optimization

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T15:28:34.979587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 996a4878-2a4d-4e5f-a1c8-5791e6ba4936 · outbound

This paper cites an unresolved cited work.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:28:39.966752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c0013807-108f-4a30-ba82-095d37b8792d · outbound

This paper cites Decision mamba: Reinforcement learning via hybrid selective sequence modeling, 2024.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Decision mamba: Reinforcement learning via hybrid selective sequence modeling, 2024

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:39.702547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3ba1c3c0-f64a-49f6-a824-1acc9db8bb54 · outbound

This paper cites Du, and Huazhe Xu.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Du, and Huazhe Xu

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:39.471916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bbd87fdd-e57a-44b2-bedc-0657196f08e6 · outbound

This paper cites Efficient recurrent off-policy RL requires a context-encoder-specific learning rate.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Efficient recurrent off-policy RL requires a context-encoder-specific learning rate

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:39.170120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2a1c6f3f-f8ee-4dd5-b4c4-48f014ae176c · outbound

This paper cites Decision mamba: A multi-grained state space model with self-evolution regularization for offline rl, 2025.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Decision mamba: A multi-grained state space model with self-evolution regularization for offline rl, 2025

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:38.809913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d29e2f8f-3b87-4eb5-a936-b175e1663822 · outbound

This paper cites Popgym: Benchmarking partially observable reinforcement learning, 2023.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Popgym: Benchmarking partially observable reinforcement learning, 2023

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:38.519287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b2b295c3-ef45-4214-90ae-3fa2b1792084 · outbound

This paper cites When do transformers shine in rl? decoupling memory from credit assignment, 2023.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task When do transformers shine in rl? decoupling memory from credit assignment, 2023

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:38.227986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0b568af3-cf56-4d9a-8073-3086ca7d744a · outbound

This paper cites Decision mamba: Reinforcement learning via sequence modeling with selective state spaces, 2024.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Decision mamba: Reinforcement learning via sequence modeling with selective state spaces, 2024

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:37.933547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a6e0cc61-88c0-4881-b376-71a9166ddc2d · outbound

This paper cites Francis Song, Jack W.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Francis Song, Jack W

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:37.694539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 896e1418-ee3c-4b2f-98cd-e6c2d2b0e9d9 · outbound

This paper cites Transformerxl as episodic memory in proximal policy optimization.Github Repository, 2023.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Transformerxl as episodic memory in proximal policy optimization.Github Repository, 2023

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:37.480182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 806735a1-f767-4017-89ef-f929645697fd · outbound

This paper cites Memory gym: Towards endless tasks to benchmark memory capabilities of agents, 2024.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Memory gym: Towards endless tasks to benchmark memory capabilities of agents, 2024

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:28:37.293317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 094d1ed2-1d67-4e4e-b3d8-ac6d31fa2498 · outbound

This paper cites Proximal policy optimization algorithms, 2017.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Proximal policy optimization algorithms, 2017

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T15:28:36.638559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca03cca5-66c7-480e-b7cb-686f2195a7ca · outbound

This paper cites Mas- tering the game of go with deep neural networks and tree search.nature, 529(7587):484–489, 2016.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Mas- tering the game of go with deep neural networks and tree search.nature, 529(7587):484–489, 2016

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T15:28:36.723806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed1e8e2f-396c-41eb-adba-8127e43dcef3 · outbound

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

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Mujoco: A physics engine for model-based control

Reference 29

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T15:28:37.050856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b7625643-bee5-4928-9685-38c8dfbd0af1 · outbound

This paper cites an unresolved cited work.

RLBenchNet: The Right Network for the Right Reinforcement Learning Task Unresolved cited work

Reference 2022

Resolution: unresolved; raw_fallback, observed 2026-08-07T15:28:40.268447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation d9610706-0245-42e6-82d7-53dc9175e2f6 · inbound

Reward Structure Shapes the Interaction Between Episodic Exploration and Neural Memory in Reinforcement Learning cites this paper.

Reward Structure Shapes the Interaction Between Episodic Exploration and Neural Memory in Reinforcement Learning RLBenchNet: The Right Network for the Right Reinforcement Learning Task

Reference 53

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T05:05:07.908039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.