Paper Citation Record · LEDGER

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning

As of 15 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 3 inbound Pith citation observations for arXiv:2501.08669.

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

pith.paper-citation-record.v1
2501.08669 v2

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:24:21.925514Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-21T07:36:12.214949Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T07:39:49.287335Z

Reference resolution

30 of 30 outbound references displayed

verified exact0
verified fuzzy7
unresolved23
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c3db4edc-b61e-4c8b-9915-74da46ceeeb4 · outbound

This paper cites Deep reinforcement learning: A brief survey.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Deep reinforcement learning: A brief survey

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.804878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c0cede0-94ee-4e67-becc-ce289267b460 · outbound

This paper cites Layer Normalization.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Layer Normalization

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.809683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a8d0cbc-09fc-45d8-888f-d0c2efaf225b · outbound

This paper cites an unresolved cited work.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-10T20:24:22.412106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 29eca1d7-2586-4177-bc6d-dd22f777b938 · outbound

This paper cites Bellemare, and Aaron C.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Bellemare, and Aaron C

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:24:22.399073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ea1a46c5-a1c6-4d04-9e03-c9fd7e22d65d · outbound

This paper cites A minimalist approach to offline reinforcement learning.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning A minimalist approach to offline reinforcement learning

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.823840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 320356c6-f7c1-4e68-badb-d92546c35e17 · outbound

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

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Addressing function approximation error in actor-critic methods

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.828054Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a10d8e33-9020-47de-81cf-ec97322144f8 · outbound

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

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.832429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3acdda27-5bfb-453a-afa9-fb692f600116 · outbound

This paper cites Dropout Q-Functions for Doubly Efficient Reinforcement Learning.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Dropout Q-Functions for Doubly Efficient Reinforcement Learning

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.837385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8061128-2d55-4be7-baa7-73bc36d15d5b · outbound

This paper cites Efficient deep reinforcement learning with imitative expert priors for autonomous driving.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Efficient deep reinforcement learning with imitative expert priors for autonomous driving

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.841673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c22e629f-3320-4d8d-8115-1cfc7b6fb075 · outbound

This paper cites When to Trust Your Model: Model-Based Policy Optimization.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning When to Trust Your Model: Model-Based Policy Optimization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.845378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3428810e-34ef-4644-ad1d-7fa9e714779c · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Offline Reinforcement Learning with Implicit Q-Learning

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.849813Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0324d47b-fabe-4530-bdc1-82696d7cd8c3 · outbound

This paper cites Conservative q-learning for offline reinforcement learning.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Conservative q-learning for offline reinforcement learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.853964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ecbb4f3-a4df-4cd8-a0e0-1119031f40ff · outbound

This paper cites Maxmin Q-learning: Controlling the Estimation Bias of Q-learning.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Maxmin Q-learning: Controlling the Estimation Bias of Q-learning

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.857688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65ef302d-67b2-4e12-b143-c8d0610e64ac · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.862302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e7b0c99d-2172-42b1-aebf-3b01f4a6ac61 · outbound

This paper cites Eliminating primacy bias in online reinforcement learning by self-distillation.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Eliminating primacy bias in online reinforcement learning by self-distillation

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:24:22.362644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b0f5eec1-118b-4cdc-bba5-e25d1014d894 · outbound

This paper cites Think2drive: Efficient reinforcement learning by thinking with latent world model for autonomous driving (in carla-v2).

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Think2drive: Efficient reinforcement learning by thinking with latent world model for autonomous driving (in carla-v2)

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:24:22.349887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e19a1db9-05c1-446d-b902-e456e938e7cc · outbound

This paper cites Continuous control with deep reinforcement learning.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Continuous control with deep reinforcement learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.874294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cfe48038-23de-4ac0-a0e1-f3f96a9eaba4 · outbound

This paper cites Serl: A software suite for sample-efficient robotic reinforcement learning.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Serl: A software suite for sample-efficient robotic reinforcement learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.878269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9468d1a-be98-4105-b466-6e0450205a3d · outbound

This paper cites Off-policy rl algorithms can be sample-efficient for continuous control via sample multiple reuse.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Off-policy rl algorithms can be sample-efficient for continuous control via sample multiple reuse

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:24:22.336723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fc7ec346-6959-4c80-a796-65e34b7ff636 · outbound

This paper cites AWAC: Accelerating Online Reinforcement Learning with Offline Datasets.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.886841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ce269abf-50d2-4818-a532-fffc5ed804ab · outbound

This paper cites Deep Reinforcement Learning with Plasticity Injection.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Deep Reinforcement Learning with Plasticity Injection

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.890658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63ae0502-2021-43bc-a86b-bfe4d98a6dfd · outbound

This paper cites Learning Dexterous In-Hand Manipulation.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Learning Dexterous In-Hand Manipulation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.894926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a0ca1e9-1464-42a8-b285-15a4fe9e6d15 · outbound

This paper cites Challenges of real-world reinforcement learning: definitions, benchmarks and analysis.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Challenges of real-world reinforcement learning: definitions, benchmarks and analysis

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:24:22.324748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ef842315-1f1c-4a73-b620-0a7762e5ae04 · outbound

This paper cites Courville, Marc G.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Courville, Marc G

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:24:22.312429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0293c6f9-6500-4874-8154-13f8c0c4e48b · outbound

This paper cites Dropout: A simple way to prevent neural networks from overfitting.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Dropout: A simple way to prevent neural networks from overfitting

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.906957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b7e667a-549e-448c-b153-25a47edbcff9 · outbound

This paper cites Reinforcement learning: An introduction.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Reinforcement learning: An introduction

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.910655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aef544f0-2ed0-49fc-a8fe-7713a79a1329 · outbound

This paper cites Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Deep Reinforcement Learning for Robotics: A Survey of Real-World Successes

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.914535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad1341c6-7447-4982-9e17-b146a4ffa28d · outbound

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

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning MuJoCo : A physics engine for model-based control

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T20:24:22.283628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 46df903e-e196-4ff4-ba8f-eb79d99e8e66 · outbound

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

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning Deep reinforcement learning with double q-learning

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.922068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 19d550be-29d4-4b40-bbf0-d3f2dd6e0bcb · outbound

This paper cites write newline.

SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning write newline

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T20:24:21.925514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation d3226db3-8999-4e41-b2ed-557a553485b1 · inbound

Distributional Value Estimation Without Target Networks for Robust Quality-Diversity cites this paper.

Distributional Value Estimation Without Target Networks for Robust Quality-Diversity SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-10T00:14:46.890229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7f147276-93d9-4b73-83bd-65f83a204543 · inbound

ARC-RL: A Reinforcement Learning Playground Inspired by ARC Raiders cites this paper.

ARC-RL: A Reinforcement Learning Playground Inspired by ARC Raiders SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-20T05:33:04.201008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f82172bd-0b00-4091-9b77-299ec47ae307 · inbound

ARC-RL: A Reinforcement Learning Playground Inspired by ARC Raiders cites this paper.

ARC-RL: A Reinforcement Learning Playground Inspired by ARC Raiders SPEQ: Offline Stabilization Phases for Efficient Q-Learning in High Update-To-Data Ratio Reinforcement Learning

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:39:49.289899Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.