Paper Citation Record · LEDGER

SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2410.09754.

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

pith.paper-citation-record.v1
2410.09754 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T19:16:28.973810Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T23:09:12.763536Z

Reference resolution

0 of 0 outbound references displayed

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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 2d0080d0-f5fe-42b8-8221-480264984ada · inbound

Hadamax Encoding: Elevating Performance in Model-Free Atari cites this paper.

Hadamax Encoding: Elevating Performance in Model-Free Atari SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-07T15:23:17.703821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e598f6e-02ff-41e2-80f0-7de53dca1f64 · inbound

Bigger, Regularized, Categorical: High-Capacity Value Functions are Efficient Multi-Task Learners cites this paper.

Bigger, Regularized, Categorical: High-Capacity Value Functions are Efficient Multi-Task Learners SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T12:58:50.224254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f39de609-c80d-4f54-8e23-36ecbf665a62 · inbound

Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning cites this paper.

Network Sparsity Unlocks the Scaling Potential of Deep Reinforcement Learning SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T19:16:28.973810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4fbd433-1d8f-41b2-8366-2add8b07afcf · inbound

A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control cites this paper.

A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T20:31:07.791190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 368842fc-30dc-4514-bb65-fb7dc3696ee5 · inbound

On the Effect of Regularization in Policy Mirror Descent cites this paper.

On the Effect of Regularization in Policy Mirror Descent SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T18:18:46.104398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bfbcbc3-15a9-4769-8931-49954e548b15 · inbound

Balancing Expressivity and Robustness: Constrained Rational Activations for Reinforcement Learning cites this paper.

Balancing Expressivity and Robustness: Constrained Rational Activations for Reinforcement Learning SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T15:55:34.443170Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6bf65cda-86bb-4f74-8cc7-f8bb7f90a255 · inbound

Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies cites this paper.

Scaling DRL for Decision Making: A Survey on Data, Network, and Training Budget Strategies SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T04:39:02.901710Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 789c6ba2-c50b-4d84-b762-c08c2fed956e · inbound

RN-D: Discretized Categorical Actors for On-Policy Reinforcement Learning cites this paper.

RN-D: Discretized Categorical Actors for On-Policy Reinforcement Learning SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 456

Resolution: unresolved; no resolver link, observed 2026-08-03T06:26:49.906939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa37823c-61fe-4fda-b66f-658cac3c605e · inbound

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control cites this paper.

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-10T22:15:49.935041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7380ff40-5d3f-48e0-9a10-f1c4a698a078 · inbound

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control cites this paper.

FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-19T17:12:41.381387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation be1bb9dc-e7a6-4167-a050-86b5f8e121a1 · inbound

When Does Non-Uniform Replay Matter in Reinforcement Learning? cites this paper.

When Does Non-Uniform Replay Matter in Reinforcement Learning? SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:36:24.525705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f38b74cd-9257-4006-b173-984feb108052 · inbound

When Does Non-Uniform Replay Matter in Reinforcement Learning? cites this paper.

When Does Non-Uniform Replay Matter in Reinforcement Learning? SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-13T06:32:24.792556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f5693bc5-6d19-4576-9e5a-f69059016ed3 · inbound

When Does Non-Uniform Replay Matter in Reinforcement Learning? cites this paper.

When Does Non-Uniform Replay Matter in Reinforcement Learning? SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-20T23:09:12.767631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 547e4950-ed51-4955-b1d5-9c4976222803 · inbound

TOPPO: Rethinking PPO for Multi-Task Reinforcement Learning with Critic Balancing cites this paper.

TOPPO: Rethinking PPO for Multi-Task Reinforcement Learning with Critic Balancing SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T01:52:05.707461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3d59e8fd-14ff-4a8e-972c-5a9a99dd5c51 · inbound

Aftab: A Comprehensive Benchmark of CNN Encoders and Advanced Value Functions in Parallelized Q-Networks cites this paper.

Aftab: A Comprehensive Benchmark of CNN Encoders and Advanced Value Functions in Parallelized Q-Networks SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T10:11:39.511565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e02e5eec-3b61-49b2-a7b2-d568eefbb8c1 · inbound

Aftab: A Comprehensive Benchmark of CNN Encoders and Advanced Value Functions in Parallelized Q-Networks cites this paper.

Aftab: A Comprehensive Benchmark of CNN Encoders and Advanced Value Functions in Parallelized Q-Networks SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-14T04:45:49.346201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0787e997-171a-42a8-bbc5-fb5348ab050a · inbound

V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control cites this paper.

V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-12T00:48:44.091692Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.