Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2410.09754.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:23:17.703821Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T23:09:12.763536Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 2d0080d0-f5fe-42b8-8221-480264984ada · inbound
Hadamax Encoding: Elevating Performance in Model-Free Atari SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Reference 34
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 SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Reference 60
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 SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Reference 21
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 SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Reference 22
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 SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Reference 12
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 SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Reference 18
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 SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Reference 456
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 SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Reference 39
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7380ff40-5d3f-48e0-9a10-f1c4a698a078 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation be1bb9dc-e7a6-4167-a050-86b5f8e121a1 · inbound
When Does Non-Uniform Replay Matter in Reinforcement Learning? SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f38b74cd-9257-4006-b173-984feb108052 · inbound
When Does Non-Uniform Replay Matter in Reinforcement Learning? SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation f5693bc5-6d19-4576-9e5a-f69059016ed3 · inbound
When Does Non-Uniform Replay Matter in Reinforcement Learning? SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Reference 16
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 547e4950-ed51-4955-b1d5-9c4976222803 · inbound
TOPPO: Rethinking PPO for Multi-Task Reinforcement Learning with Critic Balancing SimBa: Simplicity Bias for Scaling Up Parameters in Deep Reinforcement Learning
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.