Paper Citation Record · LEDGER

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation

As of 20 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 4 inbound Pith citation observations for arXiv:2412.12089.

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

pith.paper-citation-record.v1
2412.12089 v2

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:25:18.377948Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T11:03:31.098377Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T05:25:54.539497Z

Reference resolution

37 of 37 outbound references displayed

verified exact0
verified fuzzy18
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7f41b60c-134a-4edd-8cc0-81846c39d9dd · outbound

This paper cites an unresolved cited work.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:25:19.120281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b419e46c-fec9-4f62-bd09-d8490d887d7b · outbound

This paper cites an unresolved cited work.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:25:19.037570Z

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Observation 62afaa51-dc9b-4aa3-a093-68423ef2eef3 · outbound

This paper cites Simplifying Deep Temporal Difference Learning.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Simplifying Deep Temporal Difference Learning

Reference 5

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Observation f987b00d-d695-42eb-a626-7239356963ae · outbound

This paper cites We denote the goal state distribution ρ∗ if the task defines it.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation We denote the goal state distribution ρ∗ if the task defines it

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:18.987155Z

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Observation 8ac1a36d-75db-4e93-94ff-913231d78237 · outbound

This paper cites Distributed prioritized experience replay.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Distributed prioritized experience replay

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.362611Z

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Observation 28971864-133c-45bb-a2b5-a4c13ce62cbd · outbound

This paper cites Dojo: A Differentiable Physics Engine for Robotics.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Dojo: A Differentiable Physics Engine for Robotics

Reference 8

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Observation 264b630d-494c-4f26-813e-0836c279dddc · outbound

This paper cites Path integrals and symmetry breaking for optimal control theory.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Path integrals and symmetry breaking for optimal control theory

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.332846Z

Source-reported events for the cited work

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Observation 302b6345-ee9e-47c0-9f5a-60077200ad9f · outbound

This paper cites Planning with spatial-temporal abstraction from point clouds for deformable object manipulation.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Planning with spatial-temporal abstraction from point clouds for deformable object manipulation

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.309051Z

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Observation 2d62166a-a1f3-403c-a653-f6e671ba0197 · outbound

This paper cites Empirical Design in Reinforcement Learning.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Empirical Design in Reinforcement Learning

Reference 13

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Observation 2cfd67f5-9273-43b1-b5b2-fdb0940599e8 · outbound

This paper cites Diffmimic: Efficient motion mimicking with differentiable physics.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Diffmimic: Efficient motion mimicking with differentiable physics

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.286345Z

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Observation 7d48e508-54e3-4987-9f99-ea6190c75cae · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 16

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Observation bc3d8159-d346-4001-b0d8-635058cbca9a · outbound

This paper cites Learning Deployable Locomotion Control via Differentiable Simulation.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Learning Deployable Locomotion Control via Differentiable Simulation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T14:25:18.214365Z

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Observation 8c6e3295-80f7-4ebe-a84d-3c041583ffde · outbound

This paper cites Issues in using function approximation for reinforcement learning.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Issues in using function approximation for reinforcement learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.256385Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 7d2fa325-137c-4857-baab-9ce6c67ad259 · outbound

This paper cites Do You Need the Entropy Reward (in Practice)?.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Do You Need the Entropy Reward (in Practice)?

Reference 19

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Observation 951ab7bd-f575-4b3e-85f4-d69788a0d94b · outbound

This paper cites Back to Newton's Laws: Learning Vision-based Agile Flight via Differentiable Physics.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Back to Newton's Laws: Learning Vision-based Agile Flight via Differentiable Physics

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T14:25:18.240219Z

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Observation 127e30f8-775d-4bfa-8afc-9edcfbf2e2a9 · outbound

This paper cites Also using implicit differentiation, Qiao et al.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Also using implicit differentiation, Qiao et al

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.213655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 153a5a6f-abe2-44bc-9edc-24b09688c396 · outbound

This paper cites an unresolved cited work.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:25:19.191840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation a74e3df9-0876-4ec1-8a63-7d9fc1156d2a · outbound

This paper cites π[·] J(π) zt+H zt+H zt+1 zt+1 μt μt+H μt+1 σt+H σt+1 (V) (π) (π) (π) zt st at Actor MLP Actor Encoder Diff.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation π[·] J(π) zt+H zt+H zt+1 zt+1 μt μt+H μt+1 σt+H σt+1 (V) (π) (π) (π) zt st at Actor MLP Actor Encoder Diff

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.167068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation af767c56-a068-4ac3-92c9-bd3bcf68ef78 · outbound

This paper cites We leave combining differentiable rendering (of RGB or depth image observations) with differentiable simulation, like in (Murthy et al., 2021), to future work.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation We leave combining differentiable rendering (of RGB or depth image observations) with differentiable simulation, like in (Murthy et al., 2021), to future work

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.149850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 6e55127b-4105-4733-9e4b-3ef72c23c688 · outbound

This paper cites In comparison, reverse-mode AD has time complexity O(M · L), and also benefits from GPU-acceleration.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation In comparison, reverse-mode AD has time complexity O(M · L), and also benefits from GPU-acceleration

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.059741Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5095f754-cc73-47a0-8c24-8b94b695fbf3 · outbound

This paper cites an unresolved cited work.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:25:19.010612Z

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Observation fe1795f4-95c2-4318-a270-af7b127cd438 · outbound

This paper cites Based on AllegroHand from (Makoviychuk et al., 2021).

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Based on AllegroHand from (Makoviychuk et al., 2021)

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:18.966882Z

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Observation 411fd8d7-02b4-4982-8cc0-faa5d06b39b4 · outbound

This paper cites an unresolved cited work.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-11T14:25:18.860908Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 2c3edd44-66ba-4fda-bdf0-f199542e77b4 · outbound

This paper cites Based on RollingPin from (Huang et al., 2020).

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Based on RollingPin from (Huang et al., 2020)

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:18.926240Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation e5f985f1-0f44-4c6c-866c-77c900e717fe · outbound

This paper cites All algorithms use the same actor and critic network architecture.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation All algorithms use the same actor and critic network architecture

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.084085Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 5a257b74-960a-4cf5-9f25-a5aa275ccd7b · outbound

This paper cites Based on Flip from (Li et al., 2023a).

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Based on Flip from (Li et al., 2023a)

Reference 130

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:18.877566Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 786e052e-d36a-4945-b434-f1a7f32f84bf · outbound

This paper cites All algorithms use the same actor and critic network architecture.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation All algorithms use the same actor and critic network architecture

Reference 256

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.099814Z

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Observation b177be36-fbb5-41b3-809f-7e8229d41c3f · outbound

This paper cites Inspired by (Murthy et al., 2021; Hu et al., 2020).

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Inspired by (Murthy et al., 2021; Hu et al., 2020)

Reference 1000

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:18.904096Z

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Observation 00de969e-614a-418a-856a-243a103cb83b · outbound

This paper cites We review prior works on non-parallel differentiable simulators for robotics and control problems.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation We review prior works on non-parallel differentiable simulators for robotics and control problems

Reference 2008

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.236317Z

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Observation e020e6fe-8290-414f-9db3-e592d4e3d8a6 · outbound

This paper cites Differentiable Implicit Soft-Body Physics.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Differentiable Implicit Soft-Body Physics

Reference 2014

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Observation 1f87b3bd-a73b-4c89-a02d-56d7803de230 · outbound

This paper cites Soft Actor-Critic Algorithms and Applications.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Soft Actor-Critic Algorithms and Applications

Reference 2017

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This paper cites Impala: Scalable distributed deep-rl with importance weighted actor-learner architectures.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Impala: Scalable distributed deep-rl with importance weighted actor-learner architectures

Reference 2018

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:25:19.382852Z

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Observation 6428e1f0-4e4a-4f3f-a0c9-867b07190c09 · outbound

This paper cites Solving Rubik's Cube with a Robot Hand.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Solving Rubik's Cube with a Robot Hand

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-11T14:25:18.087081Z

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Observation 9e5d1978-2588-45de-a979-3fce921f4e09 · outbound

This paper cites Massively Parallel Methods for Deep Reinforcement Learning.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Massively Parallel Methods for Deep Reinforcement Learning

Reference 2021

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This paper cites Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning

Reference 2022

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Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Layer Normalization

Reference 2023

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Observation 4baeafc8-f967-42ca-95cb-4912ec108a71 · outbound

This paper cites Decoupled Weight Decay Regularization.

Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation Decoupled Weight Decay Regularization

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T14:25:18.162971Z

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Pith citing papers

Observation e35af45e-1f0b-448d-b13c-8b2845a3e1bb · inbound

Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Tasks cites this paper.

Benchmarking Massively Parallelized Multi-Task Reinforcement Learning for Robotics Tasks Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-06T11:03:31.098377Z

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Observation 0c47a33e-6ec9-4403-8350-7707d2faef05 · inbound

First Order Model-Based RL through Decoupled Backpropagation cites this paper.

First Order Model-Based RL through Decoupled Backpropagation Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation

Reference 19

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Observation d80812c7-5ba6-474f-8198-3150962b2a74 · inbound

The HydroGym Reinforcement Learning Platform for Fluid Dynamics cites this paper.

The HydroGym Reinforcement Learning Platform for Fluid Dynamics Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation

Reference 66

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Observation 838e404a-bdbb-41a5-8f71-374de83cc229 · inbound

Does "Do Differentiable Simulators Give Better Policy Gradients?'' Give Better Policy Gradients? cites this paper.

Does "Do Differentiable Simulators Give Better Policy Gradients?'' Give Better Policy Gradients? Stabilizing Reinforcement Learning in Differentiable Multiphysics Simulation

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-10T05:25:54.541004Z

Source-reported events for the cited work

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