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Paper Citation Record · LEDGER

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning

As of 8 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2506.08756.

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

pith.paper-citation-record.v1
2506.08756 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:04:53.382607Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

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  • verified fuzzy5
  • unresolved33
  • parse uncertain0
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External citation measurements

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Outbound references

Observation 59a8444d-a7bd-47bf-be9c-25b8b4301c50 · outbound

This paper cites RT-1: Robotics Transformer for Real-World Control at Scale.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning RT-1: Robotics Transformer for Real-World Control at Scale

Reference 4

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Observation 7ceef02a-4cd1-474f-8abe-81dd9ba4ed8f · outbound

This paper cites Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Language models are few-shot learners.Advances in neural information processing systems, 33:1877–1901,

Reference 6

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source=pdf_text observed=2026-08-07T05:04:53.250058Z digest=sha256:8c3c56ddecba424187b1690cc5082cb559020494862081f25725eda65c04a415

Observation a26113e8-66f5-432a-900c-6bf7e824bd86 · outbound

This paper cites The rising costs of training frontier AI models.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning The rising costs of training frontier AI models

Reference 8

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Observation bd727349-22c9-45ae-a97f-ca3a4e7e3592 · outbound

This paper cites Automating Involutive MCMC using Probabilistic and Differentiable Programming.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Automating Involutive MCMC using Probabilistic and Differentiable Programming

Reference 9

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Observation 05466b12-1c63-4a9c-9272-1007273f803e · outbound

This paper cites The Llama 3 Herd of Models.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning The Llama 3 Herd of Models

Reference 11

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Observation 81674a59-1680-42b7-9197-72089e533094 · outbound

This paper cites DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning

Reference 13

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Observation b0f74a6e-1b59-4241-aa9d-9f828ab4ce27 · outbound

This paper cites Bayesian Workflow.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Bayesian Workflow

Reference 16

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Observation e2a9b67f-77c1-4809-8a21-560d010c6f30 · outbound

This paper cites Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation

Reference 17

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 4bb14391-bbed-4785-82f0-b3e2c7e4c896 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 18

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source=pdf_text observed=2026-08-07T05:04:53.298436Z digest=sha256:24645ae75c7564a52e0af04ee164e3bf1b92eae5b30843b515892afd886926f3

Observation eb178bc4-f3b3-41d8-a3bb-0d12d11d4690 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Training Compute-Optimal Large Language Models

Reference 19

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source=pdf_text observed=2026-08-07T05:04:53.302076Z digest=sha256:30d6ea5fd3f7b4f7fda6f232e1d8dd4d174ba8f412b8b440126cdc3dbe37e2fc

Observation 6d2f26bc-5bab-44af-bcb9-f0d13526ffbe · outbound

This paper cites doi: 10.1177/0278364920987859.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning doi: 10.1177/0278364920987859

Reference 20

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Observation a581990d-01ec-4bd6-b4be-7e09892b848d · outbound

This paper cites an unresolved cited work.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Unresolved cited work

Reference 21

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source=pdf_text observed=2026-08-07T05:04:53.310102Z digest=sha256:6f7737c521c3521c04f3866065495faf7a2bd68dd0120cc67d7e3290a2e4da9a

Observation 1954b7c7-3bf7-4ee4-89b3-603e2f165845 · outbound

This paper cites Scaling Laws for Neural Language Models.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Scaling Laws for Neural Language Models

Reference 22

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Observation 4aac6718-0292-4d4e-b6ea-7c3f0e1c5d0a · outbound

This paper cites Highly Dynamic Quadruped Locomotion via Whole-Body Impulse Control and Model Predictive Control.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Highly Dynamic Quadruped Locomotion via Whole-Body Impulse Control and Model Predictive Control

Reference 23

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Observation 1ba09fc5-f363-4e7d-8847-0e29a7d81202 · outbound

This paper cites OpenVLA: An Open-Source Vision-Language-Action Model.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning OpenVLA: An Open-Source Vision-Language-Action Model

Reference 24

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Observation 068bdbf2-7e3a-4ba3-97c7-022e077dda23 · outbound

This paper cites A Differentiable Newton Euler Algorithm for Multi-body Model Learning.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning A Differentiable Newton Euler Algorithm for Multi-body Model Learning

Reference 26

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Observation 314db1f1-93d7-47f8-8671-930cccf46016 · outbound

This paper cites Igor Mordatch, Zoran Popović, and Emanuel Todorov.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Igor Mordatch, Zoran Popović, and Emanuel Todorov

Reference 27

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Observation 7c0451dc-b4de-4978-9d60-3a6e995cb6d1 · outbound

This paper cites doi: 10.3389/fmars.2019.00580.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning doi: 10.3389/fmars.2019.00580

Reference 28

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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.

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Observation 55bdb21e-10e0-4393-8fd0-ec1bbd214f02 · outbound

This paper cites Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution

Reference 29

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Observation 2594464f-76f6-4043-b0ad-6d87aa9ba426 · outbound

This paper cites Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro

Reference 30

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Observation c5c24644-4195-4f21-8937-a91a9607c444 · outbound

This paper cites Neil Rabinowitz, Frank Perbet, Francis Song, Chiyuan Zhang, SM Ali Eslami, and Matthew Botvinick.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Neil Rabinowitz, Frank Perbet, Francis Song, Chiyuan Zhang, SM Ali Eslami, and Matthew Botvinick

Reference 32

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Observation 8b9bbcd6-a6af-4829-a621-6268fe7fb533 · outbound

This paper cites Accelerating 3D Deep Learning with PyTorch3D.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Accelerating 3D Deep Learning with PyTorch3D

Reference 33

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Observation 01534e3d-aa9f-4459-a26b-70d8006e13d6 · outbound

This paper cites Progressive Neural Networks.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Progressive Neural Networks

Reference 34

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Observation ee9ecf42-99de-4e8f-90fd-e335553e962c · outbound

This paper cites URL https://doi.org/10.1080/10447318.2020.1741118.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning URL https://doi.org/10.1080/10447318.2020.1741118

Reference 35

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Observation 689319c3-678d-4da4-a70a-b982d24d5ee7 · outbound

This paper cites Will we run out of data? Limits of LLM scaling based on human-generated data.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Will we run out of data? Limits of LLM scaling based on human-generated data

Reference 37

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Observation 34b4ce6d-1865-42b1-91d3-a5d410b165a8 · outbound

This paper cites Narang, Fabio Ramos, Wojciech Matusik, Animesh Garg, and Miles Macklin.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Narang, Fabio Ramos, Wojciech Matusik, Animesh Garg, and Miles Macklin

Reference 38

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 83cc1ce6-142a-48df-a253-900b7e147898 · outbound

This paper cites Advances in variational inference.IEEE transactions on pattern analysis and machine intelligence, 41 (8):2008–2026,.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Advances in variational inference.IEEE transactions on pattern analysis and machine intelligence, 41 (8):2008–2026,

Reference 39

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Observation 887519db-99c1-4e2a-9ecf-675fa1152b1d · outbound

This paper cites Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulation.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulation

Reference 1965

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Observation 83d17b0b-f5fc-44b5-8693-0b382b0bf28f · outbound

This paper cites Efficient Reinforcement Learning Framework for Automated Logic Synthesis Exploration.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Efficient Reinforcement Learning Framework for Automated Logic Synthesis Exploration

Reference 1984

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verified fuzzy
raw_fallback, observed 2026-08-07T05:04:54.084633Z

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.

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Observation 49905a84-1029-40f2-bf2e-436a1404564c · outbound

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

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Mujoco: A physics engine for model-based control

Reference 2011

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verified fuzzy
raw_fallback, observed 2026-08-07T05:04:54.071551Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation fc2e40fe-761d-4546-953f-c10ac37441fd · outbound

This paper cites Samuli Laine, Janne Hellsten, Tero Karras, Yeongho Seol, Jaakko Lehtinen, and Timo Aila.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning Samuli Laine, Janne Hellsten, Tero Karras, Yeongho Seol, Jaakko Lehtinen, and Timo Aila

Reference 2013

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Observation d078c043-7674-472d-8754-0b042be90bb8 · outbound

This paper cites On the Opportunities and Risks of Foundation Models.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning On the Opportunities and Risks of Foundation Models

Reference 2017

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Observation 57a6845b-e494-4fb6-8101-983738edaa43 · outbound

This paper cites BlackJAX: Composable Bayesian inference in JAX.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning BlackJAX: Composable Bayesian inference in JAX

Reference 2018

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source=pdf_text observed=2026-08-07T05:04:53.254016Z digest=sha256:22d9a79b26fe41bf695816fcba8edaee3ed320a0d80e5ade30ccd63527acb7b6

Observation 16fdcde5-794d-4d46-9f70-c84308157e42 · outbound

This paper cites TensorFlow Distributions.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning TensorFlow Distributions

Reference 2019

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Observation 4afeb1bf-6a3f-46da-8b4e-ad81656a2825 · outbound

This paper cites PathNet: Evolution Channels Gradient Descent in Super Neural Networks.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning PathNet: Evolution Channels Gradient Descent in Super Neural Networks

Reference 2020

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Observation 8e39237a-521f-4e90-90ed-64638a1f4b63 · outbound

This paper cites doi: 10.1007/s10994-021-05961-4.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning doi: 10.1007/s10994-021-05961-4

Reference 2021

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Observation 32ddd985-ab74-4002-b5d9-5f65d4fdd5d8 · outbound

This paper cites RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Reference 2022

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unresolved
no resolver link, observed 2026-08-07T05:04:53.245699Z

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source=pdf_text observed=2026-08-07T05:04:53.245699Z digest=sha256:799eb828718eecbb90e2be53df2345c658a8412d729e155e4cd361e126a3cb16

Observation 9be4f5dc-1716-4c07-9f57-3e3205bcb725 · outbound

This paper cites A Conceptual Introduction to Hamiltonian Monte Carlo.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning A Conceptual Introduction to Hamiltonian Monte Carlo

Reference 2023

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source=pdf_text observed=2026-08-07T05:04:53.232794Z digest=sha256:b676c90c0b574dba8e9f54d9300ef07cb60bda4438cebbd3dbb8ddcf7ad1a39f

Observation 3e2a7f75-7552-4de5-b025-ca6c727f6145 · outbound

This paper cites DeepCoder: Learning to Write Programs.

Bayesian Inverse Physics for Neuro-Symbolic Robot Learning DeepCoder: Learning to Write Programs

Reference 2024

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source=pdf_text observed=2026-08-07T05:04:53.228075Z digest=sha256:6c0ec75bc3c818e0d26b44911e8438207204ac5b114d2341059112c9da2f53df

Pith citing papers

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