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Paper Citation Record · LEDGER

Active Inference as the Test-Time Scaling Law for Physical AI Agents

As of 24 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 0 inbound Pith citation observations for arXiv:2606.22813.

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

pith.paper-citation-record.v1
2606.22813 v1

Coverage vector

measured 53 of 53 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-26T08:54:38.246078Z

measured 53 of 53 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

53 of 53 outbound references displayed

  • verified exact8
  • verified fuzzy0
  • unresolved44
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1d80941c-6e07-4250-864b-722c4f126fa9 · outbound

This paper cites Artificial general intelligence (AGI)-native wireless systems: A journey beyond 6G,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Artificial general intelligence (AGI)-native wireless systems: A journey beyond 6G,

Reference 1

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Observation fdf07c62-bced-4aeb-a8d3-d2a5cc5bda8b · outbound

This paper cites Waymos blocked roads and caused chaos during San Francisco power outage,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Waymos blocked roads and caused chaos during San Francisco power outage,

Reference 2

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Observation 1da52061-a3d1-42b2-812a-dea53ae52b37 · outbound

This paper cites World Models.

Active Inference as the Test-Time Scaling Law for Physical AI Agents World Models

Reference 3

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Observation ad00ab47-9fb5-4ff7-bf20-ea03a2b4c738 · outbound

This paper cites Kahneman,Thinking, fast and slow.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Kahneman,Thinking, fast and slow

Reference 4

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Observation 94335d87-2fc9-43d3-95b8-0b31b64130ac · outbound

This paper cites A path towards autonomous machine intelligence version 0.9. 2, 2022-06-27,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents A path towards autonomous machine intelligence version 0.9. 2, 2022-06-27,

Reference 5

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Observation dc98e808-d87b-4260-a3b8-a50d9007f078 · outbound

This paper cites Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Predictive coding in the visual cortex: a functional interpretation of some extra-classical receptive-field effects,

Reference 6

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Observation eeb7e0fc-abb8-4e36-8044-6bb3cab3b465 · outbound

This paper cites Active inference: a process theory,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Active inference: a process theory,

Reference 7

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Observation 6dcde331-c5e3-4070-b05e-2c76acbc6eb9 · outbound

This paper cites Dissipative structures in biological systems: bistability, oscillations, spatial patterns and waves,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Dissipative structures in biological systems: bistability, oscillations, spatial patterns and waves,

Reference 8

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:735d3b95b4f0b7bad86a9555bb30c5193e325b4fe59e29bfaf6e733a69d68891

Observation e60133d7-5b0c-4716-98dd-5828732ca79f · outbound

This paper cites (2026).Active Inference for Physical AI Agents – An Engineering Perspective.

Active Inference as the Test-Time Scaling Law for Physical AI Agents (2026).Active Inference for Physical AI Agents – An Engineering Perspective

Reference 9

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Observation 1e0233ae-30de-4029-86a0-b081b768827e · outbound

This paper cites Life as we know it,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Life as we know it,

Reference 10

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Observation be92f8df-4cec-48dc-a4ef-4fef145a2ef8 · outbound

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

Active Inference as the Test-Time Scaling Law for Physical AI Agents Challenges of real-world reinforcement learning: definitions, benchmarks and analysis,

Reference 11

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Observation fd624367-f505-471f-bf28-7038bc44a2c2 · outbound

This paper cites an unresolved cited work.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Unresolved cited work

Reference 12

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:70d90c4bdb595b5aee84c2b592cbb67945ddfc8497ef3981d6685ac5fa5bc419

Observation b2b53939-a852-4d6f-8567-ec5a9406d0a5 · outbound

This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

Active Inference as the Test-Time Scaling Law for Physical AI Agents V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 13

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Observation 8b184f22-f0d9-4469-91ff-a91b9ed3a483 · outbound

This paper cites Mindjourney: Test-time scaling with world models for spatial reasoning,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Mindjourney: Test-time scaling with world models for spatial reasoning,

Reference 14

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Observation 40e55858-4f66-4feb-a9df-6f42d57eeaf0 · outbound

This paper cites π 0.7: a steerable generalist robotic foundation model with emergent capabilities,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents π 0.7: a steerable generalist robotic foundation model with emergent capabilities,

Reference 15

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Observation 22816f3e-3824-4224-86ea-b36294244170 · outbound

This paper cites V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning.

Active Inference as the Test-Time Scaling Law for Physical AI Agents V-JEPA 2.1: Unlocking Dense Features in Video Self-Supervised Learning

Reference 16

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local_arxiv, observed 2026-07-04T10:19:47.935198Z

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Observation ffd8ab1a-35dc-4927-ae05-8c27379f1326 · outbound

This paper cites The markov blankets of life: autonomy, active inference and the free energy principle,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents The markov blankets of life: autonomy, active inference and the free energy principle,

Reference 17

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Observation 1a07d237-7d41-4e96-a4f1-56708609fc57 · outbound

This paper cites A neural substrate of prediction and reward,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents A neural substrate of prediction and reward,

Reference 18

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Observation 38aea660-2ab6-4055-8726-db1d173b1345 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Training Compute-Optimal Large Language Models

Reference 19

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Observation 29d3a5e4-c54f-444b-b5fa-202d87cef81e · outbound

This paper cites Scaling Laws for Neural Language Models.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Scaling Laws for Neural Language Models

Reference 20

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Observation fa440d8a-4800-426d-93bb-fe516edeab61 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 21

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Observation 64be20da-0dd8-4e39-b24e-d48c65d3c51a · outbound

This paper cites Toward causal representation learning,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Toward causal representation learning,

Reference 22

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Observation 4f93d469-2ecd-45bd-b631-148e043dceaa · outbound

This paper cites From passive mirrors to active agents: Holonic digital twins for physical artificial intelligence over networks,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents From passive mirrors to active agents: Holonic digital twins for physical artificial intelligence over networks,

Reference 23

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Observation e11d2785-1749-4b13-8a8a-c26fdbfca9de · outbound

This paper cites Robust agents learn causal world models,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Robust agents learn causal world models,

Reference 24

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Observation 667530d3-117b-4e42-9474-20fa4dbdb3ea · outbound

This paper cites Bayesian surprise attracts human attention,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Bayesian surprise attracts human attention,

Reference 25

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Observation 00821871-d45d-4966-8b52-55e6871ccb7c · outbound

This paper cites The free-energy principle: a unified brain theory?.

Active Inference as the Test-Time Scaling Law for Physical AI Agents The free-energy principle: a unified brain theory?

Reference 26

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Observation 815fe207-b9a2-44f0-9a79-078da9c8e8d7 · outbound

This paper cites an unresolved cited work.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Unresolved cited work

Reference 27

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:db25f40a7186ebee591dd01a534072d40c3742d87753c63c79359aa8a611491d

Observation e4108b78-8ade-40f7-93d6-86ad91c00ab7 · outbound

This paper cites Path integrals, particular kinds, and strange things,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Path integrals, particular kinds, and strange things,

Reference 28

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Observation cbfd0116-9d26-49de-aefb-0f76176a8a49 · outbound

This paper cites Evidence for surprise minimization over value maximization in choice behavior,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Evidence for surprise minimization over value maximization in choice behavior,

Reference 29

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Observation 3300e92b-fc46-4d8d-aabe-e87ccc95c0f9 · outbound

This paper cites Pearl,Probabilistic reasoning in intelligent systems: networks of plausible inference.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Pearl,Probabilistic reasoning in intelligent systems: networks of plausible inference

Reference 30

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Observation c79b6ccb-f795-4780-82c2-060948937e1c · outbound

This paper cites The mathematics of changing one’s mind, via jeffrey’s or via pearl’s update rule,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents The mathematics of changing one’s mind, via jeffrey’s or via pearl’s update rule,

Reference 31

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Observation 50b5a88c-b389-4353-9c7d-7afba35ab124 · outbound

This paper cites an unresolved cited work.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Unresolved cited work

Reference 32

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Observation fef92f1e-98fe-40db-b5ae-07c59da750dc · outbound

This paper cites Human-level control through deep reinforcement learning,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Human-level control through deep reinforcement learning,

Reference 33

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Observation 86959a2f-b9df-4eca-a23d-2aa079c84d35 · outbound

This paper cites Optimizing for the future in non- stationary mdps,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Optimizing for the future in non- stationary mdps,

Reference 34

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Observation a2aad4a9-423d-4df9-b6c1-47d5360bd82f · outbound

This paper cites A tutorial on energy-based learning,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents A tutorial on energy-based learning,

Reference 35

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:5dfe095d5bf3268599a91ca86a55bd6f97a6de2d6d86e6327a89f18104814120

Observation 2f984965-eca4-4c4f-839c-71057cce7a8c · outbound

This paper cites An introduction to variational methods for graphical models,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents An introduction to variational methods for graphical models,

Reference 36

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:954153a0cba462fdeed0428763f41ccb8046b4292ff34647c67b0d8c0b10ce29

Observation 3e32a461-ed03-4ff8-9faf-455a6a1abf44 · outbound

This paper cites Graphical models, exponential families, and variational inference,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Graphical models, exponential families, and variational inference,

Reference 37

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:e1fb01225b8a6a093f2554763237154c7957e6db8bfdbad9cad0ee3348e81167

Observation d3f999a8-c7f2-4bcc-8739-156bc6cedf58 · outbound

This paper cites Variational message passing.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Variational message passing

Reference 38

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Observation 3c830c3b-8958-4dcd-92ee-3895bb36efe0 · outbound

This paper cites Auto-Encoding Variational Bayes.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Auto-Encoding Variational Bayes

Reference 39

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Observation da23e6a2-4151-488e-99cf-8ef4c8cc6a49 · outbound

This paper cites A step-by-step tutorial on active inference and its application to empirical data,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents A step-by-step tutorial on active inference and its application to empirical data,

Reference 40

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Observation 249db3f2-8da4-4024-8626-10cc330bb7a0 · outbound

This paper cites Codes on graphs: Normal realizations,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Codes on graphs: Normal realizations,

Reference 41

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Observation e84ee151-cf62-440f-9d89-43a2f503ef53 · outbound

This paper cites an unresolved cited work.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Unresolved cited work

Reference 42

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Observation 64fe366f-9f65-4747-9b02-7c400fcdcfdb · outbound

This paper cites Whence the expected free energy?.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Whence the expected free energy?

Reference 43

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Observation e8bc88e3-c5a3-4393-a40e-e5665519f456 · outbound

This paper cites Koller and N.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Koller and N

Reference 44

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:1ae13c1ced17a8cd47d31cb4692fd72236371a7d734a44b7de1979e60bb57827

Observation 5f739c0e-11da-4920-b9bc-efcf81d49c42 · outbound

This paper cites Bayesian mechanics for stationary processes,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Bayesian mechanics for stationary processes,

Reference 45

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:d31bda8d01d3a3e76fb77edf348674482f786dc6d1321698a1d7f71e61f3564c

Observation b43bfff9-1e62-4bd9-a441-a7c971a7e3ec · outbound

This paper cites On markov blankets and hierarchical self-organisation,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents On markov blankets and hierarchical self-organisation,

Reference 46

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:5c1e6fc6a17279fd269935b2133ba82bc58ca83a4c6f28caa378ebd9f25da956

Observation 327c19c5-132f-4f61-9f65-46f257a1dbbb · outbound

This paper cites Nonlinear kinetics on lattices based on the kinetic interaction principle,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Nonlinear kinetics on lattices based on the kinetic interaction principle,

Reference 47

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:4de82b1f1ea662801224150b3faaf622ce76a3ea9cf534a0848adc220235266c

Observation 50edc08a-b477-49d1-9358-874a10a169f7 · outbound

This paper cites Cognitive dynamics: From attractors to active inference,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Cognitive dynamics: From attractors to active inference,

Reference 48

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:a57660ab03141c9d90221737ef13c6156efd1fc81eb64ff0b4b3b812432e4ef8

Observation 5e37cd61-8b28-49d6-819e-4c4472569641 · outbound

This paper cites Welcome to the era of experience,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Welcome to the era of experience,

Reference 49

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:01982a72f2053b33124c48186acf2966f85cbe44b0d35bacab95887110229854

Observation 9160b45b-93f0-4752-ae48-f0d68bf5c71e · outbound

This paper cites Active inference on discrete state-spaces: A synthesis,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Active inference on discrete state-spaces: A synthesis,

Reference 50

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:db62f54377b6db5ba5737597150770ebb766072438fc4d0c54997931680e3d6c

Observation 6164a644-1fd5-416e-965e-d1fc003b8eff · outbound

This paper cites Dupoux, Y.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Dupoux, Y

Reference 51

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:f7470135ba602c0b8654df9a3ef4f188f5fcc8fba6c37a1d567851c54f1d663c

Observation 78abb40c-506d-4f86-ab58-9400a18e2ce4 · outbound

This paper cites Edge continual learning for dynamic digital twins over wireless networks,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents Edge continual learning for dynamic digital twins over wireless networks,

Reference 52

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:b12497c014c2d784bc310e002c7755f5c7474461abd409a1fe7a116d6e27406d

Observation 248c5ff8-6baa-4e38-8a8e-441dbe44d404 · outbound

This paper cites The neural basis of the speed–accuracy tradeoff,.

Active Inference as the Test-Time Scaling Law for Physical AI Agents The neural basis of the speed–accuracy tradeoff,

Reference 53

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source=pdf_text observed=2026-06-26T08:54:38.246078Z digest=sha256:b0f994033bc89fe74c71457e5e1f58a0d39ffc084fcdfebdf249773ce5944583

Pith citing papers

No inbound Pith citation observations are available.