Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value | Paper Citation Record

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This paper cites The remaining reten- tion devices: Device KR (key redraw; Type II).As defined in Sec.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value The remaining reten- tion devices: Device KR (key redraw; Type II).As defined in Sec

Reference 3

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This paper cites HenceE[W ext] of ev- eryP∈Prot b(Aτ−M,p) is a functional of the non-M marginals alone, and the blind branch does not depend on the coupling structureπ M.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value HenceE[W ext] of ev- eryP∈Prot b(Aτ−M,p) is a functional of the non-M marginals alone, and the blind branch does not depend on the coupling structureπ M

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This paper cites We state it once, so that the weight-bearing path depends on a statement rather than on the interior of an imported proof.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value We state it once, so that the weight-bearing path depends on a statement rather than on the interior of an imported proof

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This paper cites Step 1.Mis frozen (derived from Defini- tion 2(ii)+(iv)); under convention (α), apply Lemma 9 to theM=mconditional law.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Step 1.Mis frozen (derived from Defini- tion 2(ii)+(iv)); under convention (α), apply Lemma 9 to theM=mconditional law

Reference 7

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This paper cites From the definition of the implementation entropy production, Σtotal = [S(M′,D)−S(M,D,A)] + ∆Sbath.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value From the definition of the implementation entropy production, Σtotal = [S(M′,D)−S(M,D,A)] + ∆Sbath

Reference 10

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This paper cites By (β),DandX τ have identical content, so I(M′ f;Xτ |Y τ) =I(M ′ f;D|Y τ).

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value By (β),DandX τ have identical content, so I(M′ f;Xτ |Y τ) =I(M ′ f;D|Y τ)

Reference 15

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This paper cites Flat part:X,nuniform bits as a single manipulable regis- ter (K= 3, static all-read).

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Flat part:X,nuniform bits as a single manipulable regis- ter (K= 3, static all-read)

Reference 19

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This paper cites All states (F5 ′) (machine-checked; no noise is needed).

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value All states (F5 ′) (machine-checked; no noise is needed)

Reference 20

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This paper cites D= (copy ofX, J)—clause (β) broken: the record ex- ceeds the faithful observation of the medium.T=δ τ, barbitrary; capacitynbits;F={f X,fJ}.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value D= (copy ofX, J)—clause (β) broken: the record ex- ceeds the faithful observation of the medium.T=δ τ, barbitrary; capacitynbits;F={f X,fJ}

Reference 21

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This paper cites Upper end: supply boundedness—prize plus budget plus bookkeeping.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Upper end: supply boundedness—prize plus budget plus bookkeeping

Reference 22

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This paper cites Generalized Jarzynski Equality under Nonequilibrium Feedback Control.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Generalized Jarzynski Equality under Nonequilibrium Feedback Control

Reference 23

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This paper cites Stochastic Thermodynamics of Learning.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Stochastic Thermodynamics of Learning

Reference 24

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This paper cites Thermodynamic efficiency of learning a rule in neural networks.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Thermodynamic efficiency of learning a rule in neural networks

Reference 25

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Observation d8ce9f28-05f3-41f1-a8a5-ec21b5621a3a · outbound

This paper cites Thermodynamics with continuous information flow.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Thermodynamics with continuous information flow

Reference 26

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This paper cites Stochastic thermodynamics of bipartite systems: transfer entropy inequalities and a Maxwell's demon interpretation.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Stochastic thermodynamics of bipartite systems: transfer entropy inequalities and a Maxwell's demon interpretation

Reference 27

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Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value The thermodynamics of prediction

Reference 28

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This paper cites Semantic information, autonomous agency, and nonequilibrium statistical physics.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Semantic information, autonomous agency, and nonequilibrium statistical physics

Reference 29

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This paper cites Thermodynamic Machine Learning through Maximum Work Production.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Thermodynamic Machine Learning through Maximum Work Production

Reference 30

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This paper cites Sudo, The thermodynamic value of data: Meaning as enablement under budget constraints (2026), (unpub- lished).

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Sudo, The thermodynamic value of data: Meaning as enablement under budget constraints (2026), (unpub- lished)

Reference 31

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This paper cites Sudo, Replacement costs of state and structure infor- mation in opaque thermodynamic gates (2026), (unpub- lished).

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Sudo, Replacement costs of state and structure infor- mation in opaque thermodynamic gates (2026), (unpub- lished)

Reference 32

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This paper cites The Work Capacity of Channels with Memory: Maximum Extractable Work in Percept-Action Loops.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value The Work Capacity of Channels with Memory: Maximum Extractable Work in Percept-Action Loops

Reference 33

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This paper cites Mechanism-resolved second law for multipartite systems: An entropy-production ledger for correlation loss.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Mechanism-resolved second law for multipartite systems: An entropy-production ledger for correlation loss

Reference 34

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Observation 8bb19c1d-39c5-4459-8a36-7fcb766b35ee · outbound

This paper cites The Resource Theory of Quantum States Out of Thermal Equilibrium.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value The Resource Theory of Quantum States Out of Thermal Equilibrium

Reference 35

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Observation 4aee082b-3bd5-4889-9e61-785d656b5adc · outbound

This paper cites Thermodynamic Overfitting and Generalization: Energetic Limits on Predictive Complexity.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Thermodynamic Overfitting and Generalization: Energetic Limits on Predictive Complexity

Reference 36

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This paper cites Caraffa, Dissipative learning: A framework for viable adaptive systems (2026), arXiv:2601.17933.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Caraffa, Dissipative learning: A framework for viable adaptive systems (2026), arXiv:2601.17933

Reference 37

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This paper cites Sudo, A robustness spectrum for hidden target spec- ifications: Degeneracy, transfer, and effective leakage in opaque thermodynamic gates (2026), (unpublished).

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Sudo, A robustness spectrum for hidden target spec- ifications: Degeneracy, transfer, and effective leakage in opaque thermodynamic gates (2026), (unpublished)

Reference 38

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Observation b9b07c60-a83d-4435-94db-da6f39bc4b18 · outbound

This paper cites Shettell and A.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Shettell and A

Reference 39

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Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Dependence of dissipation on the initial distribution over states

Reference 40

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Observation 2321d395-0d7c-4a7c-92c5-8ca101bae003 · outbound

This paper cites Thermodynamic cost and benefit of memory.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Thermodynamic cost and benefit of memory

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Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Partially Observable Szilard Engines

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Observation 3a273627-a7ed-4d3e-8011-ed337b106740 · outbound

This paper cites The physical observer in a Szilard engine with uncertainty.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value The physical observer in a Szilard engine with uncertainty

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This paper cites Above and Beyond the Landauer Bound: Thermodynamics of Modularity.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Above and Beyond the Landauer Bound: Thermodynamics of Modularity

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Observation c6216a31-30b5-421e-8a0f-23eb1d755ef6 · outbound

This paper cites Watts-Per-Intelligence: Part I (Energy Efficiency).

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Watts-Per-Intelligence: Part I (Energy Efficiency)

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Observation 96d6b17c-0205-465b-ad75-8384ed138acc · outbound

This paper cites Watts-per-Intelligence Part II: Algorithmic Catalysis.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Watts-per-Intelligence Part II: Algorithmic Catalysis

Reference 46

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Observation 9eab54c3-2883-45c0-9959-f0052c6fac2f · outbound

This paper cites Finzi, S.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Finzi, S

Reference 47

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Observation a83e6b2a-219e-4af6-a3e0-57eea76fe6f7 · outbound

This paper cites Thermodynamic Limits of Physical Intelligence.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Thermodynamic Limits of Physical Intelligence

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This paper cites Thermodynamics of classifiers.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Thermodynamics of classifiers

Reference 49

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Observation 81238a13-90f6-4077-be21-818911f9badd · outbound

This paper cites Watanabe and R.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Watanabe and R

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This paper cites Lumbreras, R.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Lumbreras, R

Reference 51

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This paper cites Optimal Work Extraction and the Minimum Description Length Principle.

Thermodynamics of Learning: A Typed Four-Component Accounting of Memory, Fit, and Value Optimal Work Extraction and the Minimum Description Length Principle

Reference 52

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