Remark. Open model-instance questions [ftip-00KF]
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The relative capability and cost of KDA, full attention, and JEPA candidates remain empirical questions. A reproducible comparison requires identified checkpoints or reproducible training, fixed evaluation seeds, and measured cost vectors. Architecture-specific ceilings remain estimands and hypotheses rather than established constants.

Context

Interface boundaries for alternative architectures [ftip-00K9]

Definition. JEPA comparability interface [ftip-00KA]

A JEPA-like architecture is comparable to an autoregressive model only after fixing the predictor, target representation, decoder or downstream interface, training objective, inference procedure, and evaluation law. A parameter-count match alone is not a typed comparison.

Remark. Representation and task interface are separate [ftip-00KB]

A latent predictor can be excellent under one decoder and unusable under another. The evaluation record must therefore include the interface that maps the representation to the declared task output.

Theorem. Interface-preserving architecture reduction [ftip-00KC]

If two architecture records induce the same conditional output law on a fixed task and evaluation interface, every evaluation functional \(J\) gives the same value. This is an immediate pushforward identity under the stated output-law and interface assumptions. It does not imply that distinct architectures are generally equivalent.

Example. Equal benchmark score can hide different ceilings [ftip-00KD]

Two architectures may tie on a finite benchmark while differing on an unmeasured task slice or longer context. Thus a single score cannot establish equal representational ceilings; the task family and evaluation coverage must be declared.

Remark. Architecture-independent model interfaces [ftip-00KE]

A result stated solely in terms of a model/interface map applies to every architecture realizing that map and satisfying its hypotheses. An architecture-specific conclusion can require further assumptions, as in Remark [ftip-00JK].

Remark. Open model-instance questions [ftip-00KF]
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Backlinks

Definition. Architecture-family transfer matrix [ftip-00LZ]

A transfer matrix records which interfaces, intervention arms, and budgets permit a comparison. Each row is a study record: its source, estimand, matched controls, evaluation coordinates, and declared scope boundary are explicit. A blank or incompatible cell is an incomparability finding, not a missing score to be imputed. The vector and evaluation coordinates are reported together under the conditional frontier of Definition [ftip-00JM].

Comparison cell	Source	Estimand	Matched controls	Cost / stability / monitorability	Status and scope boundary
Transformer--KDA/full attention	Remark [ftip-00KF], Definition [ftip-00LU], Example [ftip-00LQ]	Difference in utility, cost, and \(K_{\rm state}\) between KDA and full attention	Same task, model scale, recipe, context, seeds, and evaluation law	Report measured cost vector, training/inference stability, and state/failure observability	Open; a finite KDA--Transformer result does not establish an architecture-wide ceiling
Transformer--Mamba	Mamba, Sections 3.1--3.3; § [ftip-00OQ]	Difference in retrieval utility and \(K_{\rm state}\) at the declared budget	Task, scale, recipe, context, and inference budget	Report cost vector, recurrence stability, and state/failure observability	Open; selective compression does not transfer a retrieval result across tasks
Transformer--linear attention	Linear attention, Sections 3.2--3.3; § [ftip-00OQ]	Difference in retrieval utility and \(K_{\rm state}\) for associative summaries	Task family, feature map, context budget, and evaluation law	Report prefix cost, numerical stability, and summary-state observability	Open; associative summaries do not imply full-attention equivalence
Transformer--CTM or looped model	Continuous Thought Machine, Sections 3.1--3.5; § [ftip-00KG]; § [ftip-00OQ]	Difference in utility and \(K_{\rm adapt}\) per charged tick or loop	Input, base model, stopping rule, recipe, and charged internal compute	Report tick/loop cost, training and inference stability, and stopping-signal monitorability	Open; extra passes are charged and do not imply continuous-time behavior
Transformer--BDH	BDH, Section 3.2; § [ftip-00OQ]	Difference in task utility and \(K_{\rm state}\) under the reduced state interface	Task, state parameterization, credit horizon, systems stack, and cost	Report memory and compute cost, optimization stability, and state observability	Open; a reduced state-space proposal is not a production transfer result
Transformer-Recurrent Looped Transformer	§ [ftip-00OQ]; [zhang2026rlt, Sections 2-3 and 5-8]	Paired change in finite-task utility and \(K_{\rm state}\) under recurrent decoder feedback	Same task, model family, parameter count, training tokens, seeds, and feedback interface; causal no-feedback and chunking arms	Report encoder/decoder FLOPs, recurrent state, chunk latency, memory, stability, and state monitorability	Open and finite-only until a declared deployment arm and transfer record exist
Residual baseline: Deep Delta rewrite	§ [ftip-00OQ]; [zhang2026deepdelta, Sections 2-4 and 6]	Paired change in utility and rewrite-sensitive state behavior after the rank-one read/compare/target/write intervention	Matched residual capacity, optimizer, tokens, seeds, and model family; no-write, write-only, and capacity controls	Report inference FLOPs, memory, residual/cache state, numerical stability, and rewrite monitorability	Open; finite GPT-2 evidence does not establish a general capability or frontier claim
Core architecture--JEPA adjunct	I-JEPA, Section 3; § [ftip-00OQ]	Conditional change in \(K_{\rm repr}\) and \(K_{\rm plast}\) after the objective intervention	Same base artifact, target task, predictor budget, data, and optimizer arm	Report intervention cost, training stability, and representation/probe monitorability	Conditional; an objective intervention is not a replacement architecture
I-JEPA--SplitJEPA	SplitJEPA, Sections 3.1--3.4; § [ftip-00OQ]	Subspace identifiability and conditional change in \(K_{\rm repr}\)	Matched invariant correspondences, variant-rank premise, normalization, and encoder budget	Report probe cost, numerical and optimization stability, and subspace monitorability	Conditional; identifiability does not become a general I-JEPA guarantee
Core architecture--liquid dynamics	Liquid time-constant networks, Sections 1--2; § [ftip-00OQ]	Difference in utility and \(K_{\rm adapt}\) under the solver intervention	Input law, solver, step budget, tolerance, task, and cost vector	Report solver cost, numerical stability, and trajectory/failure monitorability	Open; continuous dynamics and solver choices remain intervention coordinates
Core architecture--Neural Operator	Neural Operators, Section 3; § [ftip-00OQ]	Difference in utility and \(K_{\rm repr}\) across discretizations	Function-space task, discretization family, operator layer, and evaluation law	Report training/inference cost, discretization stability, and field-observation monitorability	Open; discretization invariance under one source formulation is not task transfer

A completed row must report its paired observations through § [ftip-00L4] and the common-recipe, equal-tuning, and restricted-envelope arms of § [ftip-00JU]. Until those records are supplied, its status remains open or incompatible.