Paper statuses — A work’s standing in this record: whether it is worth reading. Not whether its findings are true — that is the THEORY scheme’s business, and the two can disagree in either direction.
Attic — retired with a reason — too narrow, too theoretical, or simply not interesting enough to carry.
15 of 2004 LIT documents. Back to the full index.
| # | Title | Summary | Status |
|---|---|---|---|
| LIT-001 v2 | Quantum Mechanics can be understood through stochastic optimization on spacetimes | Lindgren & Liukkonen (2019), DOI-10.1038/s41598-019-56357-3. The paper derives a Stueckelberg-type equation i∂φ/∂τ = (1/2m)□φ − Vφ (Eq. 36) from an HJB equation, but only after putting the imaginary unit in twice by hand. The first i is a factor √g = i multiplying the Lagrangian; standard relativity uses √(−g) = 1. The second is a complex “variance” σ² = i/m (Eq. 29), chosen so that the Hopf–Cole substitution J = log φ linearizes the equation. The linearization itself is the standard λ = σ²·(control cost) condition. The Schrödinger equation (Eq. 43) then comes from c → ∞ plus complex conjugation. The Dirac equation is not derived, and the “Klein–Gordon equation” (Eq. 40) has 2mV where m² should be. | Rejected — read in full 2026-09-25 (NOTE-003); the claim that the i comes from the Minkowski metric depends on the non-standard √g, not √(−g). The complex noise it also needs leaves no real stochastic process or optimization behind. Nelson (1966), Guerra–Morato (1983) and, for the control-theory side, Kappen (2005) cover the real content better. |
| LIT-038 v2 | The Relativity of Causal Knowledge | D’Acunto & Battiloro (2025), ARXIV-2503.11718. The paper defines SCMs as functors I → Prob and interventions as natural transformations (which requires invertible mixing functions). It encodes each non-intervened SCM as the convex space Δ(V, Ω) of all probability measures on its endogenous space, and puts these spaces on a graph as stalks of a network sheaf and cosheaf. The restriction maps are interventionally consistent α-abstractions and the extension maps are unspecified affine maps. “Relative causal knowledge” is the image of alternating restriction and extension along a path (Def. 11). The two substantive-looking theorems are either unsound or vacuous. Theorem 1 (every convex combination of a model’s interventional measures is a soft-interventional measure of it) rests on a proof step that is false. Theorems 2 and 3 hold for any pushforward map, so interventional consistency does no work in them. There are no results about the sheaf. | Rejected — read in full 2026-09-25 (NOTE-050); Not worth a reader’s time as a source of results. Its one non-trivial theorem is unsound as proved and false in general, its encoding theorem is vacuous, and §4 contains definitions only. A reader wanting category-theoretic causal abstraction should go to Rischel’s thesis or Beckers–Halpern. A reader wanting sheaves on networks should go to Curry or Hansen–Ghrist. |
| LIT-050 v2 | Mean-Field-Type Game Theory with Rosenblatt Noise | Tembine et al. (2025), ARXIV-2506.08025. The paper’s control and game results use linear state feedback, and they depend on the Rosenblatt noise only through its covariance, which is exactly fBM’s with the same H. They are therefore identical to the fBM results. The ergodic LQ gain (Thm 4), K̂ = −[b₁ + √(b₁² + 4H(1−H)b₂²q/r)]/(2b₂(1−H)), is correct and reduces to the Brownian LQR gain at H = ½. But the paper’s headline “suboptimality of noise approximation” (§VI-A, repeated for the variance-aware control, zero-sum, non-zero-sum and MFTG settings) holds only against surrogates with a different covariance; against fBM with the same H it is false. The ML claim that Rosenblatt “super-diffusion transformers” “significantly enhance the performance of generative machine intelligence models” (§XIV-C) has no model, training, dataset or experiment behind it anywhere in the paper. | Rejected — read in full 2026-09-25 (NOTE-068); not worth a reader’s time. The control-theoretic results are earlier papers’ (its refs [43]–[46]) restated. Its central new claim, that Gaussian and fBM surrogates give suboptimal control, is false for fBM with matching H, since the costs depend only on covariance. Its empirical sections are unsourced vignettes: numbers without references, “Rosenblatt shape” fits without any fitting procedure, and data from the first author’s own startups. Its ML claim is an assertion with no model or experiment. A reader wanting Rosenblatt-noise LQ control should go to Čoupek–Duncan–Maslowski–Pasik-Duncan (CDC 2018, ref [43]) and Čoupek–Duncan–Pasik-Duncan (SPA 2022, ref [27]). |
| LIT-068 v2 | How Local Separators Shape Community Structure in Large Networks | Frenkel & Carmesin (2025), ARXIV-2504.14501. This is a comparison of the authors’ local 1- and 2-separator decompositions against Infomap, Label Propagation, Leiden and Louvain (igraph) on five sparse graphs (62 to 9,133 nodes). Local separators score lower overlapping modularity than the modularity optimisers everywhere, and lower than Infomap on 3 of 5 graphs (Table 2). Their edge is confined to high density thresholds on the two road networks, where the best radius gives a handful more qualifying clusters: about 12 against about 5 at β ≥ 1.25 on Euroroads, and about 50 against about 40 for Infomap at β ≥ 1.5 on NRW (Figs. 3–4). On Netscience all methods are similar. At δ = 1 on both road networks, and at δ = 1.25 on NRW, Infomap yields more qualifying clusters than any local-separator setting. | Rejected — read in full 2026-09-25 (NOTE-085); not worth a reader’s time. Its critique of modularity (§2.4) contains two false statements. Its own “community detection problem” (§2.5) is defined but never scored. Read at the paper’s own thresholds, the figures do not support “consistently identify the densest communities”. The method itself is never defined here, so a reader wanting local separators should go to Carmesin & Frenkel, arXiv:2312.12354 (its ref. [9]). |
| LIT-102 v2 | Pregeometry, Formal Language and Constructivist Foundations of Physics | Arsiwalla et al. (2023), ARXIV-2311.03973. A programmatic essay with no construction, theorem or model of its own. It argues that inferential justification in a materialist ontology regresses without end (§3), that a “coherentist” constructivism escapes the regress, and that Wheeler’s pregeometry is therefore best read as “structureless structure”: the types and compositional rules of a computational language such as homotopy type theory (§§4, 6). Every construction of space from such rules that it points to is in the authors’ own earlier papers ([13, 17, 18]) or is promised as “a forthcoming publication” (fn. 1, p. 3). | Rejected — read in full 2026-09-26 (NOTE-182); not worth a reader’s time as an argument for its thesis. The step from the regress problem to formal languages is asserted, not argued, and its one physics claim (that “widespread consensus” holds spacetime to be fundamentally discrete, p. 5) is overstated. A reader wanting pregeometry is better served by the sources it cites: Meschini, Lehto & Piilonen’s “Geometry, pregeometry and beyond” ([63]) for the history, and Döring & Isham’s topos programme ([36–40]) for a worked formal-language approach. |
| LIT-126 v2 | The Category Error in Contemporary AI Safety Discourse and Why Non-Sentient Systems Cannot Be Moral Machines | Vieira (2026), https://philarchive.org/archive/VIETCE. A ten-page position paper. Its one explicit argument is “P1: moral status requires phenomenal consciousness; P2: current and foreseeable AI lacks it; C: such AI lacks moral status” (§3, p. 3). P1 rests on Swanepoel 2020, and P2 is asserted without argument. From this Vieira recommends that AI-safety frameworks measure only effects on sentient beings (§6.4). His replies retreat from C to a weaker norm, “we should not attribute moral status absent positive evidence of phenomenal consciousness” (§6, p. 6; §7.1), and he never says what that evidence would be. | Rejected — read in full 2026-09-26 (NOTE-128); not worth a reader’s time. Its load-bearing premise (P2) is asserted, not argued. The abstract promises replies from human–AI interaction studies and global perspectives that the body does not contain. The “moral zombie” framing and the sentientist criterion are taken from Véliz (2021) and Swanepoel (2020), neither held here, and a reader gets both more directly from those sources. |
| LIT-133 v2 | Towards a Generalized Theory of Observers | Elshatlawy et al. (2025), ARXIV-2504.16225. The paper defines a “minimal observer” as a finite-state transducer with a boundary: a tuple O = (X, Y, Z, f, g, B) with |X| > 1, |Y| ≥ 1, |Z| ≥ 1 and feedback closure (Def. 4.1, p. 57). It then asserts, without derivation, that measurement outcomes, reference frames, coarse-graining and the quantum–classical cut are all defined by such observers. The paper’s only formal results are that isomorphism of these machines is an equivalence relation (“Theorem 2”, p. 93), and a complexity bound C(O) ≥ log 2 (Prop. 4.1, p. 94) whose correction term Λ is never defined and whose proof supports only C(O) ≥ 0. | Rejected — read in full 2026-09-26 (NOTE-121); not worth a reader’s time as a theory of observers. Its one definition is a Moore machine with an unformalised boundary, its “theorems” are definitional, and its quantum claims are asserted, including the claim to identify “the exact moment and mechanism of quantum collapse” (p. 75). A reader wanting minimal observers or agents is better served by the sources it surveys: Ashby, Hartle’s IGUS, Fields, and Gielen & Wise’s observer space in §4.10.3. |
| LIT-182 v3 | Towards ethical evolution: responsible autonomy of artificial intelligence across generations | Terziyan et al. (2025), DOI-10.1007/s43681-025-00759-9. The paper proposes, without implementation, formalism or experiment, that an AI system which designs further AI systems should pass on one “immutable” principle. The principle is: do not directly harm humanity or violate fundamental human values; monitor and mitigate misuse of your outputs; and make every derivative inherit this principle (p. 12). The mechanisms are a genetic-algorithm analogy, with immutable and mutable “genes”, constrained crossover and filtered mutation, together with “temporal cloning”. The paper is inconsistent about its central notion. The principle is enforced once by a penalty F = Q − α·P (p. 9) and once by “unbreachable” hard constraints (p. 13). And it is “immutable” only in its architecture, while its ethical content stays “adaptable” (p. 14). | Rejected — read in full 2026-09-26 (NOTE-156); not worth a reader’s time. It is a programme statement whose one concrete proposal is contradicted by the paper’s own later sections. It demonstrates nothing, even though its conclusion says it does (p. 21). It does not engage the alignment work on preserving goals across successors that the problem calls for. A reader interested in value preservation under recursive self-design would do better starting from that literature. |
| LIT-212 v2 | Do Large Language Models Hallucinate Electric Fata Morganas? | Šekrst (2025), ARXIV-2608.18816. A conceptual essay whose one substantive thesis is this. Following Dziri et al., hallucination includes any output “not rooted in the model’s source data”, including expressed emotions and opinions (§6). An LLM’s apparent inner life is therefore always a candidate hallucination, so any real AI consciousness “might always remain epistemically inaccessible” (§8). The empirical support is two unquantified anecdotes: a Titanic question put to gpt-3.5-turbo and GPT-4 at unstated temperatures, and an extractive-QA BERT mislabelled “WikiBERT”. Neither can bear the weight the paper puts on it. | Rejected — read in full 2026-09-26 (NOTE-176); not worth a reader’s time. Its one idea, that self-reports of inner states are exactly what a system trained on human text would produce whether or not it has them, is a single paragraph’s point. Its experiments are anecdotes with no reported settings, one of them on a mislabelled model. It asserts both that current LLMs lack understanding and that machine consciousness would be undetectable, and never reconciles the two. |
| LIT-215 v2 | Defending Informational Structural Realism: The View of Alternatives | Karpenko (2025), DOI-10.5840/eps202562230. Karpenko argues against V.E. Terekhovich’s non-eliminative OSR, which holds that entities and structures exist but “objects do not exist”. He extends Floridi’s informational structural realism with one thesis: empirically equivalent but structurally different models (wave/particle/field descriptions, superstring dualities, AdS/CFT holography, equivalent programs in digital physics) have equal ontological standing. Since nothing stands “behind” them with a privileged configuration, the descriptions, i.e. information, are themselves fundamental, and theoretical objects exist as ontological primitives. There is no formal argument, and the physics is presented by assertion, with several errors. | Rejected — read in full 2026-09-26 (NOTE-096); not worth a reader’s time on this topic. It misreports its source (Floridi, LIT-152) on the points it builds on, and it states contested or wrong physics as established. Its one novel move, reading dualities as equal-status alternatives rather than underdetermination, is asserted, not argued, and is done properly in the duality literature (LIT-113, LIT-199). |
| LIT-270 v2 | Identifying Quantum Structure in AI Language: Evidence for Evolutionary Convergence of Human and Artificial Cognition | Aerts et al. (2025), DOI-10.3390/e28060622. Two findings are reported. First, prompted as test subjects on Aerts & Sozzo’s “The Animal Acts” concept-combination test, ChatGPT and Gemini give CHSH values above 2: 4 in a guided conversation, and 2.25 and 3.09 (ChatGPT) and 2.12 and 4 (Gemini) over 81 prompted repetitions, against 2.42 for the 81 humans in 2011. Second, the rank–frequency curve of one 2,861-word Gemini story fits a Bose–Einstein form with energy E_i=(i−1)^0.8 far better than a Maxwell–Boltzmann form. The authors take these as showing that LLM “code is structurally quantum” (§5). The CHSH analysis never checks the strongly context-dependent marginals in its own tables. One reported expectation value disagrees with its table. The Bose–Einstein fit is numerically a Zipf–Mandelbrot law. | Rejected — read in full 2026-09-27 (NOTE-243); not worth a reader’s time for its claims, because the data cannot carry them. The CHSH values come from tables whose marginals shift by up to 0.96 between contexts, the confound the record already holds against this very test design (LIT-264). The “Bose–Einstein versus Maxwell–Boltzmann” contest compares a Zipf-like curve with an exponential one on a single primed story. No goodness-of-fit statistic is reported, and there is no significance test for any LLM result. |
| LIT-271 v2 | Neural Tangent Kernel of Matrix Product States: Convergence and Applications | Guo & Draper (2021), ARXIV-2111.14046. In the sequential infinite-bond-dimension limit, with tensor variances σ_i²/√(|α_i||α_{i+1}|) and per-tensor learning rates (|α_i||α_{i+1}|)^{-1/2}, the NTK of a periodic MPS tends to K(x,x′)=Σ_k φ(x_k)·φ(x′k) Π{l≠k} σ_l² φ(x_l)·φ(x′_l). By my reduction this is (Σ_k σ_k⁻²) times the MPS’s own GP covariance, so gradient flow is kernel regression with a fixed product kernel. The Born-machine solution P_x(t)=1/m−(1/m−P_x(0))e^{−4mKt/Z} is correct (I checked it; Z is in fact conserved). The lazy-training lemma is heuristic, the positive-definiteness “proof” shows at most semi-definiteness, several constants are off by factors of n or 2^{−n}, and there are no experiments. | Rejected — read in full 2026-09-27 (NOTE-244); not worth a reader’s time as a source. Its one sound calculation (the infinite-bond MPS is a linear model in a fixed product-kernel feature space, so its NTK is its GP kernel up to a constant) follows in a line from multilinearity. Tensor Programs II (ANTH-LIT-557) covers such architectures rigorously. The paper’s distinctive claims are the lazy-training proof, positive-definiteness “without any extra assumptions of the data set”, and “over-fitting is naturally avoided”. The first is circular, the second is false for the finite local dimensions it uses, and the third is contradicted by its own memorisation result. |
| LIT-276 v2 | Measurement as Sheafification: Context, Logic, and Truth after Quantum Mechanics | Ghose (2025), ARXIV-2512.12249. A programmatic essay, with no theorem, model or computation of its own. It restates Abramsky & Brandenburger’s criterion (contextuality and non-locality as the absence of a global section of a presheaf over measurement contexts) and adds three things. It declares measurement to be “sheafification” of that presheaf, without specifying a site, a topology or any sheafified object. It asserts that the Ghose–Patra seven-valued logic is a finite Heyting algebra, without giving an order or operations. It proposes that a quantum potential scaled by 0 ≤ λ ≤ 1 (λ = 1 quantum, λ = 0 classical Hamilton–Jacobi) carries the presheaf continuously to a sheaf, which is asserted, not modelled. Its one worked formula, v2’s Čech “obstruction class” [δs], is a coboundary and so is zero by construction. | Rejected — read in full 2026-09-27 (NOTE-249); not worth a reader’s time for its formal claims. Every correct formal ingredient is Abramsky & Brandenburger’s (LIT-016) or Abramsky, Mansfield & Barbosa’s, and both are better read in the original. What the essay adds is either unconstructed (the sheafification, the site, the seven-element Heyting algebra, the link from λ to cohomology) or wrong as stated: v2’s obstruction class is zero by construction, a sheaf topos is not in general Boolean, and classical distributions do not form a sheaf. Its only value is as a record of a position, the Bohrian reading of contextuality plus the Jaina analogy. |
| LIT-373 v4 | The two dragons of cognition: recursive condensation for predictive processing | Li (2026), DOI-10.3389/fncom.2026.1778902. A “Hypothesis and Theory” essay proposing that the neocortex is a “biological Savitch machine”. Alternating expansion (“odd parity”) and contraction (“even parity”) phases manufacture the disjoint closed sets of Urysohn’s Lemma, and storing (“memoizing”) the condensed tokens converts exponential search into polynomial “navigation”. Its one non-standard formal result, Theorem 2, R(N) ∝ b^{αN} (§5.2.2, p. 11), is stated without proof. There is no data, simulation or model. The two mathematical pillars are misdescribed: Savitch’s theorem saves space at the cost of time and does not memoize, and Urysohn’s Lemma gives a continuous separator, not a linear one, and is not an “if and only if”. | Rejected — re-read jointly with LIT-374 and arXiv 2602.07974 on 2026-10-01 (NOTE-321); Read jointly with LIT-374 and the companion StrLT preprint (arXiv 2602.07974), the essay is the cognitive motivation of a coherent programme: structure is discovered by costly search, condensed into frozen tokens, and reused cheaply. It is not just a misuse of two theorems. Read charitably, its mathematical slips are repairable and are not the reason to set it aside: the Urysohn “iff” and linear readout, Savitch as memoisation, the Definition 2 clash. The reason is what is left after repair: an amortised-inference and complementary-learning-systems picture already in the literature it cites; a neural mapping whose predictions do not discriminate it from standard consolidation accounts; one original quantitative claim, Theorem 2, that is not argued. A reader who wants the programme should read LIT-374 and the companion, where it is made precise. |
| LIT-377 | On Context-Content Uncertainty Principle | Li (2025), arXiv:2506.20699 v1. It posits that structured content (priors, schemas) has far lower entropy than context (sensory input), and concludes that inference should run from content to context, minimizing H(context | content). On that it builds four layers of principles. The first is structure before specificity and its equivalents. The second covers precision-weighted attention, slower learning for content than for context, and memory as low-entropy attractors. The third is staged structure-first learning, and the fourth hierarchical composition. It then reads predictive coding, the free energy principle, active inference and attractor dynamics as instances. Everything is asserted or argued informally. There are no experiments, and several proofs are wrong or missing. | Rejected — by LIT-374; read in full 2026-10-01 (NOTE-325); not worth a reader’s time as a source of results. Its foundation is the entropy chain rule plus an assumption, H(content) ≪ H(context), and from these it reads off a direction of inference. Of its eight theorems, one is proved only in sketch, one equivalence proposition is marked “proof skipped” and argued only in words (App. H), and the proofs of Theorems 6–8 swap the roles of content and context relative to the statements. The proof of Theorem 1 states the inequality backwards. Theorem 3 rests on D_KL(q‖p) ≥ H(q) − H(p), which is false in general. The abstract’s “computational simulations” are not in the paper. The author’s own v2 (June 2026) replaced the whole framework under a new title. |