Training-language dominance, not English inherent properties, determines brain-LLM alignment across English, Chinese, and French, with additional independent effects from typological distance concentrated in syntactic brain regions.
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Proposes a scale-calibrated median-of-means estimator for robust aggregation of distributed PCA estimates on the product of Euclidean space and Grassmann manifold.
Introduces De Simone laws over Kleisli categories that guarantee compositionality of coalgebraic trace equivalence and recovers the classical De Simone format while adding a probabilistic variant.
Aggregation mechanisms for surjective classifications are nearly dictatorial with high probability unless functions are nearly constant, with a full characterization of always-surjective mechanisms.
Derives covariant quadratic expansion in extrinsic curvature of the nonlocal effective action for a massless scalar field on manifolds with boundary, extending Monge-patch results to general surfaces.
The paper presents randomized tests with explicit query bounds for properties including number of leaves, maximum degree, typical distance, and diameter in tree-structured graphical models.
A solvable hierarchical model with power-law feature strengths yields explicit power-law scaling of prediction error through sequential recovery of latent directions by a layer-wise spectral algorithm.
Bayesian PLSs are special cases of non-stationary affine PIMs which are proven calibrated, and affine tracing automates construction of probabilistic iterative methods from classical code.
Moonflowers are introduced as set families with per-set unique elements, yielding near-optimal extremal bounds that enable logarithmic code sparsification with a matching lower bound.
Projective Kummer-type manifolds with finite-order symplectic birational self-maps acting nontrivially on H² are twisted modular except for Picard rank 3 cases characterized by their NS lattices; specific Mukai vectors are identified for finite-order wall-crossing maps on modular examples.
SGD, approximations of Newton's method, natural gradient descent, and Adam are proven compatible with evolutionary dynamics when augmented with DLS noise, turning them into valid in silico simulations of asexual Darwinian evolution.
Polynomial-time algorithm samples the Sherrington-Kirkpatrick Gibbs measure at beta < 1/2 with o(1) TVD error by combining potential Hessian ascent, stochastic localization, covariance estimates, and Jarzynski equality with rejection sampling.
The profile maximum likelihood estimator for the location in anisotropic hyperbolic wrapped normal models is strongly consistent, asymptotically normal, and attains the Hájek-Le Cam minimax lower bound under squared geodesic loss.
Introduces anytime-valid e-processes for first- and higher-order stochastic dominance that achieve power one and remain valid under continuous monitoring.
In open quantum systems, environmental coupling turns deterministic Krylov phase-space trajectories into stochastic ones by adding diffusion, destroying the hyperbolic mechanism for exponential complexity growth beyond a controlled scale.
Continuous focus groups enable repeated dialogue with autism care professionals across robot therapy phases to integrate evolving clinical insights and serve as an ethical safeguard.
A 2D neural cellular automaton spontaneously self-organizes into a Proto-CKY representation that exhibits syntactic processing capabilities for context-free grammars when trained on membership problems.
A 3D morphoelastic rod model with local Stokes hydrodynamics predicts flutter instability and self-sustained 2D or 3D oscillations in clamped elliptic hydrogel filaments under constant axial electric field, with a secondary bifurcation to large-amplitude motions.
Existence of self-similar finite-mass solutions is proved for the time-fractional porous-medium equation in the optimal range m > (d-2)_+/d for all d ≥ 1, with compact support for m > 1 and heavy tails for m_c < m < 1.
Chern-Simons theory on a strip yields boundary current algebras for oppositely propagating chiral bosons whose velocities follow from a bulk-boundary consistency condition and are independent of strip width.
LLMs display a consistent pattern of elevated form-meaning divergence and uniform rhetorical device use in argumentative texts compared to humans, quantified by new metrics FMD, GPR, and RDDE.
OrbEvo uses equivariant graph transformers to learn the time evolution of TDDFT wavefunction coefficients, accurately reproducing wavefunctions, dipole moments, and absorption spectra on QM9 and MD17 molecular datasets.
Causal regularities in special sciences are associated with an entropy that cannot decrease from robust causes to their effects.
Optimal additive baseline IPS asymptotically dominates SNIPS in off-policy evaluation mean squared error.
citing papers explorer
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Brain-LLM Alignment Tracks Training Data, Not Typology
Training-language dominance, not English inherent properties, determines brain-LLM alignment across English, Chinese, and French, with additional independent effects from typological distance concentrated in syntactic brain regions.
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On the Emergence of Syntax by Means of Local Interaction
A 2D neural cellular automaton spontaneously self-organizes into a Proto-CKY representation that exhibits syntactic processing capabilities for context-free grammars when trained on membership problems.
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Saying More Than They Know: A Framework for Quantifying Epistemic-Rhetorical Miscalibration in Large Language Models
LLMs display a consistent pattern of elevated form-meaning divergence and uniform rhetorical device use in argumentative texts compared to humans, quantified by new metrics FMD, GPR, and RDDE.
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Model Collapse as Cultural Evolution
Iterated learning theory predicts and LLM experiments confirm non-monotonic compositionality during self-training, reframing model collapse as cultural transmission with matching human regularization patterns.
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SimSiam Naming Game: A Unified Approach for Representation Learning and Emergent Communication
SSNG replaces sampling-based updates in MHNG with symmetric self-supervised representation alignment using Gumbel-Softmax for discrete messages, yielding higher linear-probe classification accuracy on CIFAR-10 and ImageNet-100 than referential, reconstruction, or MHNG baselines.
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Readers make targeted regressions to plausible errors in reanalysis of "noisy-channel garden-path" sentences
Readers direct regressions to plausible error sites in noisy-channel garden-path sentences, consistent with Bayesian reanalysis under a noisy-channel model.