Expander SAEs apply left-d-regular expander masks to TopK SAEs, learning only dn decoder parameters instead of mn and tracing a storage-fidelity frontier that reaches 293x compression with 84% retained performance on Qwen2.5-3B.
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The normalized orbit of a bounded normal operator can be a frame, providing a counterexample to Conjecture 3.
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SLayerGen generates crystals invariant to any space or layer group via autoregressive lattice and Wyckoff sampling plus equivariant diffusion, achieving gains over bulk models on diperiodic materials after correcting a prior loss inconsistency for hexagonal groups.
Every proper minor-closed graph class admits an optimal (1+o(1)) log n bit adjacency labeling scheme.
A directed weighted two-graph model separates feasibility from movement in solution discovery and yields a detailed complexity classification for path and shortest-path discovery.
The method reformulates ALE mesh motion as independent multi-patch spline parameterizations per time step, using barrier functions, tangential-slip reparameterization, and constant-preserving quasi-interpolation to enable large-rotation FSI simulations.
Superconductivity in high-pressure MnB4 is induced by altermagnetic spin fluctuations, yielding extended-s pairing symmetry.
A new qubit-efficient HUBO encoding for graph partitioning problems like minimum coloring uses logarithmic bits and a lexicographic penalty to cut resources while providing provable optimality conditions.
A survey of 172 open educational datasets from 204 papers across LAK, EDM, and AIED conferences reveals trends, 143 previously uncatalogued datasets, field gaps, and an 8-item PRACTICE checklist for better data publication.
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O(n log n) algorithm and matching Omega(n log n) lower bound for partitioning a simple polygon's boundary into the minimum number of contiguous visible segments.
Introduces a method to design structure-specific relational inductive biases for a base transformer architecture, enabling end-to-end transcription of documents with intrinsic structures, demonstrated on sheet music, shape drawings, and mechanical engineering drawings.
The paper introduces a probabilistic sign rule for quotients of positive series and integral transforms that reduces monotonicity, log-supermodularity, and log-convexity to kernel sign criteria via moment identities, and applies it to derive new inequalities for hypergeometric, Stieltjes, and Prabha
SPoILeR uses multimodal pre-training to enable accurate novel view synthesis of infrared, polarimetric, and multispectral data from RGB-supervised fine-tuning on new scenes.
NEvo performs evolutionary search guided by a dynamic voxel-level encoding model to synthesize videos that maximize predicted activity in target brain ROIs, recovering known selectivities and revealing temporal dynamics differences.
Every n-vertex H-minor-free graph admits a 3-coloring with monochromatic components of size O_H(n^{4/9}).
The Spin-MInt algorithm is proven symplectic for general K electronic states via explicit verification of the condition MJM^T = J on the coadjoint orbit of the su(K) Lie-Poisson algebra.
The authors synthesize a typology of fourteen OSS sub-genres from a review of 3,925 papers and present a research agenda on cross-sub-genre generalization.
Structural identifiability analysis shows point sources restore identifiability for inferring spatial stochastic dynamics parameters from static snapshots, unlike distributed sources, with limits depending on modeling choices.
Maximal quantum leakage upper-bounds quantum inference accuracy; optimal encodings are pure states, with tight frames and equiangular tight frames optimal when system dimension is small.
In multistage SI(k)R models, the relationship between prevalence peak and weighted stage functional maxima varies with scaling of progression rates, converging under Erlang scaling to a delay model that justifies the factor-two approximation with error bounds and corrections.
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Parameterization-driven arbitrary Lagrangian-Eulerian method for large-deformation isogeometric fluid-structure interaction
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Projection-Based Reconstruction for Achieving High-Order Accuracy from Low-Order DGSEM Simulations
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Complementary families of approximating polynomials with applications to finite element methods applied to differential equations of arbitrary even spatial order
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Kernel-based linear system identification using augmented Krylov subspaces
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Invariant domain preserving limiting of time explicit and time implicit discretizations for systems of conservation laws
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On the Practical Impact of Local Linear Instabilities in Entropy-Stable Schemes
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Adaptive anisotropic composite quadratures for residual minimisation in neural PDE approximations
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A Shifted Cohesive-Zone Method for Non-Interface-Fitted Meshes with Applications to Crystal Plasticity
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Neural parametric representations for thin-shell shape optimisation
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A high order stabilization-free virtual element method for general second-order elliptic eigenvalue problem
A novel high-order stabilization-free virtual element method is developed for general second-order elliptic eigenvalue problems, with optimal a priori error estimates for eigenspaces and eigenvalues, validated on various polygonal meshes.
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Efficient Krylov solvers for inverse source problem in 2D space-time fractional diffusion equation
GLT-based preconditioners are built for multilevel Toeplitz systems from finite-difference discretization of the quasi-boundary regularized inverse source problem, producing eigenvalue clustering around one and faster GMRES convergence.
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Locally conservative redistribution limiting and applications to the approximation of conservation equations, Part II
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Multiscale Fourier Neural Operator for Inverse Wave Scattering in Highly Oscillatory Media
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An indefinite LOBPCG type of algorithm for detecting a definite Hermitian matrix pair
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Singularity Formation: Synergy in Theoretical, Numerical and Machine Learning Approaches
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Justification and structure- and asymptotic-preserving discretizations of a hyperbolized Cahn-Hilliard equation
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Spectral Bounds for Tensors Derived from Trace Functionals and Wasserstein Distance in Tensor Spaces
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