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.
Canonical reference
Title resolution pending
Canonical reference. 80% of citing Pith papers cite this work as background.
1094
Pith papers citing it
1
external citations · Crossref
Background
80% of classified citations
citation-role summary
background 254
method 24
baseline 6
dataset 5
extension 2
citation-polarity summary
authors
co-cited works
representative citing papers
The normalized orbit of a bounded normal operator can be a frame, providing a counterexample to Conjecture 3.
Introduces the largest freely available Italian clinical notes corpus with 4M notes and expert-annotated subset for a new CRF-filling benchmark.
Machine learning methods discover a new noncrossing-partition statistic interpreting q,t-Narayana polynomials and yield a combinatorial proof of their symmetry.
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.
A microlocal lift of Navier-Stokes dynamics on manifolds yields an if-and-only-if geometric criterion for solution blow-up in terms of deformation integrability, directional entropy, and lifted energy.
A 9U CubeSat detector can identify a thermonuclear weapon on a satellite from 4 km away by observing spallation neutrons induced by GeV protons in roughly one week.
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.
citing papers explorer
-
Parameterization-driven arbitrary Lagrangian-Eulerian method for large-deformation isogeometric fluid-structure interaction
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.
-
Entropy correction artificial viscosity for high order DG methods using multiple artificial viscosities
Multiple artificial viscosities with analytical optimal parameters enable more flexible entropy-stable DG simulations than monolithic viscosity for 1D and 2D problems.
-
Kernel-based linear system identification using augmented Krylov subspaces
Augmented Krylov subspaces jointly approximate quadratic forms and log-dets for faster MLE-based hyperparameter tuning in kernel-based linear system identification.
-
Adaptive anisotropic composite quadratures for residual minimisation in neural PDE approximations
An adaptive anisotropic composite quadrature strategy combined with refresh-based training narrows the gap between training and reference losses in neural residual minimization for PDEs while using quadrature points more efficiently.
-
Neural parametric representations for thin-shell shape optimisation
A neural network with periodic activations parameterizes thin-shell mid-surfaces so that network weights can be optimized to minimize structural compliance subject to a volume limit.
-
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.
-
Singularity Formation: Synergy in Theoretical, Numerical and Machine Learning Approaches
The work introduces a modulation-based analytical method for singularity proofs in singular PDEs and refines ML techniques like PINNs and KANs to identify blowup solutions, with application to the open 3D Keller-Segel problem.