Alexandrov spaces with non negative curvature and displacement convexity of the entropy tensor

Coupling-Robust Accuracy in Multiphysics Physics Informed Neural Networks via Kronecker-Preconditioned Optimization

Non-normal spectral signatures of instability in neural network training dynamics

Optimization of randomized neural networks for transfer operator approximation

Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty

LLAMA LIMA: A Living Meta-Analysis on the Effects of Generative AI on Learning Mathematics

Learning Decision-Sufficient Representations for Linear Optimization

Parameterized Complexity of Stationarity Testing for Piecewise-Affine Functions and Shallow CNN Losses

Prabhakar function and unified fractional kinetic equation in bicomplex space

Computing Gamma(p/q) with Beta function values

Flows on Graded Manifolds

Optimal embedding dimension in the Nash--Tognoli theorem

An optimal first-order method for smooth and strongly convex composite optimization and its stationary limit

Sharp Bohr-Type inequalities for certain classes of close-to-convex functions

Invariants of real affine varieties based on their complexifications

Topological symmetric and braid homologies

A Formal Graph-Theoretic Framework for Pitch Class Set Analysis

Finite groups with high commuting probability for Sylow subgroups

Performance Bounds for Rollout Policies in Stochastic Shortest Path Problems

Real 2-blocks in quasi-simple groups

Maximal subalgebras of the Lie algebra $W_n(\mathbb{K})$

Cohomogeneity-One Ruled Hypersurfaces in $\mathbb{CP}^2$ and $\mathbb{C}H^2$

Global analysis of the Kuramoto flow

Cartier algebras through the lens of $p$-families

Positivity in the context of Hodge modules and Higgs bundles on Deligne-Mumford stacks

A secondary pairing between K-theory and K-homology, relative eta invariants, and zeta maps

Detecting and Correcting Sample-by-Sample Scale Distortion in RNA Sequencing Data

Neural Flow Operators can Approximate any Operator: Abstract Frameworks and Universal Approximations

LLMs as Noisy Channels: A Shannon Perspective on Model Capacity and Scaling Laws

On the Stability of Spherical Hellinger-Kantorovich Flows and Their Implications for Differential Privacy

Training-Free Looped Transformers

Move on Muon : A Hamiltonian probability gradient flow perspective of Muon optimizer

Entrywise Error Bounds for Spectral Ranking with Semi-Random Adversaries

Asymmetric Scaling Laws from Sparse Features

Is Dimensionality a Barrier for Retrieval Models?

RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programs

Commutator-Induced Uncertainty in VAEs

Weisfeiler-Leman Is Incomplete on Simple Spectrum Graphs, so Canonicalize Them

Sparse In-Network Learning via Shortest-Path Backpropagation and Finite-Rate Gating

Generalized Stochastic Approximation of the Log-Likelihood Ratio for Robust Sequential Change-Point Detection

Instance-Optimal Estimation with Multiple LLM Judges on a Budget

Entropy Equivalence Testing

Expand More, Shrink Less: Shaping Effective-Rank Dynamics for Dense Scaling in Recommendation

Any-Dimensional Invariant Universality

Operationalizing Individual Fairness via Gradient Descent and Bradley-Terry Models

Anytime Training with Schedule-Free Spectral Optimization

The Poisson Tail Conjecture for Primes in Short Intervals

Star-Shaped Integral Cartan-Type Matrices and an Egyptian-Fraction Classification of Affine Weighted Trees

A Complete Spectral Analysis of the CEV Operator with Applications to Arbitrage

Symplectic lattice counting and zeta functions of higher Heisenberg groups

Concise and elegant proofs of three formulas for complete Bell polynomials

On Reed-Muller subcodes, Grassmannian partitions and sum-free functions

Diffusion-based Denoising Beats Vanilla Score Matching in Parameter Estimation: A Theoretical Explanation

Resilience Characterization of AI-Native Wireless Receivers via Persistent Homology

The General Theory of Localization Methods

A Comprehensive Study of Clique Graphs and Clique Regular Graphs

Every signed planar graph is $5$-choosable: A short proof and refinements

PilotWiMAE: Pilot-Native Representation Learning for Wireless Channels

Proximal basin hopping: global optimization with guarantees

Democratizing Large-Scale Re-Optimization with LLM-Guided Model Patches

On Stability and Decomposition of Sample Quantiles under Heavy-Tailed Distributions

Symmetry-Compatible Principle for Optimizer Design: Embeddings, LM Heads, SwiGLU MLPs, and MoE Routers

Stochastic Non-Smooth Convex Optimization with Unbounded Gradients

Dimension-Free Convergence of Discrete Diffusion Models: Adjoint Equations Induce the Right Space

The Geometry of Cooperative Game Solutions: Stratified Egalitarian Shapley Values

An Axiomatic Theory of Tie-Breaking: Impossibility, Characterization, and Decomposition

PyCSP3-Scheduling: A Scheduling Extension for PyCSP3

Strategic PAC Learnability via Geometric Definability

Proximal-Based Generative Modeling for Bayesian Inverse Problems

Every Minimal Counterexample to the Erdős-Gyárfás Conjecture is Predominantly Cubic

SPHERICAL KV: Angle-Domain Attention and Rate-Distortion Retention for Efficient Long-Context Inference

NOVA: Fundamental Limits of Knowledge Discovery Through AI

TopoGeoScore: A Self-Supervised Source-Only Geometric Framework for OOD Checkpoint Selection

Minimal Filling Architectures of Polynomial Neural Networks: Counterexamples, Frontier Search, and Defects

Omni-scale Learning-based Sequential Decision Framework for Order Fulfillment of Tote-handling Robotic Systems

Grokking or Glitching? How Low-Precision Drives Slingshot Loss Spikes

Towards an Inferentialist Account of Information Through Proof-theoretic Semantics

Random test functions, $H^{-1}$ norm equivalence, and stochastic variational physics-informed neural networks

QUIVER: Cost-Aware Adaptive Preference Querying in Surrogate-Assisted Evolutionary Multi-Objective Optimization

Robust and Fast Training via Per-Sample Clipping

Beyond Continuity: Simulation-free Reconstruction of Discrete Branching Dynamics from Single-cell Snapshots

Deep Learning of Solver-Aware Turbulence Closures from Nudged LES Dynamics

Information bottleneck for learning the phase space of dynamics from high-dimensional experimental data

QED: An Open-Source Multi-Agent System for Generating Mathematical Proofs on Open Problems

Information-Theoretic Measures in AI: A Practical Decision Guide

Inference of Online Newton Methods with Nesterov's Accelerated Sketching

A Unified Fractional Regularization Framework for Sparse Recovery

Mathematical Foundations for Peer-to-Peer Lattice Computation

Geometric Layer-wise Approximation Rates for Deep Networks

RateQuant: Optimal Mixed-Precision KV Cache Quantization via Rate-Distortion Theory

Adaptive Learning via Off-Model Training and Importance Sampling for Fully Non-Markovian Optimal Stochastic Control. Complete version

Order-Optimal Sequential 1-Bit Mean Estimation in General Tail Regimes

Training-Free Rate-Distortion-Perception Traversal With Diffusion

Linear Regression with Unknown Truncation Beyond Gaussian Features

ArcMark: Distortion-Free Multi-Byte LLM Watermark via Optimal Transport

Feature Learning Dynamics in Infinite-Depth Neural Networks

ATHENA: Agentic Team for Hierarchical Evolutionary Numerical Algorithms

Normalizing Flows on Quotient Manifolds via Boundary Quotients

TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis

Program Evaluation with Remotely Sensed Outcomes

Efficient Gradient Estimation for Parameterized Quantum Systems with Lie Algebraic Symmetries

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