AI News

Generalization Error Curves for Analytic Spectral Algorithms under Power-law Decay (arxiv.org)

Sample-Efficient LLM-Based Detection of Malicious Web Server Logs with Forensically Explainable Reasoning (arxiv.org)

QueryWeaver: Reliable Multi-Tool Query Execution Planning via LLM-Based Graph Generation (arxiv.org)

GeoGNN: Time Series Geo-Localization using Two-Tower Graph Neural Networks (arxiv.org)

How Reliable are Fairness Audits with Unreliable Data? (arxiv.org)

Spectral Truncation Kernels: Noncommutativity in $C^*$-algebraic Kernel Machines (arxiv.org)

Beyond Humans: Multispecies Animal Face Recognition Using Transfer Learning (arxiv.org)

STELLAR: Spatio-Temporal Environmental Learning with Latent Alignment and Refinement for Long-Tailed Species Distribution Modeling (arxiv.org)

Beyond Additivity: Causal Discovery in Location-Scale Noise Models with Hidden Variables (arxiv.org)

Active Learning with Foundation Model Priors: Efficient Learning under Class Imbalance (arxiv.org)

RACT: Retrieval Augmented Column-Table Learning and Prediction for Multi-Table Schema Matching (arxiv.org)

Constrained Paraphrase Consistency for LLM Hallucination Detection (arxiv.org)

Variational Proximal Policy Optimization (arxiv.org)

Mitigating the Contractivity Trap in Diffusion ODEs via Stein Stabilization (arxiv.org)

AgentCompile: An LLM-Guided Compiler for Direct CUDA Inference (arxiv.org)

Identifiability and Estimation for Unlabeled Finite Mixtures under Marginal Independence (arxiv.org)

RepoLaunch: Automating Build and Management of Code Repositories across Languages and Platforms (arxiv.org)

Jas: AI-Paired Engineering as a Revival of N-Version Programming (arxiv.org)

Boundary Variance Inflation Causes Acquisition Bias in Gaussian Processes (arxiv.org)

Disentangling Latent Risk Pathways via Bayesian Hypergraph Inference (arxiv.org)

Contribution Weights: A Geometrical Analysis of Self-Attention Transformers (arxiv.org)

Report the Floor: A Training-Free Conformal Interval Is a Mandatory Baseline for Probabilistic Time-Series Forecasting (arxiv.org)

Heterophily-Aware Adaptive Knowledge Distillation for Hypergraph Neural Networks (arxiv.org)

Transfer learning for causal forest (arxiv.org)

QDSP: An Interpretable Structured Learning Framework for Predicting Death or Cerebral Palsy in Very Low Birth Weight Infants (arxiv.org)

SAILS: Surrogate-based Analysis of Interactions via Local Effect Smooths (arxiv.org)

SNN-MLIR: An MLIR Dialect for Compiling Neuromorphic SNNs from NIR to Bare-Metal C (arxiv.org)

Cutting LLM Evaluation Costs with SySRs: A Bandit Algorithm that Provably Exploits Model Similarity (arxiv.org)

Barycentric Projections of Optimal Transport Plans on Riemannian Manifolds (arxiv.org)

Vector Space of Cycles (arxiv.org)

MEC-Cox: Machine-Learning-Assisted Generalized Entropy Calibration for ATT Marginal Hazard-Ratio Estimation (arxiv.org)

Improving Bayesian Optimization via Training-Aware Conditional Diffusion Models (arxiv.org)

LOTTERY: Learning from Reference-Only Samples in Two-Sample Testing under Size Asymmetry (arxiv.org)

Stable and Scalable Probabilistic Numerical Solvers for Stiff and High-Dimensional ODEs (arxiv.org)

Improving the sharpness in neural network-based parametric post-processing of ensemble forecasts (arxiv.org)

Rank Intervals for Leaderboards: A Hierarchical Framework for Model Evaluation (arxiv.org)

Generalization in Nonlinear Least Squares via Learned Feature Geometry (arxiv.org)

Estimate Collapsibility of Causal Effects in Completed Partial DAGs via Strong d-Convex Hulls (arxiv.org)

Multi-Armed Bandits with Arriving Arms: Sequential Screening, Dynamic Regret, and Sublinear Guarantees (arxiv.org)

Accelerating Birkhoff Projection for Manifold-Constrained Hyper-Connections (arxiv.org)

MST-Direct at Scale: Multivariate and Conditional Geostatistical Simulation via Sinkhorn Optimal Transport (arxiv.org)

Vessel Traffic Flow Prediction on Sparse Data via Spatio-Temporal Graph Neural Networks with a Learnable Tweedie Head (arxiv.org)

A Framework for Evaluating and Benchmarking Concept Drift Detection Methods (arxiv.org)

Large-scale empirical tuning and comparison of default optimizers for variational inference (arxiv.org)

Instrumented data for causal scientific machine learning (arxiv.org)

Partially Performative Prediction (arxiv.org)

Inference for High-Dimensional Sparse Spectral Precision Matrices (arxiv.org)

Assessing model calibration with boosting trees (arxiv.org)

How Deep Are Deep GPs, Really? A Sharp Threshold and a Non-Gaussian Limit for Compositional GPs (arxiv.org)

A Switching Beamformer for Highly Non-Stationary Environments (arxiv.org)