AI News

Function-Space Temporal Self-Distillation for Policy Optimization (arxiv.org)

Subdata Selection for Measurement-Constrained Linear Regression under Model Misspecification (arxiv.org)

Outperforming 1000 Euclidean Layers With Hyperbolic Goal-Conditioned RL (arxiv.org)

Embedding Geometry Shapes LLM Routing: Tracing Failure Modes and Improving Generalization (arxiv.org)

What Information Buys in Active Inference (arxiv.org)

Loss Curvature as a Sampling-Free Proxy for Memorization in Diffusion Models (arxiv.org)

Limits of Statistical Assurance for Embodied and Agentic AI under Adaptive Adversaries (arxiv.org)

Linear regression with probabilistic networks for network-linked data (arxiv.org)

Thompson Sampling for Learning in Zero-Sum Games (arxiv.org)

Inverse Reasoning Models for Efficient Post-Training and Verification from Answer-Only Data (arxiv.org)

The minimal width of neural networks and immersions of real projective space (arxiv.org)

Mixed Poisson diffusion models and application to posterior sampling (arxiv.org)

Backpropagating Verifier Rewards Through Continuous Flow Language Models (arxiv.org)

Weighted Adjoint Matching: Finetuning Flow Matching Models with Time-Dependent Control Cost (arxiv.org)

Minimax estimation of the pseudo-spectral gap of continuous Markov chains, with applications to empirical concentration bounds (arxiv.org)

Convergence Rates of Gaussian Process Thompson Sampling for Efficient Global Optimization (arxiv.org)

On the Optimisation Landscape of Overparameterised Weighted MMD (arxiv.org)

Text-Informed Training Data Filtering for Enhanced Virtual Flow Meter Performance (arxiv.org)

Calibration and Risk-Budgeted Decisions with System One Models (arxiv.org)

SNACK: A Sequential Notation Framework for Probabilistic Graph Generation (arxiv.org)

Risk-Controlled DFT Selection for Machine-Learned Interatomic Potentials (arxiv.org)

On Inherent Privacy of Posterior Sampling: A Unified R\'enyi-Divergence Framework (arxiv.org)

Noisy-Label Calibration with Multiple Unreliable Labels (arxiv.org)

A Bregman Proximal Viewpoint on Neural Operators (arxiv.org)

High-Probability Regret Bounds for Feel-Good Thompson Sampling (arxiv.org)

State-Matched Sequence Conformal Prediction (arxiv.org)

Multi-Sensitive Distributional Fairness: Joint Wasserstein Audits and Shapley Allocation (arxiv.org)

Structure-aware Bayesian full waveform inversion via diffusion-regularized Stein variational gradient descent (arxiv.org)

Test-Time Forecasting: Recurrent Depth Enables In-Context Dynamics Prediction (arxiv.org)

Student Copula Markov Networks (arxiv.org)

Neural Supervised Clustering for Learning Individualized Treatment Rules with Many Treatments (arxiv.org)

Conformalized Physics-Informed Weak Regression for Parameter Estimation in Epidemic Models (arxiv.org)

Discrete Diffusion Models are Minimax Optimal Under Sparsity (arxiv.org)

Semi-Amortized Bayesian Inference with Reusable Local Posteriors (arxiv.org)

Asymptotic Behavior of Transformers (arxiv.org)

Delay Complexity Dimension: Learning with Delayed and Censored Labels (arxiv.org)

Projected Wasserstein-Fisher-Rao Flows for Hawkes Background-Intensity Estimation (arxiv.org)

Generalizing Identifiability Results in Causal Discovery from Complete Data to Missing Data Settings (arxiv.org)

Wong--Zakai Convergence and FNO Learning for Stochastic Volterra Equations (arxiv.org)

Bayesian Causal Forests for Zero-Inflated Continuous Outcomes (arxiv.org)

A Large-Dimensional Analysis of Least-Squares Federated Learning via Generalized Total Variation Minimization (arxiv.org)

On Global Joint Lower Bounds in Zeroth-Order Nonconvex Optimization (arxiv.org)

Large-Step Last-Iterate Convergence of Random-Reshuffling Stochastic Gradient Descent (arxiv.org)

Posterior Frequencies and the Cost of Not Fitting: A Correction to a Memorization Lower Bound (arxiv.org)

CB-Agent: Concept-Based In-Context Learning for Sequential Action Selection (arxiv.org)

What the Model Cannot See: Covert and Provable Text Invisibility in LLMs (arxiv.org)

Personalized LLM Recommendation with Semantic IDs: Autoregressive Beam Search vs. Multi-Token Prediction (arxiv.org)

LLM Value Functions for Credit Assignment in Agentic RL (arxiv.org)

Adaptive Look, Flexible Thought: Learning How and How Long to Think in Multimodal Reasoning (arxiv.org)

Counterfactual Gate-Support Decomposition: Separating Selection from Redistribution in Training-Data Filtering (arxiv.org)