LHAW: Controllable Underspecification for Long-Horizon Tasks
LHAW: Controllable Underspecification for Long-Horizon Tasks
LHAW: Controllable Underspecification for Long-Horizon Tasks
Generalized Robust Adaptive-Bandwidth Multi-View Manifold Learning in High Dimensions with Noise
From Collapse to Improvement: Statistical Perspectives on the Evolutionary Dynamics of Iterative Training on Contaminated Sources
Statistical Inference and Learning for Shapley Additive Explanations (SHAP)
Why Agentic Theorem Prover Works: A Statistical Provability Theory of Mathematical Reasoning Models
Solving PDEs in One Shot via Fourier Features with Exact Analytical Derivatives
Predictive-State Communication: Innovation Coding and Reconciliation under Delay
Deep Bootstrap
Flow-Enabled Generalization to Human Demonstrations in Few-Shot Imitation Learning
Neuro-symbolic Action Masking for Deep Reinforcement Learning
Bayesian Inference of Contextual Bandit Policies via Empirical Likelihood
Highly Adaptive Principal Component Regression
OmniSapiens: A Foundation Model for Social Behavior Processing via Heterogeneity-Aware Relative Policy Optimization
Beyond Kemeny Medians: Consensus Ranking Distributions Definition, Properties and Statistical Learning
From Diet to Free Lunch: Estimating Auxiliary Signal Properties using Dynamic Pruning Masks in Speech Enhancement Networks
A solvable high-dimensional model where nonlinear autoencoders learn structure invisible to PCA while test loss misaligns with generalization
Beyond Task Performance: A Metric-Based Analysis of Sequential Cooperation in Heterogeneous Multi-Agent Destructive Foraging
Convergence Rates for Distribution Matching with Sliced Optimal Transport
Robust Assortment Optimization from Observational Data
Spend Search Where It Pays: Value-Guided Structured Sampling and Optimization for Generative Recommendation
A Unified Experimental Architecture for Informative Path Planning: from Simulation to Deployment with GuadalPlanner
Self-Supervised Image Super-Resolution Quality Assessment based on Content-Free Multi-Model Oriented Representation Learning
Spectral-Spatial Contrastive Learning Framework for Regression on Hyperspectral Data
SecureScan: An AI-Driven Multi-Layer Framework for Malware and Phishing Detection Using Logistic Regression and Threat Intelligence Integration
Bayesian Signal Component Decomposition via Diffusion-within-Gibbs Sampling
Deep Learning-based Method for Expressing Knowledge Boundary of Black-Box LLM
Why Does RL Generalize Better Than SFT? A Data-Centric Perspective on VLM Post-Training
Self-Supervised Learning for Speaker Recognition: A study and review
SynergyKGC: Reconciling Topological Heterogeneity in Knowledge Graph Completion via Topology-Aware Synergy
Deep Learning of Compositional Targets with Hierarchical Spectral Methods
Diagnosing Structural Failures in LLM-Based Evidence Extraction for Meta-Analysis
Reinforcing Chain-of-Thought Reasoning with Self-Evolving Rubrics
Anomaly Detection with Machine Learning Algorithms in Large-Scale Power Grids
SoftMatcha 2: A Fast and Soft Pattern Matcher for Trillion-Scale Corpora
Optimal Initialization in Depth: Lyapunov Initialization and Limit Theorems for Deep Leaky ReLU Networks
Healthy Harvests: A Comparative Look at Guava Disease Classification Using InceptionV3
Variational Optimality of F\"ollmer Processes in Generative Diffusions
The emergence of numerical representations in communicating artificial agents
Fine-Tuning GPT-5 for GPU Kernel Generation
Characterizing Trainability of Instantaneous Quantum Polynomial Circuit Born Machines
A Gibbs posterior sampler for inverse problem based on prior diffusion model
SteuerLLM: Local specialized large language model for German tax law analysis
First International StepUP Competition for Biometric Footstep Recognition: Methods, Results and Remaining Challenges
Renet: Principled and Efficient Relaxation for the Elastic Net via Dynamic Objective Selection
Learning to Compose for Cross-domain Agentic Workflow Generation
LCIP: Loss-Controlled Inverse Projection of High-Dimensional Image Data
Data-Efficient Hierarchical Goal-Conditioned Reinforcement Learning via Normalizing Flows
SCRAPL: Scattering Transform with Random Paths for Machine Learning
YOR: Your Own Mobile Manipulator for Generalizable Robotics
Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data