Telecomunicaciones, información y comunicación

RedParrot: Accelerating NL-to-DSL for Business Analytics via Query Semantic Caching

- Recently, at Xiaohongshu, the rapid expansion of e-commerce and advertising demands real-time business analytics with high accuracy and low latency. To meet this demand, systems typically rely on...

HalalBench: A Multilingual OCR Benchmark for Food Packaging Ingredient Extraction

- No standardized benchmark exists for evaluating OCR on food packaging, despite its critical role in automated halal food verification. Existing benchmarks target documents or scene text, missing the...

RADIANT-LLM: an Agentic Retrieval Augmented Generation Framework for Reliable Decision Support in Safety-Critical Nuclear Engineering

- Reliable decision support in nuclear engineering requires traceable, domain-grounded knowledge retrieval, yet safety and risk analysis workflows remain hampered by fragmented documentation and...

Your Reviews Replicate You: LLM-Based Agents as Customer Digital Twins for Conjoint Analysis

- Conjoint analysis is a cornerstone of market research for estimating consumer preferences; however, traditional methods face persistent challenges regarding time, cost, and respondent fatigue. To...

StratRAG: A Multi-Hop Retrieval Evaluation Dataset for Retrieval-Augmented Generation Systems

- We introduce StratRAG, an open-source retrieval evaluation dataset for benchmarking Retrieval-Augmented Generation (RAG) systems on multi-hop reasoning tasks under realistic, noisy document-pool...

Beyond ReLU: How Activations Affect Neural Kernels and Random Wide Networks

- In recent years, the neural tangent kernel (NTK) and neural network Gaussian process kernel (NNGP) have given theoreticians tractable limiting cases of fully connected neural networks. However, the...

Learning Operators by Regularized Stochastic Gradient Descent with Operator-valued Kernels

- We consider a class of statistical inverse problems involving the estimation of a regression operator from a Polish space to a separable Hilbert space, where the target lies in a vector-valued...

Model Selection for Unit-root Time Series with Many Predictors

- This paper studies model selection for general unit-root time series, including the case with many exogenous predictors. We propose a new model selection algorithm, FHTD, that leverages forward...

Separation-based causal discovery for extremes

- Structural causal models (SCMs), with an underlying directed acyclic graph (DAG), provide a powerful analytical framework to describe the interaction mechanisms in large-scale complex systems....

High-Dimensional Private Linear Regression with Optimal Rates

- Differentially private (DP) linear regression has received significant attention in the recent theoretical literature, with several approaches proposed to improve error rates. Our work considers the...

Doubly unfolded adjacency spectral embedding of dynamic multiplex graphs

- Many real-world networks evolve dynamically over time and present different types of connections between nodes, often called layers. In this work, we propose a latent position model for these...

A cautious use of auxiliary outcomes for decision-making in randomized clinical trials

- Clinical trials often collect data on multiple outcomes, such as overall survival (OS), progression-free survival (PFS), and response to treatment (RT). In most cases, however, study designs only use...

DecompKAN: Decomposed Patch-KAN for Long-Term Time Series Forecasting

- Accurate time series forecasting in scientific domains such as climate modeling, physiological monitoring, and energy systems benefits from both competitive predictions and model transparency. This...

Shared-kernel Wavelet Neural Networks for Poisson Image Reconstruction

- The Laplacian operator transforms the image into its Laplacian field, which usually is sparse and satisfies a stable distribution. On the other hand, an image can be uniquely reconstructed from its...

Closing the Loop: A Software Framework for AI to Support Business Decision Making

- Create an idea, prototype it, evaluate if users like it, then learn. It is the circle of business. If AI can operate in all parts of the circle, it will enable rapid iteration and learning speeds for...

Quantum Prediction of Transport Dynamics in Discretized State Spaces

- We propose a gate-based quantum algorithm for the prediction step of Bayesian state estimation based on the Fokker-Planck equation on a discretized position-velocity state space. The probability...

Continuum-marginal optimal transport: a mesh-free kernel method

- In this paper we study continuum-marginal optimal transport. Given a time-continuous family of probability marginals, the problem is to recover the minimum-energy velocity field whose flow reproduces...

Stochastic simultaneous optimistic optimization

- We study the problem of global maximization of a function f given a finite number of evaluations perturbed by noise. We consider a very weak assumption on the function, namely that it is locally...

Efficient learning by implicit exploration in bandit problems with side observations

- We consider online learning problems under a partial observability model capturing situations where the information conveyed to the learner is between full information and bandit feedback. In the...

Enhancing molecular dynamics with equivariant machine-learned densities

- Machine-learning interatomic potentials (MLIPs) have enabled molecular dynamics at near ab initio accuracy, yet remain limited to energies and forces by construction, leaving electronic observables...

Learning to Think from Multiple Thinkers

- We study learning with Chain-of-Thought (CoT) supervision from multiple thinkers, all of whom provide correct but possibly systematically different solutions, e.g., step-by-step solutions to math...