Telecomunicaciones, información y comunicación

CoBRA: A Universal Strategyproof Confirmation Protocol for Quorum-based Proof-of-Stake Blockchains

- The security of many Proof-of-Stake (PoS) payment systems relies on quorum-based State Machine Replication (SMR) protocols. While classical analyses assume purely Byzantine faults, real-world systems...

Matrix nearness problems and eigenvalue optimization

- This book is about solving matrix nearness problems that are related to eigenvalues or singular values or pseudospectra. These problems arise in great diversity in various fields, be they related to...

Toward Integrated Solutions: A Systematic Interdisciplinary Review of Cybergrooming Research

- Cybergrooming exploits minors through online trust-building, yet research remains fragmented, limiting holistic prevention. Social sciences focus on behavioral insights, while computational methods...

Scalable Graph Condensation with Evolving Capabilities

- The rapid growth of graph data creates significant scalability challenges as most graph algorithms scale quadratically with size. To mitigate these issues, Graph Condensation (GC) methods have been...

Computational Safety for Generative AI: A Hypothesis Testing Perspective

- AI safety is a rapidly growing area of research that seeks to prevent the harm and misuse of frontier AI technology, particularly with respect to generative AI (GenAI) tools that are capable of...

Region-Adaptive Sampling for Diffusion Transformers

- Diffusion models (DMs) have become the leading choice for generative tasks across diverse domains. However, their reliance on multiple sequential forward passes significantly limits real-time...

Dealing with Annotator Disagreement in Hate Speech Classification

- Hate speech detection is a crucial task, especially on social media where harmful content can spread quickly. Collecting social media content (tweets etc.) to train machine learning models is easy,...

DAL: A Practical Prior-Free Black-Box Framework for Piecewise Stationary Bandits

- We introduce a practical, black-box framework termed Detection Augmented Learning (DAL) for the problem of piecewise stationary bandits without knowledge of the underlying non-stationarity. DAL...

Enhancing LLM Safety Through a Theoretical Minimax Game Lens

- The rapid advancement of large language models (LLMs) necessitates effective mechanisms to ensure their responsible deployment by accurately distinguishing unsafe content from benign content. While...

Enhancing Physics-Informed Neural Networks Through Feature Engineering

- Physics-Informed Neural Networks (PINNs) seek to solve partial differential equations (PDEs) with deep learning. Mainstream approaches that deploy fully-connected multi-layer deep learning...

Understanding, Detecting, and Repairing Real-World In-Context-Learning-Based Text-to-SQL Errors

- Large language models (LLMs) have been adopted for text-to-SQL tasks, utilizing their in-context learning (ICL) capability to translate natural language questions into SQL queries. However, such a...

Cross-lingual Embedding Clustering for Hierarchical Softmax in Low-Resource Multilingual Speech Recognition

- We present a novel approach centered on the decoding stage of Automatic Speech Recognition (ASR) that enhances multilingual performance, especially for low-resource languages. It utilizes a...

Intelligent Sailing Model for Open Sea Navigation

- Autonomous vessels potentially enhance safety and reliability of seaborne trade. To facilitate the development of autonomous vessels, simulations are required to model realistic interactions with...

GePBench: Evaluating Fundamental Geometric Perception for Multimodal Large Language Models

- Geometric shapes play important roles in both physical world and human cognition. While multimodal large language models (MLLMs) have made significant advancements in visual understanding, their...

Training-Free Adversarial Robustness in Computational MRI

- Deep learning (DL) methods have become the state-of-the-art for reconstructing sub-sampled magnetic resonance imaging (MRI) data. However, studies have shown that these methods are susceptible to...

Virtual Sensing to Enable Real-Time Monitoring of Inaccessible Locations & Unmeasurable Parameters

- Real-time monitoring of safety-critical interior states remains an open problem in energy systems where physical instrumentation is infeasible. Existing approaches rely on explicit governing...

AC-LIO: Towards Asymptotic Compensation for Distortion in LiDAR-Inertial Odometry via Selective Intra-Frame Smoothing

- Existing LiDAR-Inertial Odometry (LIO) methods typically utilize the prior trajectory derived from the IMU integration to compensate for the motion distortion within LiDAR frames. However,...

Explainable deep learning improves human mental models of self-driving cars

- Self-driving cars increasingly rely on deep neural networks to achieve human-like driving. The opacity of such black-box planners makes it challenging to accurately anticipate when they will fail,...

Multi-Sensor Fusion for UAV Classification Based on Feature Maps of Image and Radar Data

- The unique cost, flexibility, speed, and efficiency of modern UAVs make them an attractive choice in many applications in contemporary society. This, however, causes an ever-increasing number of...

Photon: Federated LLM Pre-Training

- Scaling large language models (LLMs) demands extensive data and computing resources, which are traditionally constrained to data centers by the high-bandwidth requirements of distributed training....

Distributed Load Balancing with Workload-Dependent Service Rates

- Modern service systems, including cloud platforms and large language model inference endpoints, must distribute jobs across servers whose processing speeds depend on current workloads. At scale,...