Telecomunicaciones, información y comunicación

Design and Analysis of a Concatenated Code for Intersymbol Interference Wiretap Channels

- We propose a two-stage concatenated coding scheme for reliable and secure communication over intersymbol interference wiretap channels. We first establish the secrecy capacity. Then, motivated by the...

What Really Matters for Table LLMs? A Meta-Evaluation of Model and Data Effects

- Table modeling has progressed for decades. In this work, we revisit this trajectory and highlight emerging challenges in the LLM era, particularly the paradox of choice: the difficulty of attributing...

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective

- Graph Neural Networks (GNNs) have achieved notable success in tasks such as social and transportation networks. However, recent studies have highlighted the vulnerability of GNNs to backdoor attacks,...

Deep Tree Tensor Networks

- Originating in quantum physics, tensor networks (TNs) have been widely adopted as exponential machines and parametric decomposers for recognition tasks. Typical TN models, such as Matrix Product...

Conditional Vendi Score: Prompt-Aware Diversity Evaluation for Generative AI Models and LLMs

- Generative models guided by text prompts are widely evaluated for fidelity and prompt alignment, yet their ability to produce outputs remains underexplored. Existing diversity metrics such as Vendi...

Visual-TCAV: Concept-based Attribution and Saliency Maps for Post-hoc Explainability in Image Classification

- Convolutional Neural Networks (CNNs) have shown remarkable performance in image classification. However, interpreting their predictions is challenging due to the size and complexity of these models....

Support for AI Development -- Automated Daily Measurement with Open Data and Code

- This manuscript presents and advocates for a new form of scientific communication: free and open nowcasting of public opinion via web dashboard. I present an open-source automated system that gathers...

Whisper-GPT -- Continuous Discrete Hybrid Representation Language Models For Speech And Music

- We propose WHISPER-GPT: A generative large language model (LLM) for speech and music that allows us to work with continuous audio representations and discrete tokens simultaneously as part of a...

Dynamics of Adversarial Attacks on Large Language Model-Based Search Engines

- The increasing integration of Large Language Model (LLM) based search engines has transformed the landscape of information retrieval. However, these systems are vulnerable to adversarial attacks,...

Mixtures of Neural Operators Reduce Active Complexity in Operator Learning

- Operator-learning systems are not governed solely by total parameter count; for one query, the relevant bottleneck can be the model that must be loaded and evaluated. We study this distinction for...

A Survey on Semantic Modeling for Building Energy Management

- Building Energy Management (BEM) is central to reducing energy use and CO2 emissions in the building sector. Although IoT technologies now provide extensive operational data, heterogeneous data...

MUVERA: Multi-Vector Retrieval via Fixed Dimensional Encodings

- Neural embedding models have become a fundamental component of modern information retrieval (IR) pipelines. These models produce a single embedding $x \in \mathbb{R}^d$ per data-point, allowing for...

Standard Language Ideology in AI-Generated Language

- Large language models (LLMs) generate text that reinforces standard language ideology: a bias towards certain language varieties that are granted more prestige, authority, and legitimacy than others....

EXCEEDS: Extracting Complex Events via Nugget-based Grid Modeling in Scientific Domain

- It is crucial to understand a specific domain by events. Extensive event extraction research has been conducted in many domains such as news, finance, and biology. However, event extraction in...

Rod models in continuum and soft robot control: a review

- Continuum and soft robots can transform automation tasks requiring compliant interaction in constrained or unstructured environments, including healthcare, agriculture, marine, and space...

BadRobot: Jailbreaking Embodied LLM Agents in the Physical World

- Embodied AI represents systems where AI is integrated into physical entities. Large Language Model (LLM), which exhibits powerful language understanding abilities, has been extensively employed in...

Breaking the Curse of Dimensionality: Diffusion Models Efficiently Learn Low-Dimensional Distributions

- Despite their empirical success across a wide range of generative tasks, the fundamental principles underlying the ability of diffusion models to learn data distributions are poorly understood. In...

Active-Passive Federated Learning for Vertically Partitioned Multi-view Data

- Vertical federated learning is a natural and elegant approach to integrate multi-view data vertically partitioned across devices (clients) while preserving their privacies. Apart from the model...

QCRMut: Quantum Circuit Random Mutant generator tool

- As quantum computing moves towards practical deployment, ensuring the reliability of quantum software becomes increasingly important. Mutation testing is a promising technique in this context;...

A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications

- With the rapid advancement of large language models (LLMs), aligning policy models with human preferences has become increasingly critical. Direct Preference Optimization (DPO) has emerged as a...

Deeper or Wider: A Perspective from Optimal Generalization Error with Sobolev Loss

- Constructing the architecture of a neural network is a challenging pursuit for the machine learning community, and the dilemma of whether to go deeper or wider remains a persistent question. This...