Defensa y seguridad

FunHOI: Annotation-Free 3D Hand-Object Interaction Generation via Functional Text Guidance

- Hand-object interaction(HOI) is the fundamental link between human and environment, yet its dexterous and complex pose significantly challenges for gesture control. Despite significant advances in AI...

GERD: Geometric event response data generation

- Event-based vision sensors offer high temporal resolution, high dynamic range, and low power consumption, yet event-based vision models lag behind conventional frame-based vision methods. We argue...

GSurf: Learning Signed Distance Fields from Splatting Opaque Gaussians for High-quality 3D Reconstruction

- High-fidelity surface reconstruction from multi-view images is a core problem in 3D computer vision. While neural implicit surfaces like SDFs offer smooth geometry, they are often bottlenecked by the...

Koopman-informed recurrent neural networks

- Recurrent neural networks are a successful neural architecture for many time-dependent problems, including time series analysis, forecasting, and modeling of dynamical systems. In the context of...

Adaptive and Robust Watermark for Generative Tabular Data

- In recent years, watermarking generative tabular data has become a prominent framework to protect against the misuse of synthetic data. However, while most prior work in watermarking methods for...

The Contribution of XAI for the Safe Development and Certification of AI: An Expert-Based Analysis

- Developing and certifying safe - or so-called trustworthy - AI has become an increasingly salient issue, especially in light of upcoming regulation such as the EU AI Act. In this context, the...

Data Alchemy: Mitigating Cross-Site Model Variability Through Test Time Data Calibration

- Deploying deep learning-based imaging tools across various clinical sites poses significant challenges due to inherent domain shifts and regulatory hurdles associated with site-specific fine-tuning....

Semantic Representation Learning of Scientific Literature based on Adaptive Feature and Graph Neural Network

- Because most scientific literature data are unlabeled, semantic representation learning based on unsupervised graphs has become crucial. To enrich scientific-literature features, this paper proposes...

Precise localization within the GI tract by combining classification of CNNs and time-series analysis of HMMs

- This paper presents a method to efficiently classify the gastroenterologic section of images derived from Video Capsule Endoscopy (VCE) studies by exploring the combination of a Convolutional Neural...

Knowledge Graph and Accurate Portrait Construction of Scientific and Technological Academic Conferences

- In recent years, with the continuous progress of science and technology, the number of scientific research achievements has increased rapidly. As an exchange platform and medium for scientific...

Why Do You Say It Like That? A Phoneme-Level Framework for Explainable Speech Deepfake Detection

- As the accuracy of speech deepfake detection improves with the use of self-supervised representations such as wav2vec 2.0 and HuBERT, understanding why the speech is classified as bona fide or...

Revisiting One-Zero and Two-Zero Neutrino Mass Textures in Light of Recent Oscillation and Cosmological Data

- We revisit one-zero and two-zero textures of the neutrino mass matrix under current experimental and cosmological constraints. We identify the phenomenologically viable texture structures using the...

Tubular Neighbourhoods of Pfaffian Sets and Applications to Neural Networks

- We derive bounds for the volume of tubular neighbourhoods of smooth Pfaffian hypersurfaces, generalising known results for algebraic varieties. The bounds are given in terms of the Pfaffian format of...

DKDNet: Dual Knowledge and Data-Driven Network for Cross-Domain Automatic Modulation Classification

- The dynamics of communication environments induce significant distribution shifts across domains, challenging the generalization of deep learning-based automatic modulation classification (AMC)...

Reaction-network reasoning with frontier models for experimentally confirmed catalyst-selectivity hypotheses

- Catalysts are essential for sustainable chemical manufacturing, yet discovering novel architectures remains a bottleneck dominated by trial-and-error experimentation and computationally intensive...

Expressivity and Statistical Trade-offs in Diffusion Policy Learning

- Diffusion-based policies have recently emerged as powerful policy parameterizations for reinforcement learning, representing state-conditioned action distributions as terminal laws of diffusion...

Distributionally Faithful Imputation via Positive Semi-Definite Kernel Density Estimation

- Missing values undermine statistical inference and machine learning pipelines, yet most imputation methods rely on heuristics or restrictive parametric assumptions that ignore the joint data...

SLORR: Simple and Efficient In-Training Low-Rank Regularization

- Low-rank factorization is widely used to compress neural networks, but modern models are often not naturally amenable to aggressive factorization without significant accuracy loss. Existing...

Using AI-based Learning Assistants in Higher Education: A Large-Scale Descriptive Analysis

- In this study, we present a large-scale descriptive analysis of the use of an AI-based learning assistant (Syntea) in higher education. Based on objective log data from 77,543 students enrolled in...

ARDY: Autoregressive Diffusion with Hybrid Representation for Interactive Human Motion Generation

- Generating realistic 3D human motions in real-time within interactive applications is key for animation, simulation, and humanoid robotics. While recent offline motion generation approaches offer...

Deep Learning for Joint Narrowband Interference Cancellation and Soft Demodulation in OFDM Systems

- Narrowband interference (NBI) severely degrades orthogonal frequency-division multiplexing (OFDM) systems by corrupting subcarriers and rendering classical soft demodulation ineffective. Conventional...