Telecomunicaciones, información y comunicación

ReCLIP++: Learn to Rectify the Bias of CLIP for Unsupervised Semantic Segmentation

- Recent works utilize CLIP to perform the challenging unsupervised semantic segmentation task where only images without annotations are available. However, we observe that when adopting CLIP to such a...

Simple grammar bisimilarity, with an application to session type equivalence

- We provide an algorithm for deciding simple grammar bisimilarity whose complexity is polynomial in the valuation of the grammar (maximum seminorm among production rules). Since the valuation is at...

Assessing, Exploiting, and Mitigating Syntactic Robustness Failures in LLM-Based Code Generation

- Rapid advances in the field of Large Language Models (LLMs) have made LLM-based code generation an important area for investigation. An LLM-based code generator takes a prompt as input and produces...

The Rise and Fall of the Initial Era

- Bibliographic data is a rich source of information that goes beyond the use cases of location and citation -- it also encodes both cultural and technological context. For most of its existence, the...

Active teacher selection for reward learning

- Reward learning techniques enable machine learning systems to learn objectives from human feedback. A core limitation of these systems is their assumption that all feedback comes from a single human...

Code Generation and Conic Constraints for Model-Predictive Control on Microcontrollers with Conic-TinyMPC

- Model-predictive control (MPC) is a state-of-the-art control method for constrained robotic systems, yet deployment on resource-limited hardware remains difficult. This challenge is magnified by...

Multi-Stage Prototype Learning for Interpretable Time Series Classification

- Deep learning methods are powerful tools in classifying multivariate time series data. Despite their high performance, these methods are hard to interpret, which diminishes their applications in...

Vibe Econometrics and the Analysis Contract

- "Vibe coding" and "vibe analytics" have been framed as a democratization of technical capability. This paper argues that AI-assisted methodology more broadly, or what I call "vibe...

PropSplat: Map-Free RF Field Reconstruction via 3D Gaussian Propagation Splatting

- Building a site-specific propagation model typically requires either ray-tracing over detailed 3D maps or dense measurement campaigns. Both approaches are expensive and often infeasible for rapid...

Covert Signaling for Communication and Sensing over the Bosonic Channels

- Preventing signal detection in communication and active sensing requires careful control of transmission power. In fact, the square-root laws (SRL) for covert classical and quantum communication and...

Linear Response Estimators for Singular Statistical Models

- We define susceptibilities as a measure of the response of an observable quantity of a parameterized statistical model to a perturbation of the data for a general class of observables. We define...

Uncertainty Quantification for Cardiac Shape Reconstruction with Deep Signed Distance Functions via MCMC methods

- Atlas-based approaches allow high-quality, patient-specific shape reconstructions of cardiac anatomy from sparse and/or noisy data such as point clouds. However, these methods are mainly...

Characterizing and Correcting Effective Target Shift in Online Learning

- Online learning from a stream of data is a defining feature of intelligence, yet modern machine learning systems often struggle in this setting, especially under distributional shift. To understand...

Accelerating Langevin Monte Carlo via Efficient Stochastic Runge--Kutta Methods beyond Log-Concavity

- Sampling from a high-dimensional probability distribution is a fundamental algorithmic task arising in wide-ranging applications across multiple disciplines, including scientific computing,...

Robust Capacity Expansion under Wildfire Ignition Risk and High Renewable Penetration

- In power systems, the risk of wildfire ignition has increased significantly in recent years. The impact and severity of these events on energy dispatch, as well as their societal ramifications, make...

Spectral Dynamics in Deep Networks: Feature Learning, Outlier Escape, and Learning Rate Transfer

- We study the evolution of hidden-weight spectra in wide neural networks trained by (stochastic) gradient descent. We develop a two-level dynamical mean-field theory (DMFT) that jointly tracks bulk...

PPI-Net connects molecular protein interactions to functional processes in disease

- Understanding how molecular alterations propagate across biological systems to drive disease remains a central challenge. Although high-throughput profiling enables comprehensive characterization of...

Pre-training Enables Extraordinary All-optical Image Denoising

- Optical neural networks are emerging as powerful machine learning and information processing tools because of their potential advantages in speed and energy efficiency. The training methods of these...

Flow Matching for Count Data

- High-dimensional count data arise in applications such as single-cell RNA sequencing and neural spike trains, where mapping between distributions across successive batches or time points form...

Reliable Chain-of-Thought via Prefix Consistency

- Large Language Models often improve accuracy on reasoning tasks by sampling multiple Chain-of-Thought (CoT) traces and aggregating them with majority voting (MV), a test-time technique called...

Physics-Informed Reduced-Order Operator Learning for Hyperelasticity in Continuum Micromechanics

- Physics-informed operator learning is an attractive candidate for surrogate modeling of microstructures, especially in multiscale finite-element simulations. Its practical use, however, is often...