Telecomunicaciones, información y comunicación

An iterative Ising decoder for quantum error correction codes

- The Ising framework maps the decoding problem in quantum error correction onto ground-state optimization of a classical Hamiltonian, in which $X$-$Z$ error correlations enter as cross terms. Under...

Market Design for AI: Beyond the Copyright Binary

- How can we design a market of human-generated content for use in training AI models that both enables technological progress and preserves individual incentives for high-quality content creation?...

On Subquadratic Architectures: From Applications to Principles

- Transformers dominate modern sequence modeling, but their quadratic attention incurs substantial computational cost. Subquadratic architectures offer a scalable alternative. However, it remains...

Ambient Diffusion Policy: Imitation Learning from Suboptimal Data in Robotics

- We propose Ambient Diffusion Policy, a simple and principled method for imitation learning from suboptimal data in robotics. High-quality, task-specific robot data is expensive and time-consuming to...

APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies

- Vision-Language-Action (VLA) models that couple pretrained Vision-Language Models (VLMs) with continuous action experts have achieved strong manipulation performance, yet generalization to...

DepthMaster: Unified Monocular Depth Estimation for Perspective and Panoramic Images

- While monocular depth estimation has achieved significant progress, achieving generalized metric depth estimation for both narrow field-of-view (FoV) perspectives and $360^\circ$ panoramas remains an...

Should LLM Agents Decide in Social Simulations? Comparing Finite-State and LLM-Based Decision Policies

- Large language models (LLMs) are increasingly used as decision-making components in social simulations. This introduces a methodological risk: the simulation may deviate from the explicit behavioral...

A Turbo-Inference Strategy for Object Detection and Instance Segmentation

- Object detection and instance segmentation tasks are closely related. Existing top-down instance segmentation methods usually follow a detect-then-segment paradigm, where an initial detector is used...

UniIntervene: Agentic Intervention for Efficient Real-World Reinforcement Learning

- Human-in-the-loop reinforcement learning (HiL-RL) has emerged as an effective paradigm for real-world robotic manipulation, enabling online policy improvement with human guidance. However, current...

Illumination-Robust Camera-Based Heart-Rate Estimation for Physiological Sensing in Robots

- Physiological awareness is important for service, social, and assistive robots that interact with humans in everyday environments. Remote photoplethysmography (rPPG) enables non-contact heart-rate...

SPEA2$^+$: Improved Density Estimation in SPEA2 with Provable Runtime Guarantees

- The Strength Pareto Evolutionary Algorithm 2 (SPEA2) is a popular and prominent evolutionary algorithm for solving multi-objective optimisation problems. Despite its popularity, theoretical analyses...

APPO: Agentic Procedural Policy Optimization

- Recent advances in agentic Reinforcement Learning (RL) have substantially improved the multi-turn tool-use capabilities of large language model agents. However, most existing methods assign credit...

ATLAS: Active Theory Learning for Automated Science

- Advancing scientific understanding through mechanistic modeling requires posing the right experimental questions to yield maximally informative data. To automate this pursuit within cognitive...

TAHOE: Text-to-SQL with Automated Hint Optimization from Experience

- Large Language Models (LLMs) have democratized database access through Text-to-SQL, but moving from prototypes to production remains difficult. Real deployments must handle strict SQL dialects,...

MARCIM-WG: A cyber wargame proposal based on math modeling applied in a naval scenario

- As maritime operations increasingly depend on interconnected digital ecosystems, cyber incidents can propagate across maritime networks and degrade critical services. Strengthening strategic Cyber...

Redesign Mixture-of-Experts Routers with Manifold Power Iteration

- Router is the cornerstone component to the Mixture-of-Experts models. Serving as expert proxies, the rows of the router matrix compute their similarity to the MoE inputs to determine which subset of...

Doc-to-Atom: Learning to Compile and Compose Memory Atoms

- Long input sequences are central to document understanding and multi-step reasoning in Large Language Models, yet the quadratic cost of attention makes inference both memory-intensive and slow....

DIRECT: When and Where Should You Allocate Test-Time Compute in Embodied Planners?

- Vision-Language Models (VLMs) are increasingly deployed as high-level planners for embodied agents, with an emerging strategy of scaling test-time compute to improve capability. However, we observe...

FACTR 2: Learning External Force Sensing for Commodity Robot Arms Improves Policy Learning

- Contact-rich manipulation requires force sensitivity, but many robot arms lack dedicated force sensors due to their high cost. We present Neural External Torque Estimation (NEXT), a data-driven...

How Seemingly Inconsequential Design Choices Dictate Performance of LLMs in Pathology

- General-purpose large language models (LLMs) are routinely used as baselines when evaluating specialized pathology models on whole-slide images (WSIs). Because WSIs exceed contemporary model context...

Context-Driven Incremental Compression for Multi-Turn Dialogue Generation

- Modern conversational agents condition on an ever-growing dialogue history at each turn, incurring redundant attention and encoding costs that grow with conversation length. Naive truncation or...