Related papers: VERITAS: Verifying the Performance of AI-native Tr…

Artificial Intelligence (AI) technologies have profoundly transformed the field of remote sensing, revolutionizing data collection, processing, and analysis. Traditionally reliant on manual interpretation and task-specific models, remote…

Generative models have gained significant attention for their ability to produce realistic synthetic data that supplements the quantity of real-world datasets. While recent studies show performance improvements in wireless sensing tasks by…

Sequence labeling systems should perform reliably not only under ideal conditions but also with corrupted inputs - as these systems often process user-generated text or follow an error-prone upstream component. To this end, we formulate the…

Physical-layer security is regaining traction in the research community, due to the performance boost introduced by deep learning classification algorithms. This is particularly true for sender authentication in wireless communications via…

Noise in seismic data arises from numerous sources and is continually evolving. The use of supervised deep learning procedures for denoising of seismic datasets often results in poor performance: this is due to the lack of noise-free field…

Resource-constrained IoT devices increasingly rely on deep learning models, however, these models experience significant accuracy drops due to domain shifts when encountering variations in lighting, weather, and seasonal conditions. While…

Automatic evaluation of ST systems is typically performed by comparing translation hypotheses with one or more reference translations. While effective to some extent, this approach inherits the limitation of reference-based evaluation that…

The fundamental design of wireless systems toward AI-native 6G and beyond is driven by the need for ever-increasing demand of mobile data traffic, extreme spectral efficiency, and adaptability across diverse service scenarios. To overcome…

Smart-home IoT systems rely on heterogeneous sensor networks whose correctness shapes application behavior and the physical environment. However, these low-cost, resource-constrained sensors are highly prone to failure under real-world…

This paper addresses the challenge of speaker separation, which remains an active research topic despite the promising results achieved in recent years. These results, however, often degrade in real recording conditions due to the presence…

Transformer trackers have achieved impressive advancements recently, where the attention mechanism plays an important role. However, the independent correlation computation in the attention mechanism could result in noisy and ambiguous…

Massive multiple-input multiple-output (mMIMO) is a key capacity-boosting technology in 5G wireless systems. To reduce the number of radio frequency (RF) chains needed in such systems, a novel approach has recently been introduced involving…

We present a novel framework for specifying and verifying correctness globally for neural networks on perception tasks. Most previous works on neural network verification for perception tasks focus on robustness verification. Unlike…

The integration of Reconfigurable Intelligent Surfaces (RIS) holds substantial promise for revolutionizing 6G wireless networks, offering unprecedented capabilities for real-time control over communication environments. However, determining…

In Meta-Reinforcement Learning (meta-RL) an agent is trained on a set of tasks to prepare for and learn faster in new, unseen, but related tasks. The training tasks are usually hand-crafted to be representative of the expected distribution…

The source code of Function as a Service (FaaS) applications is constantly being refined. To detect if a source code change introduces a significant performance regression, the traditional benchmarking approach evaluates both the old and…

This longitudinal pilot study tracked how generative AI reshapes problem-solving over six months across three waves in an academic setting. AI integration reached saturation by Wave 3, with daily use rising from 52.4% to 95.7% and ChatGPT…

This chapter focuses on a hardware architecture for semi-passive Reconfigurable Intelligent Surfaces (RISs) and investigates its consideration for boosting the performance of Multiple-Input Multiple-Output (MIMO) communication systems. The…

Traditional simulator-based training for maritime professionals is critical for ensuring safety at sea but often depends on subjective trainer assessments of technical skills, behavioral focus, communication, and body language, posing…

Wearable biosensors have revolutionized human performance monitoring by enabling real-time assessment of physiological and biomechanical parameters. However, existing solutions lack the ability to simultaneously capture breath-force…