相关论文: Machine Learning for Wireless Link Quality Estimat…

Key performance indicators(KPIs) are of great significance in the monitoring of wireless network service quality. The network service quality can be improved by adjusting relevant configuration parameters(CPs) of the base station. However,…

In the automotive industry, the full cycle of managing in-use vehicle quality issues can take weeks to investigate. The process involves isolating root causes, defining and implementing appropriate treatments, and refining treatments if…

This paper discusses recent advancements made in the fast prediction of signal power in mmWave communications environments. Using machine learning (ML) it is possible to train models that provide power estimates with both good accuracy and…

Deploying large language models (LLMs) in edge-cloud environments requires an efficient routing strategy to balance cost and response quality. Traditional approaches prioritize either human-preference data or accuracy metrics from benchmark…

We present MLQE-PE, a new dataset for Machine Translation (MT) Quality Estimation (QE) and Automatic Post-Editing (APE). The dataset contains eleven language pairs, with human labels for up to 10,000 translations per language pair in the…

Wireless embedded edge devices are ubiquitous in our daily lives, enabling them to gather immense data via onboard sensors and mobile applications. This offers an amazing opportunity to train machine learning (ML) models in the realm of…

Large language models (LLMs) are gaining increasing popularity in software engineering (SE) due to their unprecedented performance across various applications. These models are increasingly being utilized for a range of SE tasks, including…

We have witnessed an exponential growth in commercial data services, which has lead to the 'big data era'. Machine learning, as one of the most promising artificial intelligence tools of analyzing the deluge of data, has been invoked in…

Machine learning (ML) is a promising enabler for the fifth generation (5G) communication systems and beyond. By imbuing intelligence into the network edge, edge nodes can proactively carry out decision-making, and thereby react to local…

Understanding how data quality aligns with regulatory requirements in machine learning (ML) systems presents a critical challenge for practitioners navigating the evolving EU regulatory landscape. To address this, we first propose a…

Word-level quality estimation (QE) methods aim to detect erroneous spans in machine translations, which can direct and facilitate human post-editing. While the accuracy of word-level QE systems has been assessed extensively, their usability…

Despite prolific work on evaluating generative models, little research has been done on the quality evaluation of an individual generated sample. To address this problem, a lightweight generated sample quality evaluation (LGSQE) method is…

WLAN devices have become a fundamental component of nowadays network deployments. However, even though traditional networking applications run mostly unchanged over wireless links, the actual interaction between these applications and the…

Optimizing various wireless user tasks poses a significant challenge for networking systems because of the expanding range of user requirements. Despite advancements in Deep Reinforcement Learning (DRL), the need for customized optimization…

Localization Quality Estimation (LQE) helps to improve detection performance as it benefits post processing through jointly considering classification score and localization accuracy. In this perspective, for further leveraging the close…

Today vehicles are becoming a rich source of data as they are equipped with localization or tracking and with wireless communications technologies. With the increasing interest in automated- or self- driving technologies, vehicles are also…

The rapid evolution of wireless technologies and the growing complexity of network infrastructures necessitate a paradigm shift in how communication networks are designed, configured, and managed. Recent advancements in Large Language…

Accurate and fast packet delivery rate (PDR) estimation, used in evaluating wireless link quality, is a prerequisite to increase the performance of mobile, multi-hop and multi-rate wireless ad hoc networks. Unfortunately, contemporary PDR…

Machine learning (ML) started to become widely deployed in cyber security settings for shortening the detection cycle of cyber attacks. To date, most ML-based systems are either proprietary or make specific choices of feature…

Machine learning (ML) models have been applied to a wide range of natural language processing (NLP) tasks in recent years. In addition to making accurate decisions, the necessity of understanding how models make their decisions has become…