Related papers: Quality Evaluation of Conceptual Level Object Mult…
Fully digital massive MIMO systems with large numbers (1000+) of antennas offer dramatically increased capacity gains from spatial multiplexing and beamforming. Designing digital receivers that can scale to these array dimensions presents…
Traditional data valuation methods based on ``row-count $\times$ quality coefficient'' paradigms fail to capture the nuanced, nonlinear contributions that data makes to Large Language Model (LLM) capabilities. This paper presents a dynamic…
Dependability assurance of systems embedding machine learning(ML) components---so called learning-enabled systems (LESs)---is a key step for their use in safety-critical applications. In emerging standardization and guidance efforts, there…
Machine learning (ML) methods are widely used in industrial applications, which usually require a large amount of training data. However, data collection needs extensive time costs and investments in the manufacturing system, and data…
Millions of users rely on a market of cloud-based services to obtain access to state-of-the-art large language models. However, it has been very recently shown that the de facto pay-per-token pricing mechanism used by providers creates a…
The widespread adoption of web applications has made their security a critical concern and has increased the need for systematic ways to assess whether they can be considered trustworthy. However, "trust" assessment remains an open problem…
Non-orthogonal multiple access (NOMA) has been widely recognized as a promising way to scale up the number of users, enhance the spectral efficiency, and improve the user fairness in wireless networks, by allowing more than one user to…
While benefiting people's daily life in so many ways, smartphones and their location-based services are generating massive mobile device location data that has great potential to help us understand travel demand patterns and make…
Modern large language models (LLMs) represent a paradigm shift in what can plausibly be expected of machine learning models. The fact that LLMs can effectively generate sensible answers to a diverse range of queries suggests that they would…
This paper investigates radar-assisted user acquisition for downlink multi-user multiple-input multiple-output (MIMO) transmission using Orthogonal Frequency Division Multiplexing (OFDM) signals. Specifically, we formulate a concise…
Multimodal Large Language Models (MLLMs) have made notable advances in visual understanding, yet their abilities to recognize objects modified by specific attributes remain an open question. To address this, we explore MLLMs' reasoning…
Human-robot interactive decision-making is increasingly becoming ubiquitous, and trust is an influential factor in determining the reliance on autonomy. However, it is not reasonable to trust systems that are beyond our comprehension, and…
Driven by the ever-increasing requirements of ultra-high spectral efficiency, ultra-low latency, and massive connectivity, the forefront of wireless research calls for the design of advanced next generation multiple access schemes to…
The data that underlies automated methods in computer vision and machine learning, such as image retrieval and fine-grained recognition, often comes from crowdsourcing. In contexts that rely on the intrinsic motivation of users, we seek to…
Today, machine learning (ML) is widely used in industry to provide the core functionality of production systems. However, it is practically always used in production systems as part of a larger end-to-end software system that is made up of…
Computer-generated imagery of car models has become an indispensable part of car manufacturers' advertisement concepts. They are for instance used in car configurators to offer customers the possibility to configure their car online…
Trust is a multilayered concept with critical relevance when it comes to introducing new technologies. Understanding how humans will interact with complex vehicle systems and preparing for the functional, societal and psychological aspects…
The evolution of cellular networks is driven by the dream of ubiquitous wireless connectivity: Any data service is instantly accessible everywhere. With each generation of cellular networks, we have moved closer to this wireless dream;…
Increasingly, connected cars are becoming a decentralized data platform. With greater autonomy, they have growing needs for computation and perceiving the world around them through sensors. While todays generation of vehicles carry all the…
Today, we have required to accommodate a large number of users under a single base station. This can be possible only if we have some flexibility over the spectrum. Previously we have lots of multiplexing methods to accommodate large number…