Related papers: A Scalable Cloud-Edge Collaborative CKM Constructi…
Concept Bottleneck Models (CBMs), which break down the reasoning process into the input-to-concept mapping and the concept-to-label prediction, have garnered significant attention due to their remarkable interpretability achieved by the…
The transition to 6G calls for tightly integrated sensing and communication to support mission-critical services such as autonomous driving, embodied AI, and high-precision telemedicine. However, most existing ISAC designs rely on a single…
Mass data traffics, low-latency wireless services and advanced artificial intelligence (AI) technologies have driven the emergence of a new paradigm for wireless networks, namely edge-intelligent networks, which are more efficient and…
The 6G mobile networks will feature the widespread deployment of AI algorithms at the network edge, which provides a platform for supporting robotic edge intelligence systems. In such a system, a large-scale knowledge graph (KG) is operated…
2D top-down maps are commonly used for the navigation and exploration of mobile robots through unknown areas. Typically, the robot builds the navigation maps incrementally from local observations using onboard sensors. Recent works have…
Distributed reinforcement learning policies face network delays, jitter, and packet loss when deployed across edge devices and cloud servers. Standard RL training assumes zero-latency interaction, causing severe performance degradation…
Stacked intelligent metasurfaces (SIMs) represent a breakthrough in wireless hardware by comprising multilayer, programmable metasurfaces capable of analog computing in the electromagnetic (EM) wave domain. By examining their architectural…
Millimeter-wave (mmWave) channels, which occupy frequency ranges much higher than those being used in previous wireless communications systems, are utilized to meet the increased throughput requirements that come with 5G communications. The…
Knowledge graph (KG) foundation models aim to generalize across graphs with unseen entities and relations by learning transferable relational structure. However, most existing methods primarily emphasize relation-level universality, while…
The deep integration of communication with intelligence and sensing, as a defining vision of 6G, renders environment-aware channel prediction a key enabling technology. As a representative 6G application, vehicular communications require…
Foundation models constitute a significant advancement in computer vision: after a single, albeit costly, training phase, they can address a wide array of tasks. In the field of Earth observation, over 75 remote sensing vision foundation…
Concept bottleneck models (CBM) are a popular way of creating more interpretable neural networks by having hidden layer neurons correspond to human-understandable concepts. However, existing CBMs and their variants have two crucial…
Content-based collaborative filtering (CCF) predicts user-item interactions based on both users' interaction history and items' content information. Recently, pre-trained language models (PLM) have been used to extract high-quality item…
Recently, large language models (LLMs) have gained significant attention for their ability to generate fast and accurate answer to the given query. These models have evolved into large multimodal models (LMMs), which can interpret and…
Self-Supervised Learning (SSL) has emerged as a key technique in machine learning, tackling challenges such as limited labeled data, high annotation costs, and variable wireless channel conditions. It is essential for developing Channel…
With the rapid development of artificial general intelligence (AGI), various multimedia services based on pretrained foundation models (PFMs) need to be effectively deployed. With edge servers that have cloud-level computing power, edge…
Phasor Measurement Units (PMUs) generate high-frequency, time-synchronized data essential for real-time power grid monitoring, yet the growing scale of PMU deployments creates significant challenges in latency, scalability, and reliability.…
Entity alignment which aims at linking entities with the same meaning from different knowledge graphs (KGs) is a vital step for knowledge fusion. Existing research focused on learning embeddings of entities by utilizing structural…
The development of Cloud-Edge-IoT applications requires robust programming models. Existing models often struggle to manage the dynamic and stateful nature of these applications effectively. This paper introduces the Collaborative State…
Generative artificial intelligence (GAI) is a promising technique towards 6G networks, and generative foundation models such as large language models (LLMs) have attracted considerable interest from academia and telecom industry. This work…