Clustered Federated Learning (CFL) has emerged as a powerful approach for addressing data heterogeneity and ensuring privacy in large distributed IoT environmen...
The use of Large Language Models (LLMs) as automatic judges for code evaluation is becoming increasingly prevalent in academic environments. But their reliabili...
Real-world AI software engineering demands coding agents that can reason over massive repositories, maintain durable memory across and within long sessions, and...
LLM-agent based binary code analysis has demonstrated significant potential across a wide range of software security scenarios, including vulnerability detectio...
Introduction: The IVF Journey Meets AI Imagine trying to solve one of life’s biggest mysteries—how to help a tiny embryo grow into a healthy baby—with the powe...
The rising demand for collaborative machine learning and data analytics calls for secure and decentralized data sharing frameworks that balance privacy, trust, ...
This document reports the sequence of practices and methodologies implemented during the Big Data course. It details the workflow beginning with the processing ...
Modern cloud platforms increasingly host large-scale deep learning (DL) workloads, demanding high-throughput, low-latency GPU scheduling. However, the growing h...
Efficiency in optimisation and search processes persists to be one of the challenges, which affects the performance and use of optimisation algorithms. Utilisin...
Representations pervade our daily experience, from letters representing sounds to bit strings encoding digital files. While such representations require externa...
World models paired with model predictive control (MPC) can be trained offline on large-scale datasets of expert trajectories and enable generalization to a wid...
Towards human-robot coexistence, socially aware navigation is significant for mobile robots. Yet existing studies on this area focus mainly on path efficiency a...
