11 accepted papers
With the rise of cloud-edge collaboration, recommendation services are increasingly trained in distributed environments. Federated Recommendation (FR) enables such multi-end collaborative training while preserving privacy by sharing model parameters instead of raw data. However, the large number of
This paper presents a novel dual tiltrotor UAV design featuring foldable wings and a strategically positioned center of gravity (CG) to enable passive perching and multi-modal flight. Traditional UAVs rely on additional mechanical components for operations such as takeoff and perching, which increas
A pair of vectored thrusts grants bi-copters greater power efficiency than quadrotors but also makes them more susceptible to the uncertain center of gravity, which alters the steady state attitude and challenges the control. In this letter, we leveraged this feature by designing a new bi-copter inc
Although large language models (LLMs) have demonstrated outperforming human experts in medical examinations, it remains challenging to adopt LLMs in real-world clinical decision-making that typically involves multi-hop medical reasoning. Common practices include prompting commercial LLMs and fine-tu
Dynamic Vision Sensors (DVS) capture event data with high temporal resolution and low power consumption, presenting a more efficient solution for visual processing in dynamic and real-time scenarios compared to conventional video capture methods. Event data augmentation serves as an essential method…
As large language models (LLMs) become integral to various applications, ensuring both their safety and utility is paramount. Jailbreak attacks, which manipulate LLMs into generating harmful content, pose significant challenges to this balance. Existing defenses, such as prompt engineering and safet…
Human beings often experience stress, which can significantly influence their performance. This study explores whether Large Language Models (LLMs) exhibit stress responses similar to those of humans and whether their performance fluctuates under different stress-inducing prompts. To investigate thi…
Spiking neural networks (SNNs) are rich in spatio-temporal dynamics and are suitable for processing event-based neuromorphic data. However, event-based datasets are usually less annotated than static datasets. This small data scale makes SNNs prone to overfitting and limits their performance. In or…
Decoding non-invasive brain recordings is pivotal for advancing our understanding of human cognition but faces challenges due to individual differences and complex neural signal representations. Traditional methods often require customized models and extensive trials, lacking interpretability in vis…
A pair of vectored thrusts brings versatility and power efficiency to bi-copter unmanned aerial vehicles (UAVs). One common difficulty confronted by state-of-the-art bi-copter UAVs is the non-minimum phase nature, which puts fundamental limitations in the system and challenges the control. This lett
This paper presents the design, modeling, analysis, and experimental validation of an inductive resonant wireless power transfer (WPT) system to power a micro aerial vehicle (MAV). Using WPT, in general, enables longer flight times, virtually eliminates the need for batteries, and minimizes down tim…