14 accepted papers
We introduce CMPhysBench, designed to assess the proficiency of Large Language Models (LLMs) in Condensed Matter Physics, as a novel Benchmark. CMPhysBench is composed of more than 520 graduate-level meticulously curated questions covering both representative subfields and foundational theoretical f…
End-to-end planning methods are the de-facto standard of the current autonomous driving system, while the robustness of the data-driven approaches suffers due to the notorious long-tail problem (i.e., rare but safety-critical failure cases). In this work, we explore whether recent diffusion-based vi
With the advance of generative AI, the text-to-image (T2I) model has the ability to generate various contents. However, T2I models still can generate unsafe contents. To alleviate this issue, various concept erasing methods are proposed. However, existing methods tend to excessively erase unsafe con…
Robotic ultrasound systems offer significant potential for automated organ coverage scanning, yet acoustic shadows from bone structures can cause incomplete scans and missed diagnoses. This work presents a real-time coverage path planning method for bone-aware robotic ultrasound scanning. A voxel ba
With the advancement of face recognition (FR) systems, privacy-preserving face recognition (PPFR) systems have gained popularity for their accurate recognition, enhanced facial privacy protection, and robustness to various attacks. However, there are limited studies to further verify privacy risks b
The efficacy of facial recognition systems that utilize deep learning techniques has led to significant concerns over privacy, since they possess the capability to facilitate unauthorized monitoring of individuals in the digital realm. Current techniques for improving privacy are ineffective in prod…
Existing radiance field-based head avatar methods have mostly relied on pre-computed explicit priors (e.g., mesh, point) or neural implicit representations, making it challenging to achieve high fidelity with both computational efficiency and low memory consumption. To overcome this, we present GPAv…
The increasing data volume and the demand for real-time transmission highlight the necessity for efficient compression of dynamic point cloud data. Existing methods primarily focus on reducing inter-frame redundancy by calculating per-point motion information, overlooking the computational and stora…
Most deep learning models of multiclass arrhythmia classification are tested on fingertip photoplethysmographic (PPG) data, which has higher signal-to-noise ratios compared to smartwatch-derived PPG, and the best reported sensitivity value for premature atrial/ventricular contraction (PAC/PVC) detec…
Lane detection is an important yet challenging task in autonomous driving systems. Existing lane detection methods mainly rely on finer-scale information to identify key points of lane lines. Since local information in realistic road environments is frequently obscured by other vehicles or affected…
Tactile sensing plays a vital role for human hand function in terms of object exploration, grasping and manipulation. Different types of tactile sensors have been designed during the past decades, which are mainly focused on either the fingertips for grasping or the upper-body for human-robot intera
A technological revolution is occurring in the field of robotics with the data-driven deep learning technology. However, building datasets for each local robot is laborious. Meanwhile, data islands between local robots make data unable to be utilized collaboratively. To address this issue, the work…
Consider a full-duplex two-way relay network, where two legitimate nodes simultaneously transmit and receive confidential information through a full-duplex multiantenna relay, in the presence of an eavesdropper. To secure the communications, an artificial-noise (AN)-aided amplify-and-forward (AF) st…
Depending on a humanoid finger sensor with multimodal perception capability, physical properties such as pressure, temperature, texture features, surface roughness, micro vibration, etc., could be easily extracted when the sensor contacts with different objects. In this paper, an innovative calibrat…