12 accepted papers
Recent pseudo-bag augmentation methods for Multiple Instance Learning (MIL)-based Whole Slide Image (WSI) classification sample instances from a limited number of bags, resulting in constrained diversity. To address this issue, we propose Contrastive Cross-Bag Augmentation (C2Aug) to sample instance
Mobility impairments among older adults and individuals with neuromuscular weakness motivate the need for timely and adaptive exoskeleton assistance. This paper presents a human-in-the-loop muscle sensing and control system based on capacitive microphone sensors (CMS) that capture subtle mechanical
Despite the rapid evolution of training paradigms, the decoder backbone of large vision--language models (LVLMs) remains fundamentally rooted in the residual-connection Transformer architecture. Therefore, deciphering the distinct roles of internal modules is critical for understanding model mechani…
Tracking Any Point (TAP) is a foundational task in computer vision with broad applicability. The state-of-the-art self-supervised TAP method leverages a global matching transformer and contrastive random walks to learn point correspondences. However, its dense all-pairs attention and correlation vol
Small language models (SLMs) are attractive for agent deployment, but they struggle to reliably retain and reuse decision-relevant state information over long interactions. This issue is exacerbated when working memory is maintained via unstructured natural-language summarization. Some recent work a…
The limited data annotations have made semi-supervised learning (SSL) increasingly popular in medical image analysis. However, the use of pseudo labels in SSL degrades the performance of decoders that heavily rely on high-accuracy annotations. This issue is particularly pronounced in class-imbalance…
Microscale droplet-based robotic systems have emerged as a promising platform for targeted drug delivery, minimally invasive surgery, and lab-on-a-chip applications. Here, we report a novel microrobotic swarm based on microdroplets of silicone oil-based ferrofluid, which exhibits excellent biocompat
Personalized federated learning (PFL) aims to improve the performance of the local model on each client with the non-IID data among different clients. This paper introduces FedFPC, a PFL method that allows effective and robust parameter-wise collaboration to achieve outperforming performance. Stem f…
"In recent years, the Whole Slide Image (WSI) classification task has achieved great advancement due to the success of Multiple Instance Learning (MIL). However, the MIL-based studies usually consider instances within each bag as unordered, potentially resulting in the missing of local and global co…
Adversarial learning plays an important role in recovering 3D human pose and shape from monocular videos. However, the effectiveness of this process is not often considered. Hence we aim to improve the performance of adversarial learning in 3D human pose and shape estimation. The performance of adve…
Traditional robotic systems have proven to be instrumental in object manipulation tasks for automated manufacturing processes. Object manipulation in such cases typically involves transport, pick-and-place and assembly of objects using automated conveyors and robotic arms. However, the forces at mic
We use multiple spinning micro-rafts at the air-water interface as mobile microrobot collectives and present here their collective behaviors, including navigating around anchored obstacles, and trapping and transporting floating objects. The 3D-printed micro-rafts are circular disKS of 100 μm in dia…