Zobrazeno 1 - 10
of 24 830
pro vyhledávání: '"Jiacheng An"'
Autor:
Sun, Jiacheng, Li, Fajun, Wang, Xudong, He, Jing, Ni, Dangwu, Wang, Lang, Lin, Shaowei, Min, Qiu, Zhu, Jinfeng, Wen, Liaoyong
Optical metasurface has brought a revolution in label-free molecular sensing, attracting extensive attention. Currently, such sensing approaches are being designed to respond to peak wavelengths with a higher Q factor in the visible and near-infrared
Externí odkaz:
http://arxiv.org/abs/2411.18110
Given a single image of a target object, image-to-3D generation aims to reconstruct its texture and geometric shape. Recent methods often utilize intermediate media, such as multi-view images or videos, to bridge the gap between input image and the 3
Externí odkaz:
http://arxiv.org/abs/2411.18866
Autor:
Yang, Liu, Paischer, Fabian, Hassani, Kaveh, Li, Jiacheng, Shao, Shuai, Li, Zhang Gabriel, He, Yun, Feng, Xue, Noorshams, Nima, Park, Sem, Long, Bo, Nowak, Robert D, Gao, Xiaoli, Eghbalzadeh, Hamid
Sequential dense retrieval models utilize advanced sequence learning techniques to compute item and user representations, which are then used to rank relevant items for a user through inner product computation between the user and all item representa
Externí odkaz:
http://arxiv.org/abs/2411.18814
In the 21st-century information age, with the development of big data technology, effectively extracting valuable information from massive data has become a key issue. Traditional data mining methods are inadequate when faced with large-scale, high-d
Externí odkaz:
http://arxiv.org/abs/2411.18622
Deep Neural Networks exhibit inherent vulnerabilities to adversarial attacks, which can significantly compromise their outputs and reliability. While existing research primarily focuses on attacking single-task scenarios or indiscriminately targeting
Externí odkaz:
http://arxiv.org/abs/2411.17936
In-hospital mortality (IHM) prediction for ICU patients is critical for timely interventions and efficient resource allocation. While structured physiological data provides quantitative insights, clinical notes offer unstructured, context-rich narrat
Externí odkaz:
http://arxiv.org/abs/2411.16818
This paper presents an innovative approach to enhancing few-shot learning by integrating data augmentation with model fine-tuning in a framework designed to tackle the challenges posed by small-sample data. Recognizing the critical limitations of tra
Externí odkaz:
http://arxiv.org/abs/2411.16567
Large language models (LLMs) are known to struggle with complicated reasoning tasks such as math word problems (MWPs). In this paper, we present how analogy from similarly structured questions can improve LLMs' problem-solving capabilities for MWPs.
Externí odkaz:
http://arxiv.org/abs/2411.16454
The surge in micro-videos is transforming the concept of popularity. As researchers delve into vast multi-modal datasets, there is a growing interest in understanding the origins of this popularity and the forces driving its rapid expansion. Recent s
Externí odkaz:
http://arxiv.org/abs/2411.15455
Medical image segmentation is crucial for accurate clinical diagnoses, yet it faces challenges such as low contrast between lesions and normal tissues, unclear boundaries, and high variability across patients. Deep learning has improved segmentation
Externí odkaz:
http://arxiv.org/abs/2411.14353