no code implementations • 29 Feb 2024 • Hongyi Liu, Zirui Liu, Ruixiang Tang, Jiayi Yuan, Shaochen Zhong, Yu-Neng Chuang, Li Li, Rui Chen, Xia Hu
Our aim is to raise awareness of the potential risks under the emerging share-and-play scenario, so as to proactively prevent potential consequences caused by LoRA-as-an-Attack.
1 code implementation • 5 Feb 2024 • Zirui Liu, Jiayi Yuan, Hongye Jin, Shaochen Zhong, Zhaozhuo Xu, Vladimir Braverman, Beidi Chen, Xia Hu
This memory demand increases with larger batch sizes and longer context lengths.
no code implementations • 4 Aug 2023 • Qizhang Feng, Jiayi Yuan, Forhan Bin Emdad, Karim Hanna, Xia Hu, Zhe He
Stroke is a significant cause of mortality and morbidity, necessitating early predictive strategies to minimize risks.
no code implementations • 23 Jun 2023 • Zhongzhi Yu, Yonggan Fu, Jiayi Yuan, Haoran You, Yingyan Lin
Tiny deep learning has attracted increasing attention driven by the substantial demand for deploying deep learning on numerous intelligent Internet-of-Things devices.
no code implementations • 24 Apr 2023 • Yonggan Fu, Zhifan Ye, Jiayi Yuan, Shunyao Zhang, Sixu Li, Haoran You, Yingyan Lin
Novel view synthesis is an essential functionality for enabling immersive experiences in various Augmented- and Virtual-Reality (AR/VR) applications, for which generalizable Neural Radiance Fields (NeRFs) have gained increasing popularity thanks to their cross-scene generalization capability.
no code implementations • 24 Apr 2023 • Yonggan Fu, Ye Yuan, Shang Wu, Jiayi Yuan, Yingyan Lin
Transfer learning leverages feature representations of deep neural networks (DNNs) pretrained on source tasks with rich data to empower effective finetuning on downstream tasks.
no code implementations • 24 Mar 2023 • Jiayi Yuan, Ruixiang Tang, Xiaoqian Jiang, Xia Hu
The process of matching patients with suitable clinical trials is essential for advancing medical research and providing optimal care.
no code implementations • 24 Mar 2023 • Chia-Yuan Chang, Jiayi Yuan, Sirui Ding, Qiaoyu Tan, Kai Zhang, Xiaoqian Jiang, Xia Hu, Na Zou
To tackle these challenges, deep learning frameworks have been created to match patients to trials.
no code implementations • 19 Mar 2023 • Chaojian Li, Wenwan Chen, Jiayi Yuan, Yingyan Lin, Ashutosh Sabharwal
To this end, we propose a dedicated neural architecture search framework for Energy-efficient and Real-time SAM (ERSAM).
no code implementations • 31 Jan 2023 • Jiayi Yuan, Haobo Jiang, Xiang Li, Jianjun Qian, Jun Li, Jian Yang
Second, instead of the coarse concatenation guidance, we propose a recurrent structure attention block, which iteratively utilizes the latest depth estimation and the image features to jointly select clear patterns and boundaries, aiming at providing refined guidance for accurate depth recovery.
no code implementations • 31 Jan 2023 • Jiayi Yuan, Haobo Jiang, Xiang Li, Jianjun Qian, Jun Li, Jian Yang
Specifically, our framework consists of a cross-modality flow-guided upsampling network (CFUNet) and a flow-enhanced pyramid edge attention network (PEANet).
1 code implementation • 2 Jun 2022 • Yonggan Fu, Haichuan Yang, Jiayi Yuan, Meng Li, Cheng Wan, Raghuraman Krishnamoorthi, Vikas Chandra, Yingyan Lin
Efficient deep neural network (DNN) models equipped with compact operators (e. g., depthwise convolutions) have shown great potential in reducing DNNs' theoretical complexity (e. g., the total number of weights/operations) while maintaining a decent model accuracy.