Zobrazeno 1 - 10
of 490
pro vyhledávání: '"Zhang, Ya‐Qin"'
Autor:
Li, Jianxiong, Wang, Zhihao, Zheng, Jinliang, Zhou, Xiaoai, Wang, Guanming, Song, Guanglu, Liu, Yu, Liu, Jingjing, Zhang, Ya-Qin, Yu, Junzhi, Zhan, Xianyuan
Multimodal task specification is essential for enhanced robotic performance, where \textit{Cross-modality Alignment} enables the robot to holistically understand complex task instructions. Directly annotating multimodal instructions for model trainin
Externí odkaz:
http://arxiv.org/abs/2410.01529
Data generation-based zero-shot learning, although effective in training Small Task-specific Models (STMs) via synthetic datasets generated by Pre-trained Language Models (PLMs), is often limited by the low quality of such synthetic datasets. Previou
Externí odkaz:
http://arxiv.org/abs/2406.12527
Autor:
Gao, Bowen, Tan, Haichuan, Huang, Yanwen, Ren, Minsi, Huang, Xiao, Ma, Wei-Ying, Zhang, Ya-Qin, Lan, Yanyan
Recent advancements in structure-based drug design (SBDD) have significantly enhanced the efficiency and precision of drug discovery by generating molecules tailored to bind specific protein pockets. Despite these technological strides, their practic
Externí odkaz:
http://arxiv.org/abs/2406.08980
Small molecules play a pivotal role in modern medicine, and scrutinizing their interactions with protein targets is essential for the discovery and development of novel, life-saving therapeutics. The term "bioactivity" encompasses various biological
Externí odkaz:
http://arxiv.org/abs/2406.08961
Autor:
Li, Jianxiong, Zheng, Jinliang, Zheng, Yinan, Mao, Liyuan, Hu, Xiao, Cheng, Sijie, Niu, Haoyi, Liu, Jihao, Liu, Yu, Liu, Jingjing, Zhang, Ya-Qin, Zhan, Xianyuan
Multimodal pretraining is an effective strategy for the trinity of goals of representation learning in autonomous robots: 1) extracting both local and global task progressions; 2) enforcing temporal consistency of visual representation; 3) capturing
Externí odkaz:
http://arxiv.org/abs/2402.18137
Autor:
Wang, Zhe, Fan, Siqi, Huo, Xiaoliang, Xu, Tongda, Wang, Yan, Liu, Jingjing, Chen, Yilun, Zhang, Ya-Qin
In autonomous driving, cooperative perception makes use of multi-view cameras from both vehicles and infrastructure, providing a global vantage point with rich semantic context of road conditions beyond a single vehicle viewpoint. Currently, two majo
Externí odkaz:
http://arxiv.org/abs/2402.15272
Autor:
Xu, Tongda, Zhu, Ziran, Li, Jian, He, Dailan, Wang, Yuanyuan, Sun, Ming, Li, Ling, Qin, Hongwei, Wang, Yan, Liu, Jingjing, Zhang, Ya-Qin
Diffusion Inverse Solvers (DIS) are designed to sample from the conditional distribution $p_{\theta}(X_0|y)$, with a predefined diffusion model $p_{\theta}(X_0)$, an operator $f(\cdot)$, and a measurement $y=f(x'_0)$ derived from an unknown image $x'
Externí odkaz:
http://arxiv.org/abs/2403.12063
Autor:
Li, Yuanchun, Wen, Hao, Wang, Weijun, Li, Xiangyu, Yuan, Yizhen, Liu, Guohong, Liu, Jiacheng, Xu, Wenxing, Wang, Xiang, Sun, Yi, Kong, Rui, Wang, Yile, Geng, Hanfei, Luan, Jian, Jin, Xuefeng, Ye, Zilong, Xiong, Guanjing, Zhang, Fan, Li, Xiang, Xu, Mengwei, Li, Zhijun, Li, Peng, Liu, Yang, Zhang, Ya-Qin, Liu, Yunxin
Since the advent of personal computing devices, intelligent personal assistants (IPAs) have been one of the key technologies that researchers and engineers have focused on, aiming to help users efficiently obtain information and execute tasks, and pr
Externí odkaz:
http://arxiv.org/abs/2401.05459
Autor:
Bengio, Yoshua, Hinton, Geoffrey, Yao, Andrew, Song, Dawn, Abbeel, Pieter, Darrell, Trevor, Harari, Yuval Noah, Zhang, Ya-Qin, Xue, Lan, Shalev-Shwartz, Shai, Hadfield, Gillian, Clune, Jeff, Maharaj, Tegan, Hutter, Frank, Baydin, Atılım Güneş, McIlraith, Sheila, Gao, Qiqi, Acharya, Ashwin, Krueger, David, Dragan, Anca, Torr, Philip, Russell, Stuart, Kahneman, Daniel, Brauner, Jan, Mindermann, Sören
Artificial Intelligence (AI) is progressing rapidly, and companies are shifting their focus to developing generalist AI systems that can autonomously act and pursue goals. Increases in capabilities and autonomy may soon massively amplify AI's impact,
Externí odkaz:
http://arxiv.org/abs/2310.17688
Vertical Federated Learning (VFL) has emerged as a collaborative training paradigm that allows participants with different features of the same group of users to accomplish cooperative training without exposing their raw data or model parameters. VFL
Externí odkaz:
http://arxiv.org/abs/2310.09827