Zobrazeno 1 - 10
of 3 563
pro vyhledávání: '"Li, TianYu"'
Autor:
Zhou, Chuyu, Li, Tianyu, Lan, Chenxi, Du, Rongyu, Xin, Guoguo, Nan, Pengyu, Yang, Hangzhou, Wang, Guoqing, Liu, Xun, Li, Wei
Soft- and hard-constrained Physics Informed Neural Networks (PINNs) have achieved great success in solving partial differential equations (PDEs). However, these methods still face great challenges when solving the Navier-Stokes equations (NSEs) with
Externí odkaz:
http://arxiv.org/abs/2411.08122
We propose an object-centric recovery policy framework to address the challenges of out-of-distribution (OOD) scenarios in visuomotor policy learning. Previous behavior cloning (BC) methods rely heavily on a large amount of labeled data coverage, fai
Externí odkaz:
http://arxiv.org/abs/2411.03294
Autor:
Liao, Shijia, Wang, Yuxuan, Li, Tianyu, Cheng, Yifan, Zhang, Ruoyi, Zhou, Rongzhi, Xing, Yijin
Text-to-Speech (TTS) systems face ongoing challenges in processing complex linguistic features, handling polyphonic expressions, and producing natural-sounding multilingual speech - capabilities that are crucial for future AI applications. In this pa
Externí odkaz:
http://arxiv.org/abs/2411.01156
Autor:
Wang, Yifeng, Gu, Zhouhong, Zhang, Siwei, Zheng, Suhang, Wang, Tao, Li, Tianyu, Feng, Hongwei, Xiao, Yanghua
Explainable fake news detection predicts the authenticity of news items with annotated explanations. Today, Large Language Models (LLMs) are known for their powerful natural language understanding and explanation generation abilities. However, presen
Externí odkaz:
http://arxiv.org/abs/2409.01787
Autor:
Shao, Yifei Simon, Li, Tianyu, Keyvanian, Shafagh, Chaudhari, Pratik, Kumar, Vijay, Figueroa, Nadia
Constraint-aware estimation of human intent is essential for robots to physically collaborate and interact with humans. Further, to achieve fluid collaboration in dynamic tasks intent estimation should be achieved in real-time. In this paper, we pres
Externí odkaz:
http://arxiv.org/abs/2409.00215
Autor:
Yu, Geoffrey X., Wu, Ziniu, Kossmann, Ferdi, Li, Tianyu, Markakis, Markos, Ngom, Amadou, Madden, Samuel, Kraska, Tim
Modern organizations manage their data with a wide variety of specialized cloud database engines (e.g., Aurora, BigQuery, etc.). However, designing and managing such infrastructures is hard. Developers must consider many possible designs with non-obv
Externí odkaz:
http://arxiv.org/abs/2407.15363
Autor:
Zhou, Minghang, Li, Tianyu, Qiao, Chaofan, Xie, Dongyu, Wang, Guoqing, Ruan, Ningjuan, Mei, Lin, Yang, Yang
Multispectral oriented object detection faces challenges due to both inter-modal and intra-modal discrepancies. Recent studies often rely on transformer-based models to address these issues and achieve cross-modal fusion detection. However, the quadr
Externí odkaz:
http://arxiv.org/abs/2407.08132
Autor:
Bai, Ye, Chen, Jingping, Chen, Jitong, Chen, Wei, Chen, Zhuo, Ding, Chuang, Dong, Linhao, Dong, Qianqian, Du, Yujiao, Gao, Kepan, Gao, Lu, Guo, Yi, Han, Minglun, Han, Ting, Hu, Wenchao, Hu, Xinying, Hu, Yuxiang, Hua, Deyu, Huang, Lu, Huang, Mingkun, Huang, Youjia, Jin, Jishuo, Kong, Fanliu, Lan, Zongwei, Li, Tianyu, Li, Xiaoyang, Li, Zeyang, Lin, Zehua, Liu, Rui, Liu, Shouda, Lu, Lu, Lu, Yizhou, Ma, Jingting, Ma, Shengtao, Pei, Yulin, Shen, Chen, Tan, Tian, Tian, Xiaogang, Tu, Ming, Wang, Bo, Wang, Hao, Wang, Yuping, Wang, Yuxuan, Xia, Hanzhang, Xia, Rui, Xie, Shuangyi, Xu, Hongmin, Yang, Meng, Zhang, Bihong, Zhang, Jun, Zhang, Wanyi, Zhang, Yang, Zhang, Yawei, Zheng, Yijie, Zou, Ming
Modern automatic speech recognition (ASR) model is required to accurately transcribe diverse speech signals (from different domains, languages, accents, etc) given the specific contextual information in various application scenarios. Classic end-to-e
Externí odkaz:
http://arxiv.org/abs/2407.04675
Point clouds are vital in computer vision tasks such as 3D reconstruction, autonomous driving, and robotics. However, TLS-acquired point clouds often contain virtual points from reflective surfaces, causing disruptions. This study presents a reflecti
Externí odkaz:
http://arxiv.org/abs/2407.02830
Autor:
Dauner, Daniel, Hallgarten, Marcel, Li, Tianyu, Weng, Xinshuo, Huang, Zhiyu, Yang, Zetong, Li, Hongyang, Gilitschenski, Igor, Ivanovic, Boris, Pavone, Marco, Geiger, Andreas, Chitta, Kashyap
Benchmarking vision-based driving policies is challenging. On one hand, open-loop evaluation with real data is easy, but these results do not reflect closed-loop performance. On the other, closed-loop evaluation is possible in simulation, but is hard
Externí odkaz:
http://arxiv.org/abs/2406.15349