Zobrazeno 1 - 10
of 24 529
pro vyhledávání: '"An Jialiang"'
Autor:
Chen, Yuhao, Hu, Jialiang, Cheng, Guanchong, Ye, Jing, Mei, Zhixing, Shen, Chengcai, Lin, Jun
New emerging flux (NEF) has long been considered a mechanism for solar eruptions, but detailed process remains an open question. In this work, we explore how NEF drives a coronal magnetic configuration to erupt. This configuration is created by two m
Externí odkaz:
http://arxiv.org/abs/2411.13839
With the continuous deepening and development of the concept of smart education, learners' comprehensive development and individual needs have received increasing attention. However, traditional educational evaluation systems tend to assess learners'
Externí odkaz:
http://arxiv.org/abs/2411.05325
Prior study shows that LLMs sometimes generate content that violates copyright. In this paper, we study another important yet underexplored problem, i.e., will LLMs respect copyright information in user input, and behave accordingly? The research pro
Externí odkaz:
http://arxiv.org/abs/2411.01136
Autor:
Zhang, Jialiang, Liu, Haoran, Li, Danshi, Yu, Xinqiang, Geng, Haoran, Ding, Yufei, Chen, Jiayi, Wang, He
Grasping in cluttered scenes remains highly challenging for dexterous hands due to the scarcity of data. To address this problem, we present a large-scale synthetic benchmark, encompassing 1319 objects, 8270 scenes, and 427 million grasps. Beyond ben
Externí odkaz:
http://arxiv.org/abs/2410.23004
Probabilistic Bit (P-Bit) device serves as the core hardware for implementing Ising computation. However, the severe intrinsic variations of stochastic P-Bit devices hinder the large-scale expansion of the P-Bit array, significantly limiting the prac
Externí odkaz:
http://arxiv.org/abs/2410.16915
Autor:
Polyak, Adam, Zohar, Amit, Brown, Andrew, Tjandra, Andros, Sinha, Animesh, Lee, Ann, Vyas, Apoorv, Shi, Bowen, Ma, Chih-Yao, Chuang, Ching-Yao, Yan, David, Choudhary, Dhruv, Wang, Dingkang, Sethi, Geet, Pang, Guan, Ma, Haoyu, Misra, Ishan, Hou, Ji, Wang, Jialiang, Jagadeesh, Kiran, Li, Kunpeng, Zhang, Luxin, Singh, Mannat, Williamson, Mary, Le, Matt, Yu, Matthew, Singh, Mitesh Kumar, Zhang, Peizhao, Vajda, Peter, Duval, Quentin, Girdhar, Rohit, Sumbaly, Roshan, Rambhatla, Sai Saketh, Tsai, Sam, Azadi, Samaneh, Datta, Samyak, Chen, Sanyuan, Bell, Sean, Ramaswamy, Sharadh, Sheynin, Shelly, Bhattacharya, Siddharth, Motwani, Simran, Xu, Tao, Li, Tianhe, Hou, Tingbo, Hsu, Wei-Ning, Yin, Xi, Dai, Xiaoliang, Taigman, Yaniv, Luo, Yaqiao, Liu, Yen-Cheng, Wu, Yi-Chiao, Zhao, Yue, Kirstain, Yuval, He, Zecheng, He, Zijian, Pumarola, Albert, Thabet, Ali, Sanakoyeu, Artsiom, Mallya, Arun, Guo, Baishan, Araya, Boris, Kerr, Breena, Wood, Carleigh, Liu, Ce, Peng, Cen, Vengertsev, Dimitry, Schonfeld, Edgar, Blanchard, Elliot, Juefei-Xu, Felix, Nord, Fraylie, Liang, Jeff, Hoffman, John, Kohler, Jonas, Fire, Kaolin, Sivakumar, Karthik, Chen, Lawrence, Yu, Licheng, Gao, Luya, Georgopoulos, Markos, Moritz, Rashel, Sampson, Sara K., Li, Shikai, Parmeggiani, Simone, Fine, Steve, Fowler, Tara, Petrovic, Vladan, Du, Yuming
We present Movie Gen, a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio. We also show additional capabilities such as precise instruction-based video editing and generation of
Externí odkaz:
http://arxiv.org/abs/2410.13720
Publikováno v:
Neurips 2024
One of the roadblocks for training generalist robotic models today is heterogeneity. Previous robot learning methods often collect data to train with one specific embodiment for one task, which is expensive and prone to overfitting. This work studies
Externí odkaz:
http://arxiv.org/abs/2409.20537
Autor:
Zhang, Christina, Motwani, Simran, Yu, Matthew, Hou, Ji, Juefei-Xu, Felix, Tsai, Sam, Vajda, Peter, He, Zijian, Wang, Jialiang
Latent diffusion models (LDMs) have made significant advancements in the field of image generation in recent years. One major advantage of LDMs is their ability to operate in a compressed latent space, allowing for more efficient training and deploym
Externí odkaz:
http://arxiv.org/abs/2409.17565
Knowledge Distillation (KD) transfers knowledge from a large pre-trained teacher network to a compact and efficient student network, making it suitable for deployment on resource-limited media terminals. However, traditional KD methods require balanc
Externí odkaz:
http://arxiv.org/abs/2409.07694
PSLF: A PID Controller-incorporated Second-order Latent Factor Analysis Model for Recommender System
A second-order-based latent factor (SLF) analysis model demonstrates superior performance in graph representation learning, particularly for high-dimensional and incomplete (HDI) interaction data, by incorporating the curvature information of the los
Externí odkaz:
http://arxiv.org/abs/2409.00448