Zobrazeno 1 - 10
of 3 888
pro vyhledávání: '"Jia Zhen-an"'
Autor:
Han, Xiangyu, Jia, Zhen, Li, Boyi, Wang, Yan, Ivanovic, Boris, You, Yurong, Liu, Lingjie, Wang, Yue, Pavone, Marco, Feng, Chen, Li, Yiming
Photorealistic simulators are essential for the training and evaluation of vision-centric autonomous vehicles (AVs). At their core is Novel View Synthesis (NVS), a crucial capability that generates diverse unseen viewpoints to accommodate the broad a
Externí odkaz:
http://arxiv.org/abs/2412.05256
Autor:
Pan, Rui, Wang, Zhuang, Jia, Zhen, Karakus, Can, Zancato, Luca, Dao, Tri, Wang, Yida, Netravali, Ravi
Hybrid models that combine the language modeling capabilities of Attention layers with the efficiency of Recurrent layers (e.g., State Space Models) have gained traction in practically supporting long contexts in Large Language Model serving. Yet, th
Externí odkaz:
http://arxiv.org/abs/2411.19379
Let $m\geq 2$, $n$ be positive integers, and $R_i=\{k_{i,1} >k_{i,2} >\cdots> k_{i,t_i}\}$ be subsets of $[n]$ for $i=1,2,\ldots,m$. The families $\mathcal{F}_1\subseteq \binom{[n]}{R_1},\mathcal{F}_2\subseteq \binom{[n]}{R_2},\ldots,\mathcal{F}_m\su
Externí odkaz:
http://arxiv.org/abs/2411.18426
Training deep neural networks (DNNs) from noisy labels is an important and challenging task. However, most existing approaches focus on the corrupted labels and ignore the importance of inherent data structure. To bridge the gap between noisy labels
Externí odkaz:
http://arxiv.org/abs/2405.01186
Publikováno v:
36th Conference on Neural Information Processing Systems (NeurIPS 2022)
Self-training is a powerful approach to deep learning. The key process is to find a pseudo-label for modeling. However, previous self-training algorithms suffer from the over-confidence issue brought by the hard labels, even some confidence-related r
Externí odkaz:
http://arxiv.org/abs/2405.01175
Publikováno v:
MLSys 2024
Diffusion models have emerged as dominant performers for image generation. To support training large diffusion models, this paper studies pipeline parallel training of diffusion models and proposes DiffusionPipe, a synchronous pipeline training syste
Externí odkaz:
http://arxiv.org/abs/2405.01248
The Mixture-of-Expert (MoE) technique plays a crucial role in expanding the size of DNN model parameters. However, it faces the challenge of extended all-to-all communication latency during the training process. Existing methods attempt to mitigate t
Externí odkaz:
http://arxiv.org/abs/2404.19429
Temporal question answering (QA) involves time constraints, with phrases such as "... in 2019" or "... before COVID". In the former, time is an explicit condition, in the latter it is implicit. State-of-the-art methods have limitations along three di
Externí odkaz:
http://arxiv.org/abs/2402.15400
Multi-task model training has been adopted to enable a single deep neural network model (often a large language model) to handle multiple tasks (e.g., question answering and text summarization). Multi-task training commonly receives input sequences o
Externí odkaz:
http://arxiv.org/abs/2311.10418
Publikováno v:
陆军军医大学学报, Vol 46, Iss 22, Pp 2576-2580 (2024)
Objective To explore the mediating role of personality traits and mental resilience in the relationship between competence and job performance among junior officers. Methods Competency Inventory, 25-Item Connor-Davidson Resilience Scale (CD-RISC-25),
Externí odkaz:
https://doaj.org/article/27cce50af0df41439556eb3c54610856
