Zobrazeno 1 - 10
of 3 562
pro vyhledávání: '"Lei, TAO"'
Autor:
Gunter, Tom, Wang, Zirui, Wang, Chong, Pang, Ruoming, Narayanan, Andy, Zhang, Aonan, Zhang, Bowen, Chen, Chen, Chiu, Chung-Cheng, Qiu, David, Gopinath, Deepak, Yap, Dian Ang, Yin, Dong, Nan, Feng, Weers, Floris, Yin, Guoli, Huang, Haoshuo, Wang, Jianyu, Lu, Jiarui, Peebles, John, Ye, Ke, Lee, Mark, Du, Nan, Chen, Qibin, Keunebroek, Quentin, Wiseman, Sam, Evans, Syd, Lei, Tao, Rathod, Vivek, Kong, Xiang, Du, Xianzhi, Li, Yanghao, Wang, Yongqiang, Gao, Yuan, Ahmed, Zaid, Xu, Zhaoyang, Lu, Zhiyun, Rashid, Al, Jose, Albin Madappally, Doane, Alec, Bencomo, Alfredo, Vanderby, Allison, Hansen, Andrew, Jain, Ankur, Anupama, Anupama Mann, Kamal, Areeba, Wu, Bugu, Brum, Carolina, Maalouf, Charlie, Erdenebileg, Chinguun, Dulhanty, Chris, Moritz, Dominik, Kang, Doug, Jimenez, Eduardo, Ladd, Evan, Shi, Fangping, Bai, Felix, Chu, Frank, Hohman, Fred, Kotek, Hadas, Coleman, Hannah Gillis, Li, Jane, Bigham, Jeffrey, Cao, Jeffery, Lai, Jeff, Cheung, Jessica, Shan, Jiulong, Zhou, Joe, Li, John, Qin, Jun, Singh, Karanjeet, Vega, Karla, Zou, Kelvin, Heckman, Laura, Gardiner, Lauren, Bowler, Margit, Cordell, Maria, Cao, Meng, Hay, Nicole, Shahdadpuri, Nilesh, Godwin, Otto, Dighe, Pranay, Rachapudi, Pushyami, Tantawi, Ramsey, Frigg, Roman, Davarnia, Sam, Shah, Sanskruti, Guha, Saptarshi, Sirovica, Sasha, Ma, Shen, Ma, Shuang, Wang, Simon, Kim, Sulgi, Jayaram, Suma, Shankar, Vaishaal, Paidi, Varsha, Kumar, Vivek, Wang, Xin, Zheng, Xin, Cheng, Walker, Shrager, Yael, Ye, Yang, Tanaka, Yasu, Guo, Yihao, Meng, Yunsong, Luo, Zhao Tang, Ouyang, Zhi, Aygar, Alp, Wan, Alvin, Walkingshaw, Andrew, Lin, Antonie, Farooq, Arsalan, Ramerth, Brent, Reed, Colorado, Bartels, Chris, Chaney, Chris, Riazati, David, Yang, Eric Liang, Feldman, Erin, Hochstrasser, Gabriel, Seguin, Guillaume, Belousova, Irina, Pelemans, Joris, Yang, Karen, Vahid, Keivan Alizadeh, Cao, Liangliang, Najibi, Mahyar, Zuliani, Marco, Horton, Max, Cho, Minsik, Bhendawade, Nikhil, Dong, Patrick, Maj, Piotr, Agrawal, Pulkit, Shan, Qi, Fu, Qichen, Poston, Regan, Xu, Sam, Liu, Shuangning, Rao, Sushma, Heeramun, Tashweena, Merth, Thomas, Rayala, Uday, Cui, Victor, Sridhar, Vivek Rangarajan, Zhang, Wencong, Zhang, Wenqi, Wu, Wentao, Zhou, Xingyu, Liu, Xinwen, Zhao, Yang, Xia, Yin, Ren, Zhile, Ren, Zhongzheng
We present foundation language models developed to power Apple Intelligence features, including a ~3 billion parameter model designed to run efficiently on devices and a large server-based language model designed for Private Cloud Compute. These mode
Externí odkaz:
http://arxiv.org/abs/2407.21075
Autor:
McKinzie, Brandon, Gan, Zhe, Fauconnier, Jean-Philippe, Dodge, Sam, Zhang, Bowen, Dufter, Philipp, Shah, Dhruti, Du, Xianzhi, Peng, Futang, Weers, Floris, Belyi, Anton, Zhang, Haotian, Singh, Karanjeet, Kang, Doug, Jain, Ankur, Hè, Hongyu, Schwarzer, Max, Gunter, Tom, Kong, Xiang, Zhang, Aonan, Wang, Jianyu, Wang, Chong, Du, Nan, Lei, Tao, Wiseman, Sam, Yin, Guoli, Lee, Mark, Wang, Zirui, Pang, Ruoming, Grasch, Peter, Toshev, Alexander, Yang, Yinfei
In this work, we discuss building performant Multimodal Large Language Models (MLLMs). In particular, we study the importance of various architecture components and data choices. Through careful and comprehensive ablations of the image encoder, the v
Externí odkaz:
http://arxiv.org/abs/2403.09611
Publikováno v:
Open Geosciences, Vol 16, Iss 1, Pp 669-79 (2024)
The Lower Shihezi Formation of the Upper Paleozoic at the northeastern margin of the Ordos Basin develops widely distributed thick massive and multilayer gas reservoirs. How to formulate an effective development policy is a difficult and hot spot. In
Externí odkaz:
https://doaj.org/article/0479e00d06484ca3b71a2b7ebddc2893
The hybrid architecture of convolution neural networks (CNN) and Transformer has been the most popular method for medical image segmentation. However, the existing networks based on the hybrid architecture suffer from two problems. First, although th
Externí odkaz:
http://arxiv.org/abs/2306.04086
Publikováno v:
The 32nd International Joint Conference on Artificial Intelligence, IJCAI2023, MACAO
The hybrid architecture of convolutional neural networks (CNNs) and Transformer are very popular for medical image segmentation. However, it suffers from two challenges. First, although a CNNs branch can capture the local image features using vanilla
Externí odkaz:
http://arxiv.org/abs/2306.03373
Autor:
Lei, Tao, Xu, Yetong, Ning, Hailong, Lv, Zhiyong, Min, Chongdan, Jin, Yaochu, Nandi, Asoke K.
Popular Transformer networks have been successfully applied to remote sensing (RS) image change detection (CD) identifications and achieve better results than most convolutional neural networks (CNNs), but they still suffer from two main problems. Fi
Externí odkaz:
http://arxiv.org/abs/2306.01988
Autor:
Lei, Tao, Bai, Junwen, Brahma, Siddhartha, Ainslie, Joshua, Lee, Kenton, Zhou, Yanqi, Du, Nan, Zhao, Vincent Y., Wu, Yuexin, Li, Bo, Zhang, Yu, Chang, Ming-Wei
We propose Conditional Adapter (CoDA), a parameter-efficient transfer learning method that also improves inference efficiency. CoDA generalizes beyond standard adapter approaches to enable a new way of balancing speed and accuracy using conditional c
Externí odkaz:
http://arxiv.org/abs/2304.04947
Autor:
Lee, Jinhyuk, Dai, Zhuyun, Duddu, Sai Meher Karthik, Lei, Tao, Naim, Iftekhar, Chang, Ming-Wei, Zhao, Vincent Y.
Multi-vector retrieval models such as ColBERT [Khattab and Zaharia, 2020] allow token-level interactions between queries and documents, and hence achieve state of the art on many information retrieval benchmarks. However, their non-linear scoring fun
Externí odkaz:
http://arxiv.org/abs/2304.01982
Autor:
Ainslie, Joshua, Lei, Tao, de Jong, Michiel, Ontañón, Santiago, Brahma, Siddhartha, Zemlyanskiy, Yury, Uthus, David, Guo, Mandy, Lee-Thorp, James, Tay, Yi, Sung, Yun-Hsuan, Sanghai, Sumit
Many natural language processing tasks benefit from long inputs, but processing long documents with Transformers is expensive -- not only due to quadratic attention complexity but also from applying feedforward and projection layers to every token. H
Externí odkaz:
http://arxiv.org/abs/2303.09752