Zobrazeno 1 - 10
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pro vyhledávání: '"Yingbo An"'
Autor:
Yingbo An, Huasen Zhou
Publikováno v:
Energy Reports, Vol 8, Iss , Pp 1004-1012 (2022)
In rural energy construction, systematic research is needed in multiple fields including the following: basic frontier investigation on energy resource evaluation and optimal regulation, development of common key technologies, application demonstrati
Externí odkaz:
https://doaj.org/article/0cdc694c801e453c877827723e6a66fe
Autor:
Cao, Lu, Xue, Yucheng, Wang, Yingbo, Zhang, Fu-Chun, Kang, Jian, Gao, Hong-Jun, Mao, Jinhai, Jiang, Yuhang
Publikováno v:
Nat Commun 15, 7234 (2024)
Pair density wave (PDW) is a distinct superconducting state characterized by a periodic modulation of its order parameter in real space. Its intricate interplay with the charge density wave (CDW) state is a continuing topic of interest in condensed m
Externí odkaz:
http://arxiv.org/abs/2409.00660
Autor:
Qin, Can, Xia, Congying, Ramakrishnan, Krithika, Ryoo, Michael, Tu, Lifu, Feng, Yihao, Shu, Manli, Zhou, Honglu, Awadalla, Anas, Wang, Jun, Purushwalkam, Senthil, Xue, Le, Zhou, Yingbo, Wang, Huan, Savarese, Silvio, Niebles, Juan Carlos, Chen, Zeyuan, Xu, Ran, Xiong, Caiming
We present xGen-VideoSyn-1, a text-to-video (T2V) generation model capable of producing realistic scenes from textual descriptions. Building on recent advancements, such as OpenAI's Sora, we explore the latent diffusion model (LDM) architecture and i
Externí odkaz:
http://arxiv.org/abs/2408.12590
Autor:
Zhang, Kexun, Yao, Weiran, Liu, Zuxin, Feng, Yihao, Liu, Zhiwei, Murthy, Rithesh, Lan, Tian, Li, Lei, Lou, Renze, Xu, Jiacheng, Pang, Bo, Zhou, Yingbo, Heinecke, Shelby, Savarese, Silvio, Wang, Huan, Xiong, Caiming
Large language model (LLM) agents have shown great potential in solving real-world software engineering (SWE) problems. The most advanced open-source SWE agent can resolve over 27% of real GitHub issues in SWE-Bench Lite. However, these sophisticated
Externí odkaz:
http://arxiv.org/abs/2408.07060
Single-pixel imaging (SPI) using a single-pixel detector is an unconventional imaging method, which has great application prospects in many fields to realize high-performance imaging. In especial, the recent proposed catadioptric panoramic ghost imag
Externí odkaz:
http://arxiv.org/abs/2407.19130
Autor:
Ma, Yingbo, Song, Yukyeong, Balch, Jeremy A., Ren, Yuanfang, Vellanki, Divya, Hu, Zhenhong, Brennan, Meghan, Kolla, Suraj, Guan, Ziyuan, Armfield, Brooke, Ozrazgat-Baslanti, Tezcan, Rashidi, Parisa, Loftus, Tyler J., Bihorac, Azra, Shickel, Benjamin
As more clinical workflows continue to be augmented by artificial intelligence (AI), AI literacy among physicians will become a critical requirement for ensuring safe and ethical AI-enabled patient care. Despite the evolving importance of AI in healt
Externí odkaz:
http://arxiv.org/abs/2407.18939
Large language models (LLMs) for code are typically trained to align with natural language instructions to closely follow their intentions and requirements. However, in many practical scenarios, it becomes increasingly challenging for these models to
Externí odkaz:
http://arxiv.org/abs/2407.02518
Autor:
Dong, Hanze, Xiong, Wei, Pang, Bo, Wang, Haoxiang, Zhao, Han, Zhou, Yingbo, Jiang, Nan, Sahoo, Doyen, Xiong, Caiming, Zhang, Tong
We present the workflow of Online Iterative Reinforcement Learning from Human Feedback (RLHF) in this technical report, which is widely reported to outperform its offline counterpart by a large margin in the recent large language model (LLM) literatu
Externí odkaz:
http://arxiv.org/abs/2405.07863
Although Federated Learning (FL) enables collaborative learning in Artificial Intelligence of Things (AIoT) design, it fails to work on low-memory AIoT devices due to its heavy memory usage. To address this problem, various federated pruning methods
Externí odkaz:
http://arxiv.org/abs/2405.04765
Autor:
Ren, Yuanfang, Tripathi, Chirayu, Guan, Ziyuan, Zhu, Ruilin, Hougha, Victoria, Ma, Yingbo, Hu, Zhenhong, Balch, Jeremy, Loftus, Tyler J., Rashidi, Parisa, Shickel, Benjamin, Ozrazgat-Baslanti, Tezcan, Bihorac, Azra
Given the sheer volume of surgical procedures and the significant rate of postoperative fatalities, assessing and managing surgical complications has become a critical public health concern. Existing artificial intelligence (AI) tools for risk survei
Externí odkaz:
http://arxiv.org/abs/2404.16064