Zobrazeno 1 - 10
of 404
pro vyhledávání: '"Li, Yiyuan"'
Fuzzy reasoning is vital due to the frequent use of imprecise information in daily contexts. However, the ability of current large language models (LLMs) to handle such reasoning remains largely uncharted. In this paper, we introduce a new benchmark,
Externí odkaz:
http://arxiv.org/abs/2407.01046
Autor:
Huang, Zhen, Wang, Zengzhi, Xia, Shijie, Li, Xuefeng, Zou, Haoyang, Xu, Ruijie, Fan, Run-Ze, Ye, Lyumanshan, Chern, Ethan, Ye, Yixin, Zhang, Yikai, Yang, Yuqing, Wu, Ting, Wang, Binjie, Sun, Shichao, Xiao, Yang, Li, Yiyuan, Zhou, Fan, Chern, Steffi, Qin, Yiwei, Ma, Yan, Su, Jiadi, Liu, Yixiu, Zheng, Yuxiang, Zhang, Shaoting, Lin, Dahua, Qiao, Yu, Liu, Pengfei
The evolution of Artificial Intelligence (AI) has been significantly accelerated by advancements in Large Language Models (LLMs) and Large Multimodal Models (LMMs), gradually showcasing potential cognitive reasoning abilities in problem-solving and s
Externí odkaz:
http://arxiv.org/abs/2406.12753
Generalization remains a central challenge in machine learning. In this work, we propose Learning from Teaching (LoT), a novel regularization technique for deep neural networks to enhance generalization. Inspired by the human ability to capture conci
Externí odkaz:
http://arxiv.org/abs/2402.02769
Generalized quantifiers (e.g., few, most) are used to indicate the proportions predicates are satisfied (for example, some apples are red). One way to interpret quantifier semantics is to explicitly bind these satisfactions with percentage scopes (e.
Externí odkaz:
http://arxiv.org/abs/2311.04659
Pretrained language models (PLMs) have been shown to accumulate factual knowledge during pretrainingng (Petroni et al., 2019). Recent works probe PLMs for the extent of this knowledge through prompts either in discrete or continuous forms. However, t
Externí odkaz:
http://arxiv.org/abs/2211.07078
Autor:
Li, Yiyuan1 (AUTHOR), Chen, Weiyi1 (AUTHOR), Liu, Shukan1 (AUTHOR), Yang, Guang1 (AUTHOR), He, Fan1 (AUTHOR)
Publikováno v:
International Journal of Aerospace Engineering. 5/24/2024, Vol. 2024, p1-17. 17p.
This paper presents two approaches of privacy-preserving voting system: Blind Signature-based Voting (BSV) and Homorphic Encryption Based Voting (HEV). BSV is simple, stable, and scalable, but requires additional anonymous property in the communicati
Externí odkaz:
http://arxiv.org/abs/2205.12094
Publikováno v:
IEEE Access, Vol 12, Pp 9497-9509 (2024)
Supercavitating vehicles have received significant attention in military applications due to their high underwater speed. This paper aims to establish analytic models of the encounter probability between a supercavitating vehicle and its target in tw
Externí odkaz:
https://doaj.org/article/d02a5a91c41c445781d093b43f914a67
Autor:
Gallo, Lucas, Churchill, Isabella F., Wong Riff, Karen W.Y., Bulstrode, Neil W., Berenguer, Beatriz, Cui, Chunxiao, Li, Yiyuan, Zhang, Ruhong, Klassen, Anne F., Rae, Charlene
Publikováno v:
In Journal of Plastic, Reconstructive & Aesthetic Surgery June 2024 93:62-69
Autor:
Chowdhury, Somnath Basu Roy, Ghosh, Sayan, Li, Yiyuan, Oliva, Junier B., Srivastava, Shashank, Chaturvedi, Snigdha
Contextual representations learned by language models can often encode undesirable attributes, like demographic associations of the users, while being trained for an unrelated target task. We aim to scrub such undesirable attributes and learn fair re
Externí odkaz:
http://arxiv.org/abs/2109.08613