Zobrazeno 1 - 10
of 888
pro vyhledávání: '"Chen Haipeng"'
Autor:
Lewington, Aiden, Vittalam, Alekhya, Singh, Anshumaan, Uppuluri, Anuja, Ashok, Arjun, Athmaram, Ashrith Mandayam, Milt, Austin, Smith, Benjamin, Weinberger, Charlie, Sarin, Chatanya, Bergmeir, Christoph, Chang, Cliff, Patel, Daivik, Li, Daniel, Bell, David, Cao, Defu, Shin, Donghwa, Kang, Edward, Zhang, Edwin, Li, Enhui, Chen, Felix, Smithline, Gabe, Chen, Haipeng, Gasztowtt, Henry, Shin, Hoon, Zhang, Jiayun, Gray, Joshua, Low, Khai Hern, Patel, Kishan, Cooke, Lauren Hannah, Burstein, Marco, Kalapatapu, Maya, Mittal, Mitali, Chen, Raymond, Zhao, Rosie, Majid, Sameen, Potlapalli, Samya, Wang, Shang, Patel, Shrenik, Li, Shuheng, Komaragiri, Siva, Lu, Song, Siangjaeo, Sorawit, Jung, Sunghoo, Zhang, Tianyu, Mao, Valery, Krishnakumar, Vikram, Zhu, Vincent, Kam, Wesley, Li, Xingzhe, Liu, Yumeng
Advances in artificial intelligence (AI) present significant risks and opportunities, requiring improved governance to mitigate societal harms and promote equitable benefits. Current incentive structures and regulatory delays may hinder responsible A
Externí odkaz:
http://arxiv.org/abs/2412.06936
Large language models (LLMs) have significantly improved their reasoning and decision-making capabilities, as seen in methods like ReAct. However, despite its effectiveness in tackling complex tasks, ReAct faces two main challenges: losing focus on t
Externí odkaz:
http://arxiv.org/abs/2410.10779
Autor:
Wu, Sifan, Chen, Haipeng, Yin, Yifang, Hu, Sihao, Feng, Runyang, Jiao, Yingying, Yang, Ziqi, Liu, Zhenguang
Human pose estimation in videos has long been a compelling yet challenging task within the realm of computer vision. Nevertheless, this task remains difficult because of the complex video scenes, such as video defocus and self-occlusion. Recent metho
Externí odkaz:
http://arxiv.org/abs/2408.02285
Autor:
Yu, Yaolong, Chen, Haipeng
We study an online learning problem in general-sum Stackelberg games, where players act in a decentralized and strategic manner. We study two settings depending on the type of information for the follower: (1) the limited information setting where th
Externí odkaz:
http://arxiv.org/abs/2405.03158
Many experimental studies report that economics students tend to act more selfishly than students of other disciplines, a finding that received widespread public and professional attention. Two main explanations that the existing literature offers fo
Externí odkaz:
http://arxiv.org/abs/2405.03893
Autor:
Messaoud, Safa, Mokeddem, Billel, Xue, Zhenghai, Pang, Linsey, An, Bo, Chen, Haipeng, Chawla, Sanjay
Learning expressive stochastic policies instead of deterministic ones has been proposed to achieve better stability, sample complexity, and robustness. Notably, in Maximum Entropy Reinforcement Learning (MaxEnt RL), the policy is modeled as an expres
Externí odkaz:
http://arxiv.org/abs/2405.00987
We report the results of surveys we conducted in the US and Israel in 2020, a time when many prices increased following the spread of the pandemic. To assess respondents perceptions of price increases, we focus on goods whose prices have increased du
Externí odkaz:
http://arxiv.org/abs/2403.07617
Publikováno v:
Materials Research Express, Vol 7, Iss 5, p 056502 (2020)
The effects of antimony (Sb) on the deformation behaviour of high-grade non-oriented silicon steel at a low temperature were studied by using a Gleeble-3800 thermal simulator and the field-emission scanning-electron microscope. The tensile strength o
Externí odkaz:
https://doaj.org/article/d141ef9183614659806bbacdf810eb7a
Autor:
Yang, Yuheng, Chen, Haipeng, Liu, Zhenguang, Lyu, Yingda, Zhang, Beibei, Wu, Shuang, Wang, Zhibo, Ren, Kui
Action recognition has long been a fundamental and intriguing problem in artificial intelligence. The task is challenging due to the high dimensionality nature of an action, as well as the subtle motion details to be considered. Current state-of-the-
Externí odkaz:
http://arxiv.org/abs/2306.07576
In this paper, we propose a novel image forgery detection paradigm for boosting the model learning capacity on both forgery-sensitive and genuine compact visual patterns. Compared to the existing methods that only focus on the discrepant-specific pat
Externí odkaz:
http://arxiv.org/abs/2304.13349