Zobrazeno 1 - 10
of 2 208
pro vyhledávání: '"ZHANG, Jiahao"'
Optimizing the learning rate remains a critical challenge in machine learning, essential for achieving model stability and efficient convergence. The Vector Auxiliary Variable (VAV) algorithm introduces a novel energy-based self-adjustable learning r
Externí odkaz:
http://arxiv.org/abs/2411.06573
Autor:
Zhu, Menglin, Xu, Michael, Qi, Yubo, Gilgenbach, Colin, Kim, Jieun, Zhang, Jiahao, Denzer, Bridget R., Martin, Lane W., Rappe, Andrew M., LeBeau, James M.
Introducing structural and/or chemical heterogeneity into otherwise ordered crystals can dramatically alter material properties. Lead-based relaxor ferroelectrics are a prototypical example, with decades of investigation having connected chemical and
Externí odkaz:
http://arxiv.org/abs/2408.11685
As Large Language Models (LLMs) are increasingly being deployed in safety-critical applications, their vulnerability to potential jailbreaks -- malicious prompts that can disable the safety mechanism of LLMs -- has attracted growing research attentio
Externí odkaz:
http://arxiv.org/abs/2408.03603
Autor:
Wang, Bowen, Chang, Jiuyang, Qian, Yiming, Chen, Guoxin, Chen, Junhao, Jiang, Zhouqiang, Zhang, Jiahao, Nakashima, Yuta, Nagahara, Hajime
Large language models (LLMs) have recently showcased remarkable capabilities, spanning a wide range of tasks and applications, including those in the medical domain. Models like GPT-4 excel in medical question answering but may face challenges in the
Externí odkaz:
http://arxiv.org/abs/2408.01933
Autor:
Zhang, Jiahao, Zhang, Frederic Z., Rodriguez, Cristian, Ben-Shabat, Yizhak, Cherian, Anoop, Gould, Stephen
We study the challenging problem of simultaneously localizing a sequence of queries in the form of instructional diagrams in a video. This requires understanding not only the individual queries but also their interrelationships. However, most existin
Externí odkaz:
http://arxiv.org/abs/2407.12066
The imperative to comprehend the behaviors of deep learning models is of utmost importance. In this realm, Explainable Artificial Intelligence (XAI) has emerged as a promising avenue, garnering increasing interest in recent years. Despite this, most
Externí odkaz:
http://arxiv.org/abs/2407.05616
Autor:
Deng, Jinyi, Tang, Xinru, Yue, Zhiheng, Lu, Guangyang, Yang, Qize, Zhang, Jiahao, Li, Jinxi, Li, Chao, Wei, Shaojun, Hu, Yang, Yin, Shouyi
Given the increasing complexity of AI applications, traditional spatial architectures frequently fall short. Our analysis identifies a pattern of interconnected, multi-faceted tasks encompassing both AI and general computational processes. In respons
Externí odkaz:
http://arxiv.org/abs/2405.17221
Autor:
Orenstein, Gal, Krapivin, Viktor, Huang, Yijing, Zhan, Zhuquan, Munoz, Gilberto de la Pena, Duncan, Ryan A., Nguyen, Quynh, Stanton, Jade, Teitelbaum, Samuel, Yavas, Hasan, Sato, Takahiro, Hoffmann, Matthias C., Kramer, Patrick, Zhang, Jiahao, Cavalleri, Andrea, Comin, Riccardo, Dean, Mark P. M., Disa, Ankit S., Forst, Michael, Johnson, Steven L., Mitrano, Matteo, Rappe, Andrew M., Reis, David, Zhu, Diling, Nelson, Keith A., Trigo, Mariano
The nature of the "failed" ferroelectric transition in SrTiO3 has been a long-standing puzzle in condensed matter physics. A compelling explanation is the competition between ferroelectricity and an instability with a mesoscopic modulation of the pol
Externí odkaz:
http://arxiv.org/abs/2403.17203
Autor:
Xu, Minghui, Zhang, Jiahao, Guo, Hechuan, Cheng, Xiuzhen, Yu, Dongxiao, Hu, Qin, Li, Yijun, Wu, Yipu
Decentralized Storage Network (DSN) is an emerging technology that challenges traditional cloud-based storage systems by consolidating storage capacities from independent providers and coordinating to provide decentralized storage and retrieval servi
Externí odkaz:
http://arxiv.org/abs/2403.14985
Graph Neural Networks (GNNs) have achieved remarkable success in various real-world applications. However, GNNs may be trained on undesirable graph data, which can degrade their performance and reliability. To enable trained GNNs to efficiently unlea
Externí odkaz:
http://arxiv.org/abs/2403.07353