Zobrazeno 1 - 10
of 38 444
pro vyhledávání: '"Li Qi"'
Bias Voltage Driven Tunneling Magnetoresistance Polarity Reversal in 2D Stripy Antiferromagnet CrOCl
Autor:
Zhang, Lihao, Wang, Xiaoyu, Li, Qi, Xie, Haibo, Zhang, Liangliang, Zhang, Lei, Pan, Jie, Cheng, Yingchun, Wang, Zhe
Publikováno v:
Applied Physics Letters 125, 222403(2024)
Atomically thin materials with coupled magnetic and electric polarization are critical for developing energy-efficient and high-density spintronic devices, yet they remain scarce due to often conflicting requirements of stabilizing both magnetic and
Externí odkaz:
http://arxiv.org/abs/2412.04813
Retrieval Augmented Generation (RAG) has proven to be highly effective in boosting the generative performance of language model in knowledge-intensive tasks. However, existing RAG framework either indiscriminately perform retrieval or rely on rigid s
Externí odkaz:
http://arxiv.org/abs/2412.01572
Autor:
He, Hongliang, Huang, Jinfeng, Li, Qi, Wang, Xu, Zhang, Feibin, Yang, Kangding, Meng, Li, Chu, Fulei
In recent years, large language models have made significant advancements in the field of natural language processing, yet there are still inadequacies in specific domain knowledge and applications. This paper Proposes MaintAGT, a professional large
Externí odkaz:
http://arxiv.org/abs/2412.00481
Autor:
Tavanaei, Amir, Koo, Kee Kiat, Ceker, Hayreddin, Jiang, Shaobai, Li, Qi, Han, Julien, Bouyarmane, Karim
In this paper, we study the problem of generating structured objects that conform to a complex schema, with intricate dependencies between the different components (facets) of the object. The facets of the object (attributes, fields, columns, propert
Externí odkaz:
http://arxiv.org/abs/2411.19301
Autor:
Zhang, Zhihui, Hao, Xiaoshuai, Yuan, Hanning, Chi, Lianhua, Guo, Qi, Li, Qi, Yuan, Ziqiang, Pang, Jinhui, Li, Yexin, Ruan, Sijie
Multi-view contrastive clustering (MVCC) has gained significant attention for generating consistent clustering structures from multiple views through contrastive learning. However, most existing MVCC methods create cross-views by combining any two vi
Externí odkaz:
http://arxiv.org/abs/2411.17354
In this work, we systematically explore the data privacy issues of dataset pruning in machine learning systems. Our findings reveal, for the first time, that even if data in the redundant set is solely used before model training, its pruning-phase me
Externí odkaz:
http://arxiv.org/abs/2411.15796
After more than 40 years of development, the fundamental TCP/IP protocol suite, serving as the backbone of the Internet, is widely recognized for having achieved an elevated level of robustness and security. Distinctively, we take a new perspective t
Externí odkaz:
http://arxiv.org/abs/2411.09895
Knowledge graph completion (KGC) is a task of inferring missing triples based on existing Knowledge Graphs (KGs). Both structural and semantic information are vital for successful KGC. However, existing methods only use either the structural knowledg
Externí odkaz:
http://arxiv.org/abs/2411.06660
Autor:
Sium, Yonas, Li, Qi
Graph Neural Networks (GNNs) have become the leading approach for addressing graph analytical problems in various real-world scenarios. However, GNNs may produce biased predictions against certain demographic subgroups due to node attributes and neig
Externí odkaz:
http://arxiv.org/abs/2411.04371
Autor:
Feng, Xuewei, Yang, Yuxiang, Li, Qi, Zhan, Xingxiang, Sun, Kun, Wang, Ziqiang, Wang, Ao, Du, Ganqiu, Xu, Ke
In this paper, we conduct an empirical study on remote DoS attacks targeting NAT networks. We show that Internet attackers operating outside local NAT networks can remotely identify a NAT device and subsequently terminate TCP connections initiated fr
Externí odkaz:
http://arxiv.org/abs/2410.21984