Zobrazeno 1 - 10
of 3 981
pro vyhledávání: '"CAO Qi"'
Publikováno v:
Hangkong gongcheng jinzhan, Vol 15, Iss 5, Pp 148-154 (2024)
The aerodynamic noise test of counter-rotating propellers in wind tunnels has the problems of difficult time coordination and high cost. The aerodynamic noise test system of counter-rotating propellers，which is capable of simulating the driving sta
Externí odkaz:
https://doaj.org/article/22269dd690c14de8a8e3775dfb0e2682
Publikováno v:
Fushe yanjiu yu fushe gongyi xuebao, Vol 42, Iss 3, Pp 030101-030101 (2024)
Effective water chemistry technology can inhibit the radiolysis of primary coolants and material corrosion in pressurized water reactors (PWRs). Research and operational experience suggest that methanol is a potential additive for the coolant transfo
Externí odkaz:
https://doaj.org/article/0e02d3adc744489595c18de257f679f0
Adversarial Collaborative Filtering (ACF), which typically applies adversarial perturbations at user and item embeddings through adversarial training, is widely recognized as an effective strategy for enhancing the robustness of Collaborative Filteri
Externí odkaz:
http://arxiv.org/abs/2410.22844
Autor:
Uchiyama, Fumiya, Kojima, Takeshi, Gambardella, Andrew, Cao, Qi, Iwasawa, Yusuke, Matsuo, Yutaka
Recent large language models (LLMs) have demonstrated remarkable generalization abilities in mathematics and logical reasoning tasks. Prior research indicates that LLMs pre-trained with programming language data exhibit high mathematical and reasonin
Externí odkaz:
http://arxiv.org/abs/2410.06735
Autor:
Takashiro, Shota, Kojima, Takeshi, Gambardella, Andrew, Cao, Qi, Iwasawa, Yusuke, Matsuo, Yutaka
As large language models (LLMs) are applied across diverse domains, the ability to selectively unlearn specific information has become increasingly essential. For instance, LLMs are expected to provide confidential information to authorized internal
Externí odkaz:
http://arxiv.org/abs/2410.00382
Improving the Shortest Plank: Vulnerability-Aware Adversarial Training for Robust Recommender System
Recommender systems play a pivotal role in mitigating information overload in various fields. Nonetheless, the inherent openness of these systems introduces vulnerabilities, allowing attackers to insert fake users into the system's training data to s
Externí odkaz:
http://arxiv.org/abs/2409.17476
Publikováno v:
Fushe yanjiu yu fushe gongyi xuebao, Vol 41, Iss 3, Pp 030201-030201 (2023)
In this study, the γ-radiolysis of boric acid-lithium hydroxide-ammonia coolant was investigated under different conditions, including boric acid concentration, absorbed dose, and absorbed dose rate. The concentrations of H2O2, NO2-, and NO3- were d
Externí odkaz:
https://doaj.org/article/c151d3bd66d24a1796467ed680432915
Publikováno v:
网络与信息安全学报, Vol 7, Iss 1, Pp 65-75 (2021)
Hyperledger Fabric is an extensible alliance blockchain platform and provides support for enterprise-level commercial blockchain projects. The cryptographic algorithm is the core technologies of the platform, ensuring the security and non-tampering o
Externí odkaz:
https://doaj.org/article/72a5c8fbe2ac442d94557f5d3a44dedd
Recent studies have demonstrated the vulnerability of recommender systems to data poisoning attacks, where adversaries inject carefully crafted fake user interactions into the training data of recommenders to promote target items. Current attack meth
Externí odkaz:
http://arxiv.org/abs/2408.10666
This paper investigates the zero-error capacity of channels with memory. Motivated by the nuanced requirements of semantic communication that incorporate memory, we advance the classical enlightened dictator channel by introducing a new category know
Externí odkaz:
http://arxiv.org/abs/2407.21732