Zobrazeno 1 - 10
of 11 744
pro vyhledávání: '"Amir M'"'
Publikováno v:
Empirical Software Engineering. 29, 2024, 1-51
The proxy pattern is a well-known design pattern with numerous use cases in several sectors of the software industry. As such, the use of the proxy pattern is also a common approach in the development of complex decentralized applications (DApps) on
Externí odkaz:
http://arxiv.org/abs/2501.00965
Software applications that run on a blockchain platform are known as DApps. DApps are built using smart contracts, which are immutable after deployment. Just like any real-world software system, DApps need to receive new features and bug fixes over t
Externí odkaz:
http://arxiv.org/abs/2501.00674
Most static program analyses depend on Call Graphs (CGs), including reachability of security vulnerabilities. Static CGs ensure soundness through over-approximation, which results in inflated sizes and imprecision. Recent research has employed machin
Externí odkaz:
http://arxiv.org/abs/2412.09110
Publikováno v:
AEU - International Journal of Electronics and Communications, 2024
In-memory computing (IMC) offloads parts of the computations to memory to fulfill the performance and energy demands of applications such as neuromorphic computing, machine learning, and image processing. Fortunately, the main features that stochasti
Externí odkaz:
http://arxiv.org/abs/2411.19344
Autor:
Majd, Amir M.
One propounded theory for the presence of chaos in biological neural networks is that it could be involved in discriminating different olfactory stimuli. Inspired by the idea, in this paper, we define the visual ``chaotic perception'' and spell out t
Externí odkaz:
http://arxiv.org/abs/2411.08511
Autor:
Vahedi, Amir M., Ilies, Horea T.
Optimization algorithms are pivotal in advancing various scientific and industrial fields but often encounter obstacles such as trapping in local minima, saddle points, and plateaus (flat regions), which makes the convergence to reasonable or near-op
Externí odkaz:
http://arxiv.org/abs/2411.04946
Everyday decisions often involve many different levels. What connects these higher and lower level decisions hierarchy to one another determines how the cause(s) of failures are interpreted. It is hypothesized that decision confidence guides the assi
Externí odkaz:
http://arxiv.org/abs/2410.23313
Autor:
Venkatesh, Ashwin Prasad Shivarpatna, Sunil, Rose, Sabu, Samkutty, Mir, Amir M., Reis, Sofia, Bodden, Eric
Large Language Models (LLMs) are increasingly being explored for their potential in software engineering, particularly in static analysis tasks. In this study, we investigate the potential of current LLMs to enhance call-graph analysis and type infer
Externí odkaz:
http://arxiv.org/abs/2410.00603
In digital healthcare, large language models (LLMs) have primarily been utilized to enhance question-answering capabilities and improve patient interactions. However, effective patient care necessitates LLM chains that can actively gather information
Externí odkaz:
http://arxiv.org/abs/2409.19487
Autor:
Cioppa, Anthony, Giancola, Silvio, Somers, Vladimir, Joos, Victor, Magera, Floriane, Held, Jan, Ghasemzadeh, Seyed Abolfazl, Zhou, Xin, Seweryn, Karolina, Kowalczyk, Mateusz, Mróz, Zuzanna, Łukasik, Szymon, Hałoń, Michał, Mkhallati, Hassan, Deliège, Adrien, Hinojosa, Carlos, Sanchez, Karen, Mansourian, Amir M., Miralles, Pierre, Barnich, Olivier, De Vleeschouwer, Christophe, Alahi, Alexandre, Ghanem, Bernard, Van Droogenbroeck, Marc, Gorski, Adam, Clapés, Albert, Boiarov, Andrei, Afanasiev, Anton, Xarles, Artur, Scott, Atom, Lim, ByoungKwon, Yeung, Calvin, Gonzalez, Cristian, Rüfenacht, Dominic, Pacilio, Enzo, Deuser, Fabian, Altawijri, Faisal Sami, Cachón, Francisco, Kim, HanKyul, Wang, Haobo, Choe, Hyeonmin, Kim, Hyunwoo J, Kim, Il-Min, Kang, Jae-Mo, Tursunboev, Jamshid, Yang, Jian, Hong, Jihwan, Lee, Jimin, Zhang, Jing, Lee, Junseok, Zhang, Kexin, Habel, Konrad, Jiao, Licheng, Li, Linyi, Gutiérrez-Pérez, Marc, Ortega, Marcelo, Li, Menglong, Lopatto, Milosz, Kasatkin, Nikita, Nemtsev, Nikolay, Oswald, Norbert, Udin, Oleg, Kononov, Pavel, Geng, Pei, Alotaibi, Saad Ghazai, Kim, Sehyung, Ulasen, Sergei, Escalera, Sergio, Zhang, Shanshan, Yang, Shuyuan, Moon, Sunghwan, Moeslund, Thomas B., Shandyba, Vasyl, Golovkin, Vladimir, Dai, Wei, Chung, WonTaek, Liu, Xinyu, Zhu, Yongqiang, Kim, Youngseo, Li, Yuan, Yang, Yuting, Xiao, Yuxuan, Cheng, Zehua, Li, Zhihao
The SoccerNet 2024 challenges represent the fourth annual video understanding challenges organized by the SoccerNet team. These challenges aim to advance research across multiple themes in football, including broadcast video understanding, field unde
Externí odkaz:
http://arxiv.org/abs/2409.10587