Zobrazeno 1 - 10
of 58 991
pro vyhledávání: '"Saleh, P"'
Autor:
Liu, Tianqi, Xiong, Wei, Ren, Jie, Chen, Lichang, Wu, Junru, Joshi, Rishabh, Gao, Yang, Shen, Jiaming, Qin, Zhen, Yu, Tianhe, Sohn, Daniel, Makarova, Anastasiia, Liu, Jeremiah, Liu, Yuan, Piot, Bilal, Ittycheriah, Abe, Kumar, Aviral, Saleh, Mohammad
Reward models (RMs) play a pivotal role in aligning large language models (LLMs) with human preferences. However, traditional RM training, which relies on response pairs tied to specific prompts, struggles to disentangle prompt-driven preferences fro
Externí odkaz:
http://arxiv.org/abs/2409.13156
Autor:
Kaneko, Yuta, Miah, Abu Saleh Musa, Hassan, Najmul, Lee, Hyoun-Sup, Jang, Si-Woong, Shin, Jungpil
Weakly supervised video anomaly detection (WS-VAD) is a crucial area in computer vision for developing intelligent surveillance systems. This system uses three feature streams: RGB video, optical flow, and audio signals, where each stream extracts co
Externí odkaz:
http://arxiv.org/abs/2409.11223
Human Activity Recognition (HAR) systems aim to understand human behaviour and assign a label to each action, attracting significant attention in computer vision due to their wide range of applications. HAR can leverage various data modalities, such
Externí odkaz:
http://arxiv.org/abs/2409.09678
Considering the growing prominence of production-level AI and the threat of adversarial attacks that can evade a model at run-time, evaluating the robustness of models to these evasion attacks is of critical importance. Additionally, testing model ch
Externí odkaz:
http://arxiv.org/abs/2409.07609
We establish empirical risk minimization principles for active learning by deriving a family of upper bounds on the generalization error. Aligning with empirical observations, the bounds suggest that superior query algorithms can be obtained by combi
Externí odkaz:
http://arxiv.org/abs/2409.09078
Autor:
Darzi, Saleh, Yavuz, Attila Altay
As network services progress and mobile and IoT environments expand, numerous security concerns have surfaced for spectrum access systems. The omnipresent risk of Denial-of-Service (DoS) attacks and raising concerns about user privacy (e.g., location
Externí odkaz:
http://arxiv.org/abs/2409.01924
Autor:
Xiong, Wei, Shi, Chengshuai, Shen, Jiaming, Rosenberg, Aviv, Qin, Zhen, Calandriello, Daniele, Khalman, Misha, Joshi, Rishabh, Piot, Bilal, Saleh, Mohammad, Jin, Chi, Zhang, Tong, Liu, Tianqi
Recent studies have shown that large language models' (LLMs) mathematical problem-solving capabilities can be enhanced by integrating external tools, such as code interpreters, and employing multi-turn Chain-of-Thought (CoT) reasoning. While current
Externí odkaz:
http://arxiv.org/abs/2409.02392
This study evaluates the accessibility of public EV charging stations in the Washington metropolitan area using a comprehensive measure that accounts for both destination-based and en route charging opportunities. By incorporating the full spectrum o
Externí odkaz:
http://arxiv.org/abs/2409.08287
Autor:
Miah, Abu Saleh Musa, Hasan, Md. Al Mehedi, Hadiuzzaman, Md, Islam, Muhammad Nazrul, Shin, Jungpil
Hand gesture-based sign language recognition (SLR) is one of the most advanced applications of machine learning, and computer vision uses hand gestures. Although, in the past few years, many researchers have widely explored and studied how to address
Externí odkaz:
http://arxiv.org/abs/2408.14111
Developmental dysgraphia is a neurological disorder that hinders children's writing skills. In recent years, researchers have increasingly explored machine learning methods to support the diagnosis of dysgraphia based on offline and online handwritin
Externí odkaz:
http://arxiv.org/abs/2408.13754