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pro vyhledávání: '"Akhavan, A."'
Transformer-based Mixture-of-Experts (MoE) models have been driving several recent technological advancements in Natural Language Processing (NLP). These MoE models adopt a router mechanism to determine which experts to activate for routing input tok
Externí odkaz:
http://arxiv.org/abs/2409.06669
Dynamical low-rank approximation allows for solving large-scale matrix differential equations (MDEs) with significantly fewer degrees of freedom and has been applied to a growing number of applications. However, most existing techniques rely on expli
Externí odkaz:
http://arxiv.org/abs/2408.16591
In metal Additive Manufacturing (AM), monitoring the temperature of the Melt Pool (MP) is crucial for ensuring part quality, process stability, defect prevention, and overall process optimization. Traditional methods, are slow to converge and require
Externí odkaz:
http://arxiv.org/abs/2408.11126
Accurately localizing multiple sources is a critical task with various applications in wireless communications, such as emergency services including natural post-disaster search and rescue operations. However, the scenarios where the receiver is movi
Externí odkaz:
http://arxiv.org/abs/2408.06274
Autor:
Ebrahimi, Seyedeh Fatemeh, Azari, Karim Akhavan, Iravani, Amirmasoud, Alizadeh, Hadi, Taghavi, Zeinab Sadat, Sameti, Hossein
Publikováno v:
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
Semantic Textual Relatedness holds significant relevance in Natural Language Processing, finding applications across various domains. Traditionally, approaches to STR have relied on knowledge-based and statistical methods. However, with the emergence
Externí odkaz:
http://arxiv.org/abs/2407.12426
Autor:
Ebrahimi, Seyedeh Fatemeh, Azari, Karim Akhavan, Iravani, Amirmasoud, Qazvini, Arian, Sadeghi, Pouya, Taghavi, Zeinab Sadat, Sameti, Hossein
Detecting Machine-Generated Text (MGT) has emerged as a significant area of study within Natural Language Processing. While language models generate text, they often leave discernible traces, which can be scrutinized using either traditional feature-
Externí odkaz:
http://arxiv.org/abs/2407.11774
Visual attention modeling, important for interpreting and prioritizing visual stimuli, plays a significant role in applications such as marketing, multimedia, and robotics. Traditional saliency prediction models, especially those based on Convolution
Externí odkaz:
http://arxiv.org/abs/2406.17815
Autor:
Anvari, Mohammad Akhavan, Kashefi, Rojina, Khazaie, Vahid Reza, Khalooei, Mohammad, Sabokrou, Mohammad
Anomaly detection involves identifying instances within a dataset that deviate from the norm and occur infrequently. Current benchmarks tend to favor methods biased towards low diversity in normal data, which does not align with real-world scenarios.
Externí odkaz:
http://arxiv.org/abs/2406.10617
We study the contextual continuum bandits problem, where the learner sequentially receives a side information vector and has to choose an action in a convex set, minimizing a function associated to the context. The goal is to minimize all the underly
Externí odkaz:
http://arxiv.org/abs/2406.05714
The InterPlanetary File System (IPFS) is a peer-to-peer network for storing data in a distributed file system, hosting over 190,000 peers spanning 152 countries. Despite its prominence, the privacy properties that IPFS offers to peers are severely li
Externí odkaz:
http://arxiv.org/abs/2405.17307