Zobrazeno 1 - 10
of 2 846
pro vyhledávání: '"Ghiasvand, A."'
Despite the strong performance of large language models (LLMs) in tasks like mathematical reasoning, their practical use is limited by high computational demands and proprietary restrictions. Chain-of-thought (CoT) and program-of-thought (PoT) fine-t
Externí odkaz:
http://arxiv.org/abs/2411.05407
Autor:
Ghiasvand, Sajjad, Yang, Yifan, Xue, Zhiyu, Alizadeh, Mahnoosh, Zhang, Zheng, Pedarsani, Ramtin
Parameter-efficient fine-tuning (PEFT) methods typically assume that Large Language Models (LLMs) are trained on data from a single device or client. However, real-world scenarios often require fine-tuning these models on private data distributed acr
Externí odkaz:
http://arxiv.org/abs/2410.13097
Automated fact-checking is an important task because determining the accurate status of a proposed claim within the vast amount of information available online is a critical challenge. This challenge requires robust evaluation to prevent the spread o
Externí odkaz:
http://arxiv.org/abs/2408.08400
The Industrial Internet of Things (IIoT) is a transformative paradigm that integrates smart sensors, advanced analytics, and robust connectivity within industrial processes, enabling real-time data-driven decision-making and enhancing operational eff
Externí odkaz:
http://arxiv.org/abs/2407.11278
Autor:
Mohammadkhani, Ali Ghiasvand
Recently, various encoder-only and encoder-decoder pre-trained models like BERT and T5 have been applied to automatic essay scoring (AES) as small language models. However, existing studies have primarily treated this task akin to a classification pr
Externí odkaz:
http://arxiv.org/abs/2407.13781
Generative approaches have significantly influenced Aspect-Based Sentiment Analysis (ABSA), garnering considerable attention. However, existing studies often predict target text components monolithically, neglecting the benefits of utilizing single e
Externí odkaz:
http://arxiv.org/abs/2405.06454
As distributed learning applications such as Federated Learning, the Internet of Things (IoT), and Edge Computing grow, it is critical to address the shortcomings of such technologies from a theoretical perspective. As an abstraction, we consider dec
Externí odkaz:
http://arxiv.org/abs/2405.00965
Monitoring the status of large computing systems is essential to identify unexpected behavior and improve their performance and uptime. However, due to the large-scale and distributed design of such computing systems as well as a large number of moni
Externí odkaz:
http://arxiv.org/abs/2402.05114
This work prioritizes building a modular pipeline that utilizes existing models to systematically restore images, rather than creating new restoration models from scratch. Restoration is carried out at an object-specific level, with each object regen
Externí odkaz:
http://arxiv.org/abs/2401.05049
Autor:
Tayebe Ghiasvand, Jamshid Karimi, Iraj Khodadadi, Amirhossein Yazdi, Salman Khazaei, Zahra Abedi Kichi, Seyed Kianoosh Hosseini
Publikováno v:
BMC Genomic Data, Vol 25, Iss 1, Pp 1-14 (2024)
Abstract Background Coronary artery disease (CAD) significantly contributes to global fatalities. Recent studies have demonstrated the crucial roles of sortilin1 (SORT1) and sestrin1 (SESN1) in lipid metabolism, as well as their involvement in the de
Externí odkaz:
https://doaj.org/article/e663ba9a68084975b4096d17399db446
