Zobrazeno 1 - 10
of 507
pro vyhledávání: '"P. Edalat"'
Humour, a fundamental aspect of human communication, manifests itself in various styles that significantly impact social interactions and mental health. Recognising different humour styles poses challenges due to the lack of established datasets and
Externí odkaz:
http://arxiv.org/abs/2410.12842
In this work, we introduce several schemes to leverage description-augmented embedding similarity for dataless intent classification using current state-of-the-art (SOTA) text embedding models. We report results of our methods on four commonly used i
Externí odkaz:
http://arxiv.org/abs/2407.17862
Autor:
Abaskohi, Amirhossein, Baruni, Sara, Masoudi, Mostafa, Abbasi, Nesa, Babalou, Mohammad Hadi, Edalat, Ali, Kamahi, Sepehr, Sani, Samin Mahdizadeh, Naghavian, Nikoo, Namazifard, Danial, Sadeghi, Pouya, Yaghoobzadeh, Yadollah
This paper explores the efficacy of large language models (LLMs) for Persian. While ChatGPT and consequent LLMs have shown remarkable performance in English, their efficiency for more low-resource languages remains an open question. We present the fi
Externí odkaz:
http://arxiv.org/abs/2404.02403
Autor:
Di Gianantonio, Pietro, Edalat, Abbas
We present a novel, yet rather simple construction within the traditional framework of Scott domains to provide semantics to probabilistic programming, thus obtaining a solution to a long-standing open problem in this area. Unlike current main approa
Externí odkaz:
http://arxiv.org/abs/2402.11727
Understanding various humour styles is essential for comprehending the multifaceted nature of humour and its impact on fields such as psychology and artificial intelligence. This understanding has revealed that humour, depending on the style employed
Externí odkaz:
http://arxiv.org/abs/2402.01759
Autor:
Law, Alicia Jiayun, Hu, Ruoyu, Alazraki, Lisa, Gopalan, Anandha, Polydorou, Neophytos, Edalat, Abbas
Publikováno v:
2022 IEEE 4th International Conference on Cognitive Machine Intelligence (CogMI)
In this work, we propose a computational framework that leverages existing out-of-language data to create a conversational agent for the delivery of Self-Attachment Technique (SAT) in Mandarin. Our framework does not require large-scale human transla
Externí odkaz:
http://arxiv.org/abs/2310.18366
Autor:
Huot, Sébastien, Edalat, Abbas
We study $n$-agent Bayesian Games with $m$-dimensional vector types and linear payoffs, also called Linear Multidimensional Bayesian Games. This class of games is equivalent with $n$-agent, $m$-game Uniform Multigames. We distinguish between games th
Externí odkaz:
http://arxiv.org/abs/2310.13992
Autor:
Elahimanesh, Sina, Salehi, Shayan, Movahed, Sara Zahedi, Alazraki, Lisa, Hu, Ruoyu, Edalat, Abbas
In the wake of the post-pandemic era, marked by social isolation and surging rates of depression and anxiety, conversational agents based on digital psychotherapy can play an influential role compared to traditional therapy sessions. In this work, we
Externí odkaz:
http://arxiv.org/abs/2310.09362
Autor:
Alireza Shamsaeefar, Fatemeh Masjedi, Jamshid Roozbeh, Sahar Sohrabi Nazari, Edalat Zarei, Mehran Jafari, Sara Farifteh, Mohammad Alikhani, Mohammad Eslamian, Maryam Mardani, Reyhaneh Naseri, Hamed Nikoupour
Publikováno v:
Journal of Medical Case Reports, Vol 18, Iss 1, Pp 1-10 (2024)
Abstract Background Situs inversus totalis is a rare congenital anomaly characterized by a mirror-image orientation of abdominal, and in some cases, thoracic organs. Here, we report our situs inversus totalis transplantation experience and further re
Externí odkaz:
https://doaj.org/article/2f022cd81ca14348adaa0f89c0edc814
Publikováno v:
Chinese Journal of Traumatology, Vol 27, Iss 4, Pp 242-248 (2024)
Purpose: Road traffic accidents pose a global challenge with substantial human and economic costs. Iran experiences a high incidence of road traffic injuries, leading to a significant burden on society. This study aims to predict the future burden of
Externí odkaz:
https://doaj.org/article/347ac851b9df4c92913780723c6ff3a1