Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Abaskohi, Amirhossein"'
Memes, combining text and images, frequently use metaphors to convey persuasive messages, shaping public opinion. Motivated by this, our team engaged in SemEval-2024 Task 4, a hierarchical multi-label classification task designed to identify rhetoric
Externí odkaz:
http://arxiv.org/abs/2404.03022
Inspired by human cognition, Jiang et al.(2023c) create a benchmark for assessing LLMs' lateral thinking-thinking outside the box. Building upon this benchmark, we investigate how different prompting methods enhance LLMs' performance on this task to
Externí odkaz:
http://arxiv.org/abs/2404.02474
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
In recent years, there has been significant progress in developing pre-trained language models for NLP. However, these models often struggle when fine-tuned on small datasets. To address this issue, researchers have proposed various adaptation approa
Externí odkaz:
http://arxiv.org/abs/2305.18169
Autor:
Salemi, Alireza, Abaskohi, Amirhossein, Tavakoli, Sara, Yaghoobzadeh, Yadollah, Shakery, Azadeh
Multilingual pre-training significantly improves many multilingual NLP tasks, including machine translation. Most existing methods are based on some variants of masked language modeling and text-denoising objectives on monolingual data. Multilingual
Externí odkaz:
http://arxiv.org/abs/2304.01282
Autor:
ShabaniMirzaei, Taha, Chamani, Houmaan, Abaskohi, Amirhossein, Zadeh, Zhivar Sourati Hassan, Bahrak, Behnam
Publikováno v:
Soc. Netw. Anal. Min. 13, 148 (2023)
The Covid-19 pandemic had an enormous effect on our lives, especially on people's interactions. By introducing Covid-19 vaccines, both positive and negative opinions were raised over the subject of taking vaccines or not. In this paper, using data ga
Externí odkaz:
http://arxiv.org/abs/2302.04511
Publikováno v:
ACM Transactions on Asian and Low-Resource Language Information Processing 2022
Emotion recognition is one of the machine learning applications which can be done using text, speech, or image data gathered from social media spaces. Detecting emotion can help us in different fields, including opinion mining. With the spread of soc
Externí odkaz:
http://arxiv.org/abs/2211.08029
Publikováno v:
International Workshop on Semantic Evaluation 2022 co-located with NAACL
Sarcasm is a term that refers to the use of words to mock, irritate, or amuse someone. It is commonly used on social media. The metaphorical and creative nature of sarcasm presents a significant difficulty for sentiment analysis systems based on affe
Externí odkaz:
http://arxiv.org/abs/2204.08198
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing 2022
Preschool evaluation is crucial because it gives teachers and parents influential knowledge about children's growth and development. The COVID-19 pandemic has highlighted the necessity of online assessment for preschool children. One of the areas tha
Externí odkaz:
http://arxiv.org/abs/2203.12886