Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Eetemadi, Sauleh"'
This study investigates the performance of the zero-shot method in classifying data using three large language models, alongside two models with large input token sizes and the two pre-trained models on legal data. Our main dataset comes from the dom
Externí odkaz:
http://arxiv.org/abs/2406.16490
This paper outlines our approach to SemEval 2024 Task 9, BRAINTEASER: A Novel Task Defying Common Sense. The task aims to evaluate the ability of language models to think creatively. The dataset comprises multi-choice questions that challenge models
Externí odkaz:
http://arxiv.org/abs/2406.04947
Publikováno v:
AAAI-2024 Workshop on Public Sector LLMs: Algorithmic and Sociotechnical Design
Stance detection, the classification of attitudes expressed in a text towards a specific topic, is vital for applications like fake news detection and opinion mining. However, the scarcity of labeled data remains a challenge for this task. To address
Externí odkaz:
http://arxiv.org/abs/2405.11637
In recent years, people have increasingly used AI to help them with their problems by asking questions on different topics. One of these topics can be software-related and programming questions. In this work, we focus on the questions which need the
Externí odkaz:
http://arxiv.org/abs/2405.10736
Autor:
Aminimehr, Amirhossein, Aminimehr, Amin, Kamali, Hamid Moradi, Eetemadi, Sauleh, Hoseinzade, Saeid
Studies conducted on financial market prediction lack a comprehensive feature set that can carry a broad range of contributing factors; therefore, leading to imprecise results. Furthermore, while cooperating with the most recent innovations in explai
Externí odkaz:
http://arxiv.org/abs/2405.09932
Large-scale pretrained models such as LXMERT are becoming popular for learning cross-modal representations on text-image pairs for vision-language tasks. According to the lottery ticket hypothesis, NLP and computer vision models contain smaller subne
Externí odkaz:
http://arxiv.org/abs/2310.15325
WSD (Word Sense Disambiguation) is the task of identifying which sense of a word is meant in a sentence or other segment of text. Researchers have worked on this task (e.g. Pustejovsky, 2002) for years but it's still a challenging one even for SOTA (
Externí odkaz:
http://arxiv.org/abs/2212.07669
Publikováno v:
Proceedings of the The Fourth Widening Natural Language Processing Workshop (2020)
Recently, the automatic prediction of personality traits has received increasing attention and has emerged as a hot topic within the field of affective computing. In this work, we present a novel deep learning-based approach for automated personality
Externí odkaz:
http://arxiv.org/abs/2010.01309
Autor:
Ataei, Taha Shangipour, Darvishi, Kamyar, Javdan, Soroush, Minaei-Bidgoli, Behrouz, Eetemadi, Sauleh
Due to the increased availability of online reviews, sentiment analysis had been witnessed a booming interest from the researchers. Sentiment analysis is a computational treatment of sentiment used to extract and understand the opinions of authors. W
Externí odkaz:
http://arxiv.org/abs/1908.01815
Publikováno v:
Machine Translation, 2015 Dec 01. 29(3/4), 189-223.
Externí odkaz:
https://www.jstor.org/stable/44113790
