Zobrazeno 1 - 10
of 81
pro vyhledávání: '"Kolesnikova Olga P."'
Autor:
Yigezu, Mesay Gemeda, Mersha, Melkamu Abay, Bade, Girma Yohannis, Kalita, Jugal, Kolesnikova, Olga, Gelbukh, Alexander
Publikováno v:
ACLing 2024: 6th International Conference on AI in Computational Linguistics
The proliferation of fake news has emerged as a significant threat to the integrity of information dissemination, particularly on social media platforms. Misinformation can spread quickly due to the ease of creating and disseminating content, affecti
Externí odkaz:
http://arxiv.org/abs/2410.02609
This study performs analysis of Predictive statements, Hope speech, and Regret Detection behaviors within cryptocurrency-related discussions, leveraging advanced natural language processing techniques. We introduce a novel classification scheme named
Externí odkaz:
http://arxiv.org/abs/2409.02836
This study delves into the relationship between emotional trends from X platform data and the market dynamics of well-known cryptocurrencies Cardano, Binance, Fantom, Matic, and Ripple over the period from October 2022 to March 2023. Leveraging Senti
Externí odkaz:
http://arxiv.org/abs/2405.03084
Autor:
Tonja, Atnafu Lambebo, Balouchzahi, Fazlourrahman, Butt, Sabur, Kolesnikova, Olga, Ceballos, Hector, Gelbukh, Alexander, Solorio, Thamar
The paper focuses on the marginalization of indigenous language communities in the face of rapid technological advancements. We highlight the cultural richness of these languages and the risk they face of being overlooked in the realm of Natural Lang
Externí odkaz:
http://arxiv.org/abs/2404.05365
Recent research in natural language processing (NLP) has achieved impressive performance in tasks such as machine translation (MT), news classification, and question-answering in high-resource languages. However, the performance of MT leaves much to
Externí odkaz:
http://arxiv.org/abs/2403.19365
Autor:
Tonja, Atnafu Lambebo, Azime, Israel Abebe, Belay, Tadesse Destaw, Yigezu, Mesay Gemeda, Mehamed, Moges Ahmed, Ayele, Abinew Ali, Jibril, Ebrahim Chekol, Woldeyohannis, Michael Melese, Kolesnikova, Olga, Slusallek, Philipp, Klakow, Dietrich, Xiong, Shengwu, Yimam, Seid Muhie
Large language models (LLMs) have gained popularity recently due to their outstanding performance in various downstream Natural Language Processing (NLP) tasks. However, low-resource languages are still lagging behind current state-of-the-art (SOTA)
Externí odkaz:
http://arxiv.org/abs/2403.13737
This paper presents the creation of initial bilingual corpora for thirteen very low-resource languages of India, all from Northeast India. It also presents the results of initial translation efforts in these languages. It creates the first-ever paral
Externí odkaz:
http://arxiv.org/abs/2312.04764
SpaDeLeF: A Dataset for Hierarchical Classification of Lexical Functions for Collocations in Spanish
In natural language processing (NLP), lexical function is a concept to unambiguously represent semantic and syntactic features of words and phrases in text first crafted in the Meaning-Text Theory. Hierarchical classification of lexical functions inv
Externí odkaz:
http://arxiv.org/abs/2311.04189
In this paper, we investigate the issue of hate speech by presenting a novel task of translating hate speech into non-hate speech text while preserving its meaning. As a case study, we use Spanish texts. We provide a dataset and several baselines as
Externí odkaz:
http://arxiv.org/abs/2306.01261
Autor:
Tonja, Atnafu Lambebo, Maldonado-Sifuentes, Christian, Castillo, David Alejandro Mendoza, Kolesnikova, Olga, Castro-Sánchez, Noé, Sidorov, Grigori, Gelbukh, Alexander
In this paper, we present a parallel Spanish-Mazatec and Spanish-Mixtec corpus for machine translation (MT) tasks, where Mazatec and Mixtec are two indigenous Mexican languages. We evaluated the usability of the collected corpus using three different
Externí odkaz:
http://arxiv.org/abs/2305.17404