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Kara Combs, Adam Moyer and Trevor J. Bihl
Recently, generative artificial intelligence (GAI) has impressed the world with its ability to create text, images, and videos. However, there are still areas in which GAI produces undesirable or unintended results due to being ?uncertain?. Before wider ...
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Fenfang Li, Zhengzhang Zhao, Li Wang and Han Deng
Sentence Boundary Disambiguation (SBD) is crucial for building datasets for tasks such as machine translation, syntactic analysis, and semantic analysis. Currently, most automatic sentence segmentation in Tibetan adopts the methods of rule-based and stat...
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Xin Tian and Yuan Meng
Multi-relational graph neural networks (GNNs) have found widespread application in tasks involving enhancing knowledge representation and knowledge graph (KG) reasoning. However, existing multi-relational GNNs still face limitations in modeling the excha...
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Varsha S. Lalapura, Veerender Reddy Bhimavarapu, J. Amudha and Hariram Selvamurugan Satheesh
The Recurrent Neural Networks (RNNs) are an essential class of supervised learning algorithms. Complex tasks like speech recognition, machine translation, sentiment classification, weather prediction, etc., are now performed by well-trained RNNs. Local o...
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Frederick Gyasi and Tim Schlippe
French is a strategically and economically important language in the regions where the African language Twi is spoken. However, only a very small proportion of Twi speakers in Ghana speak French. The development of a Twi?French parallel corpus and corres...
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Célia Tavares, Luciana Oliveira, Pedro Duarte and Manuel Moreira da Silva
According to a recent study by OpenAI, Open Research, and the University of Pennsylvania, large language models (LLMs) based on artificial intelligence (AI), such as generative pretrained transformers (GPTs), may have potential implications for the job m...
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Marian Bucos and Bogdan Dragulescu
Misinformation poses a significant challenge in the digital age, requiring robust methods to detect fake news. This study investigates the effectiveness of using Back Translation (BT) augmentation, specifically transformer-based models, to improve fake n...
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Yanna Sang, Yuan Chen and Juwei Zhang
Neural machine translation has achieved good translation results, but needs further improvement in low-resource and domain-specific translation. To this end, the paper proposed to incorporate source language syntactic information into neural machine tran...
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Zepeng Wang, Yuan Chen and Juwei Zhang
In practical applications, the accuracy of domain terminology translation is an important criterion for the performance evaluation of domain machine translation models. Aiming at the problem of phrase mismatch and improper translation caused by word-by-w...
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Rafal Jaworski, Sanja Seljan and Ivan Dunder
Parallel corpora have been widely used in the fields of natural language processing and translation as they provide crucial multilingual information. They are used to train machine translation systems, compile dictionaries, or generate inter-language wor...
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