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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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Jungha Son and Boyoung Kim
The rapid global expansion of ChatGPT, which plays a crucial role in interactive knowledge sharing and translation, underscores the importance of comparative performance assessments in artificial intelligence (AI) technology. This study concentrated on t...
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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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Atnafu Lambebo Tonja, Olga Kolesnikova, Alexander Gelbukh and Grigori Sidorov
Despite the many proposals to solve the neural machine translation (NMT) problem of low-resource languages, it continues to be difficult. The issue becomes even more complicated when few resources cover only a single domain. In this paper, we discuss the...
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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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Yonghua Wen, Junjun Guo, Zhiqiang Yu and Zhengtao Yu
Parallel sentences play a crucial role in various NLP tasks, particularly for cross-lingual tasks such as machine translation. However, due to the time-consuming and laborious nature of manual construction, many low-resource languages still suffer from a...
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Zohreh Madhoushi, Abdul Razak Hamdan and Suhaila Zainudin
Advancements in text representation have produced many deep language models (LMs), such as Word2Vec and recurrent-based LMs. However, there are scarce works that focus on detecting implicit sentiments with a small amount of labelled data because there ar...
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Ivan Kosyanenko,Roman Bolbakov
Pág. 53 - 59
In today's team-based software development, good commit messages - comments on changes made in natural language - are essential. The metric for evaluating a commit message is its relevance. A good commit message should not only describe the changes made,...
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Kaustubh Mani Tripathi, Pooja Kamat, Shruti Patil, Ruchi Jayaswal, Swati Ahirrao and Ketan Kotecha
This research paper focuses on developing an effective gesture-to-text translation system using state-of-the-art computer vision techniques. The existing research on sign language translation has yet to utilize skin masking, edge detection, and feature e...
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