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Found 12 papers, 1 papers with code
ChatGPT and Beyond: The Generative AI Revolution in Education
The wide adoption and usage of generative artificial intelligence (AI) models, particularly ChatGPT, has sparked a surge in research exploring their potential applications in the educational landscape.
Healthcare Knowledge Graph Construction: State-of-the-art, open issues, and opportunities
The incorporation of data analytics in the healthcare industry has made significant progress, driven by the demand for efficient and effective big data analytics solutions.
A Benchmark Arabic Dataset for Commonsense Explanation
Language comprehension and commonsense knowledge validation by machines are challenging tasks that are still under researched and evaluated for Arabic text.
JUSTMasters at SemEval-2020 Task 3: Multilingual Deep Learning Model to Predict the Effect of Context in Word Similarity
In this task, the organizers provided unlabeled datasets for four languages, English, Croatian, Finnish and Slovenian.
HR@JUST Team at SemEval-2020 Task 4: The Impact of RoBERTa Transformer for Evaluation Common Sense Understanding
This paper describes the results of our team HR@JUST participation at SemEval-2020 Task 4 - Commonsense Validation and Explanation (ComVE) for POST evaluation period.
NLP@JUST at SemEval-2020 Task 4: Ensemble Technique for BERT and Roberta to Evaluate Commonsense Validation
This paper presents the work of the NLP@JUST team at SemEval-2020 Task 4 competition that related to commonsense validation and explanation (ComVE) task.
Is this sentence valid? An Arabic Dataset for Commonsense Validation
In this paper, we present a benchmark Arabic dataset for commonsense understanding and validation as well as a baseline research and models trained using the same dataset.
KEIS@JUST at SemEval-2020 Task 12: Identifying Multilingual Offensive Tweets Using Weighted Ensemble and Fine-Tuned BERT
This research presents our team KEIS@JUST participation at SemEval-2020 Task 12 which represents shared task on multilingual offensive language.
SAJA at TRAC 2020 Shared Task: Transfer Learning for Aggressive Identification with XGBoost
we have developed a system based on transfer learning technique depending on universal sentence encoder (USE) embedding that will be trained in our developed model using xgboost classifier to identify the aggressive text data from English content.
Team JUST at the MADAR Shared Task on Arabic Fine-Grained Dialect Identification
In this paper, we describe our team{'}s effort on the MADAR Shared Task on Arabic Fine-Grained Dialect Identification.
