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This paper presents a sentiment analysis and spam detection system for Arabic tweets using the MARBERT model, trained on a dataset of 24,513 tweets to improve customer service for Saudi Telecom Company.
OpenAI demonstrates that domain randomization—randomly varying colors, textures, lighting, and camera settings in simulated training data—enables deep learning models to effectively transfer from simulation to real-world robotic spam detection tasks without retraining from scratch.