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This experiment explores how different language variations impact AI-generated outputs. Using 200 prompts, three bilingual evaluators assessed AI-generated images based on prompts in different languages.
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This project explores the intersection of Data Science, Machine Learning, and AI Communication, highlighting the importance of effectively conveying AI-driven insights to diverse audiences.
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This study focuses on the classification of hotel reviews as either truthful or deceptive. Various machine learning models were evaluated to determine their effectiveness in identifying deceptive reviews.
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Modern software often integrates multiple programming languages, increasing complexity and security vulnerabilities. This paper investigates how known sanitizers can be adapted to detect and mitigate cross-language call vulnerabilities.