Information Overload

Information overload, the overwhelming abundance of data hindering effective knowledge acquisition and decision-making, is a growing concern across various fields. Current research focuses on developing methods to mitigate this problem, including improving large language models (LLMs) to reduce hallucinations and enhance contextual clarity, and designing more efficient information extraction and recommendation systems. These efforts leverage techniques like transformer models, collaborative and content-based filtering, and novel approaches to feature augmentation for deception detection. Ultimately, addressing information overload is crucial for advancing scientific progress and improving the usability of information in practical applications.