Keeping up with the daily influx of preprints on arXiv is an overwhelming task. Especially, when lists like quant-ph get around 50 preprints every day! Frustrated by this, I developed an automated, machine-learning-driven dashboard designed to filter the noise and highlight the most relevant daily research. Every night, the system automatically pulls the latest preprint submissions from 'quant-ph + hep-lat + nucl-th' arXiv categories. It employs a natural language processing model to generate embeddings of each paper's abstract. These representations are then evaluated by a custom-trained algorithmic classifier that I specifically tuned to recognize my research interests. The classifier assigns a predictive relevancy score to every new submission. The results are compiled into an interactive, web-based dashboard that I can easily check over my morning coffee.