Automated Academic Paper Monitoring with PDF Vector, GPT-3.5 & Slack

This n8n workflow automates monitoring of academic databases like arXiv and Semantic Scholar for new papers matching keywords in Machine Learning, Neural Networks, and Computer Vision. It runs daily at 9 AM, searches recent publications (e.g., last 24 hours), filters by criteria such as authors or journals, generates summaries using GPT-3.5, and creates vector embeddings from PDFs for future retrieval.

Key benefits include staying ahead in fast-evolving fields without manual checks, personalized digests saving hours weekly, and instant Slack notifications for high-impact papers. It supports email digests and archiving for reference, ideal for self-hosted n8n with community nodes.

Perfect for PhD students, research labs, or professionals tracking competitors. Customize queries, schedules, and notifications easily. Enhances productivity by delivering curated, summarized research directly to your tools.