Used local Ollama (gemma4:e4b + nomic-embed-text) to bulk-generate AI summaries for 4300 arXiv papers and push them to a remote Cloudflare DB — pipeline walkthrough
A developer has created ArxivExplorer, a tool that generates AI summaries for arXiv papers using a local pipeline. The system processes approximately 4300 papers, employing Gemma 4 for summarization and Nomic-Embed-Text for generating embeddings. These summaries and embeddings are then stored in a remote Cloudflare database, with a 95% success rate for academic papers in the cs.AI/cs.LG categories. AI
IMPACT Demonstrates efficient local processing of large academic datasets, potentially reducing reliance on cloud APIs for similar tasks.