Automated Batch Processing Solutions
To address the inefficiency of reading arXiv papers manually, arXiv Summarizer offers three efficient automation options:
- Batch URL processing: Create a text file containing the URLs of multiple papers via the
python url_summarize.py --batch urls.txtcommand to realize batch summary generation. Each URL should occupy one line, and it is recommended to process no more than 20 articles at one time to avoid triggering the API limit. - Keyword monitoring: Modification
keyword_summarize.pyConfiguration file, set the target keywords (e.g. "quantum computing") and date range. The system will automatically crawl the matching papers and generate abstracts through arXiv API. - timed task: Combine with cron (Linux/Mac) or Task Scheduler (Windows) to set up a daily autorun, the output can be directed to Google Docs or a local file. It is recommended to set it to run in the early morning to avoid network peaks.
Note: For particularly complex papers, it is recommended that the generated abstracts be combined with the original text charts and graphs to validate the key conclusions, which can be used with literature management tools such as Zotero to build a knowledge graph.
This answer comes from the articleArXiv Paper Summarizer: automatic summary tool for arXiv papersThe
May not be reproduced without permission:AI productivity tools " How to solve the problem of inefficiency in reading tons of arXiv papers manually?
