deep-learn

To find frontier research papers, you can use an automated pipeline to locate relevant arxiv publications and compile concise summaries into a single deep-analysis note. This automates paper retrieval and note generation for a specified domain or subtopic.

Tracking learning progress across deep research tasks is handled by an automated pipeline that updates your learning stages automatically after fetching papers and generating deep-analysis notes. This structured workflow replaces manual progress tracking.

Yes, you can preview deep-analysis note generation using a dry-run mode. This allows you to preview outputs for subtopic-focused exploration before the automated pipeline updates with the final frontier paper summaries.

Yes, the automated research pipeline supports subtopic-focused exploration. You can specify a subtopic alongside the main domain, and the agent will fetch frontier papers and generate summaries narrowed to that specific focus area.

You can automate arxiv paper discovery by running a deep-learn command that fetches frontier papers relevant to your domain learning target. The agent then compiles concise summaries from the retrieved papers into a structured note.