conf-papers

You can discover top conference papers by querying DBLP for a chosen year and venue, then enriching the results with Semantic Scholar abstracts and citation counts to compute a recommendation score for ranking.

Yes, you can generate Obsidian notes directly from DBLP and Semantic Scholar results. The process outputs per-paper metadata with a dedicated note_filename, enabling automatic note organization and keyword linking within your vault.

Supported conferences for fetching research papers include major computer science venues such as CVPR, ICCV, ECCV, ICLR, AAAI, NeurIPS, and ICML. You can specify the year to retrieve and rank papers from these specific conferences.

Research papers are ranked using a three-dimensional scoring model that evaluates relevance, popularity, and quality. This model leverages enriched Semantic Scholar data like citation counts to identify top candidates for note generation.

Yes, the recommendation tool requires the Python dependencies 'requests' and 'PyYAML' to function. These libraries facilitate fetching paper data from APIs and managing YAML configurations or Obsidian note structures.

Exported conference paper notes include metadata such as title, authors, venue, year, DBLP URL, arXiv or DOI links when available, and the computed recommendation score to provide comprehensive research context.