firecrawl_research_search_papers
Discover research papers across AI, computer science, math, physics, and life sciences by posing a natural-language question. Semantic search returns ranked papers with id, title, authors, and abstract.
Instructions
Primary entry point for finding research papers by topic across AI/ML, computer science, math, physics, biomedical, life sciences, and clinical literature. Semantic (HyDE) search over indexed paper metadata and abstracts; returns ranked papers with paper id, title, authors, and abstract. The query should be a natural-language research topic or question. Run SEVERAL distinct framings of the question (sibling domains, rival methods, dataset or benchmark names, conditions, populations, interventions, or outcomes) rather than one query — recall improves markedly with diverse framings.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| k | No | Number of ranked papers to return (default 40). | |
| to | No | Inclusive upper bound on created/updated date (`YYYY-MM-DD`). | |
| from | No | Inclusive lower bound on created/updated date (`YYYY-MM-DD`). | |
| query | Yes | Natural-language research topic or question, including methods, systems, conditions, populations, interventions, or outcomes when relevant. | |
| authors | No | Author substring filter(s); ALL must match (case-insensitive). | |
| categories | No | Paper category filter(s) (e.g. `cs.LG`); ALL provided values must match. |