paper_ranking

What problem does it solve?

This Skill helps researchers quickly identify and prioritize academic papers that are most relevant to their specific research objectives, saving time sifting through vast amounts of literature.

Core Features & Use Cases

• Relevance Scoring: Assigns a numerical score to papers based on their alignment with a given research question.
• Prioritization: Differentiates between empirical and theoretical contributions, favoring domain-specific and evidence-based work.
• Use Case: When exploring a new research area, input your core question (e.g., "impact of exploration strategies on Q-learning convergence") to get a ranked list of the most pertinent papers, complete with notes on their specific contributions.

Quick Start

Rank the provided academic papers based on their relevance to the research objective: "What are the key factors affecting Q-learning convergence?".