Paper Recommendation Guide

Overview

Finding the right papers to read is a research skill in itself. Beyond keyword searches, modern researchers have access to a rich ecosystem of recommendation tools that use citation networks, semantic similarity, co-authorship patterns, and collaborative filtering to surface relevant papers you might otherwise miss.

This skill provides a systematic approach to paper discovery that goes beyond passive reading. It covers algorithmic recommendation services, citation-based discovery techniques, social and community-driven methods, and strategies for building and maintaining a well-curated reading pipeline. The goal is to minimize the chance that you miss an important paper while avoiding information overload.

Whether you are entering a new field and need foundational papers, tracking the frontier of a mature research area, or looking for interdisciplinary connections, this guide provides concrete methods for each scenario.

Algorithmic Recommendation Services

OpenAlex Related Works

OpenAlex provides concept-based and citation-based discovery for 250M+ works across all disciplines: