Elicit vs Connected Papers

Elicit

Elicit's semantic search capability goes beyond keyword matching to understand the conceptual meaning behind research questions. When users enter a query like 'What interventions reduce anxiety in college students?', the system interprets the underlying research intent and searches across millions of academic papers to find semantically relevant results—even if papers don't contain the exact search terms. The AI understands synonyms, related concepts, and contextual relationships, surfacing papers that traditional keyword searches would miss. Results are ranked by relevance to the specific research question rather than just citation count or recency. Researchers discover more relevant papers faster, including studies they would have missed with traditional keyword-based searches.

✓ Researchers discover more relevant papers faster, including studies they would have missed with traditional keyword-based searches

Connected Papers

Connected Papers' signature feature transforms complex citation networks into intuitive visual graphs where each paper appears as a node, with connections representing citation relationships and content similarity. The AI engine analyzes thousands of papers to identify meaningful relationships, positioning closely related works near each other in the visualization. Node size indicates the paper's influence within the network (based on citation count and centrality), while color coding represents publication year, enabling researchers to instantly distinguish foundational works from recent developments. Users can zoom, pan, and interact with the graph to explore different areas of the research landscape, clicking on any node to view paper details, abstracts, and direct links to full texts. Researchers can comprehend an entire research field's structure in minutes rather than hours, identifying key papers and relationships that would be missed through traditional linear search results.

✓ Researchers can comprehend an entire research field's structure in minutes rather than hours, identifying key papers and relationships that would be missed through traditional linear search results

Elicit

Elicit's data extraction engine automatically reads through research papers and pulls out structured information based on user-defined columns. Researchers can specify what data points they need—such as sample size, study duration, intervention type, primary outcomes, effect sizes, or limitations—and Elicit will extract this information from each paper in a systematic, tabular format. The system handles variations in how information is presented across different papers and journals, normalizing extracted data for easy comparison. Users can export extracted data to spreadsheets for further analysis or meta-analysis calculations. Transforms weeks of manual data extraction work into hours, enabling more comprehensive systematic reviews with larger paper sets.

✓ Transforms weeks of manual data extraction work into hours, enabling more comprehensive systematic reviews with larger paper sets

Connected Papers

Beyond the main similarity graph, Connected Papers provides specialized views that separate a paper's intellectual ancestry from its subsequent influence. The 'Prior Works' view identifies foundational papers that the selected work builds upon, tracing the intellectual lineage and theoretical foundations of research. Conversely, the 'Derivative Works' view shows papers that have cited and built upon the selected work, revealing how ideas have been extended, applied, or challenged. This bidirectional analysis helps researchers understand both the historical context of research and its ongoing impact, essential for comprehensive literature reviews and identifying research trajectories. Users can trace the complete intellectual history of any research topic, understanding both where ideas originated and how they've evolved, enabling more thorough and contextualized literature reviews.

✓ Users can trace the complete intellectual history of any research topic, understanding both where ideas originated and how they've evolved, enabling more thorough and contextualized literature reviews

Elicit

Beyond individual paper analysis, Elicit synthesizes findings across multiple papers to identify patterns, consensus views, and contradictions in the literature. The platform can generate summaries that aggregate key findings from dozens of papers, highlighting where studies agree, where they diverge, and what gaps exist in current research. This synthesis capability helps researchers quickly understand the state of knowledge on a topic without reading every paper in detail. The AI identifies methodological trends, common limitations, and emerging research directions across the literature. Enables researchers to rapidly develop comprehensive understanding of research landscapes and identify opportunities for novel contributions.

✓ Enables researchers to rapidly develop comprehensive understanding of research landscapes and identify opportunities for novel contributions

Connected Papers

Connected Papers allows researchers to build comprehensive graphs by adding multiple seed papers, creating a unified visualization that shows how different papers and research threads interconnect. This feature is particularly valuable for interdisciplinary research or when exploring how different approaches to a problem relate to each other. Users can start with several key papers from their reading list and generate a combined graph that reveals unexpected connections, identifies bridging papers that link different research communities, and provides a holistic view of complex research landscapes spanning multiple sub-fields or methodological approaches. Researchers working on interdisciplinary projects or complex topics can map relationships across multiple research threads, discovering connections and bridging works that would be invisible when examining papers individually.

✓ Researchers working on interdisciplinary projects or complex topics can map relationships across multiple research threads, discovering connections and bridging works that would be invisible when examining papers individually

Elicit

Elicit maintains rigorous academic standards by providing transparent citations and direct links to source documents for all extracted information. Every data point, quote, or finding extracted by the AI includes a citation to the specific paper and often the specific section where the information was found. Users can click through to verify any extracted information against the original source, ensuring accuracy and enabling proper academic citation. The platform also flags when information is uncertain or when papers contain conflicting claims. Maintains academic integrity and enables researchers to confidently cite findings while quickly verifying AI-extracted information.

✓ Maintains academic integrity and enables researchers to confidently cite findings while quickly verifying AI-extracted information

Connected Papers

Each paper in the Connected Papers graph includes comprehensive metadata displayed in an accessible sidebar panel. Users can view full abstracts, author lists, publication venues, citation counts, and publication dates without leaving the platform. The interface provides direct links to the paper on its original source (journal website, arXiv, PubMed, etc.) as well as links to the paper on Google Scholar for additional context. For papers available as open access, Connected Papers often provides direct PDF links, streamlining the research workflow by reducing the need to navigate multiple databases and repositories. Researchers can evaluate paper relevance directly within the platform, accessing abstracts and metadata to make informed decisions about which papers to read in full, significantly accelerating the literature review process.

✓ Researchers can evaluate paper relevance directly within the platform, accessing abstracts and metadata to make informed decisions about which papers to read in full, significantly accelerating the literature review process

Elicit

Elicit supports flexible research workflows that adapt to different research methodologies and project requirements. Users can create custom extraction templates with specific columns tailored to their research questions, save and reuse search strategies across projects, and organize papers into collections for different aspects of their research. The platform supports iterative refinement of searches and extractions, allowing researchers to progressively narrow focus or expand scope as their understanding develops. Collaboration features enable research teams to share workflows and build on each other's work. Adapts to diverse research needs from quick literature scans to comprehensive systematic reviews requiring PRISMA-compliant documentation.

✓ Adapts to diverse research needs from quick literature scans to comprehensive systematic reviews requiring PRISMA-compliant documentation

Connected Papers

Connected Papers generates unique, shareable URLs for every graph created on the platform, enabling seamless collaboration and knowledge sharing among research teams. When a researcher discovers a valuable graph visualization, they can share the exact view with colleagues, supervisors, or students via a simple link. Recipients see the identical graph with all papers and connections preserved, facilitating discussions about research directions, collaborative literature reviews, and educational contexts where instructors want to show students the landscape of a research area. This feature transforms individual discovery into collaborative knowledge building. Research teams can collaborate effectively on literature reviews and research planning, sharing discoveries instantly and building collective understanding of research landscapes without requiring recipients to recreate searches.

✓ Research teams can collaborate effectively on literature reviews and research planning, sharing discoveries instantly and building collective understanding of research landscapes without requiring recipients to recreate searches