Semantic Scholar 4
Similarity-based search engine for scientific literature, using machine learning to find related papers.
Citrus is a similarity-based search engine for scientific literature. You select a paper, start the search, and jump right to the heart of your research domain. Get an overview of important contributions from seminal papers to the state of the art. Citrus helps you find relevant articles in a research field with a single search. It allows you to explore closely related research, find relevant work fast, view important contributions at a glance on a timeline, and avoid missing papers using different taxonomy. Behind the scenes, the similarity of papers is computed using graph and text-based machine-learning techniques. Citrus indexes data provided by Semantic Scholar's Open Research Corpus, which spans over 200 Million publications and around 2 Billion citations.
GenSearch: Build custom AI search engines with various LLMs and search backends without coding.
GenSearch is a platform that allows users to build their own AI search engine. It offers customization options with various LLMs, search backends, and personalized branding. Users can get precise, cited answers or conversational interactions, powered by advanced LLMs and AI crawlers for reliable results. The platform aims to revolutionize search with generative AI, enabling the deployment of AI-driven search experiences that enhance user engagement and satisfaction without coding.
AI-powered academic search engine for scientific research, providing summaries and insights.
VortiX is an AI-powered academic search engine designed for scientific research. It helps users find relevant citations, generate summaries, and synthesize insights to accelerate their research process. VortiX searches across a large database of academic papers, providing accurate results and clear explanations.
Visual tool for researchers to find and explore relevant academic papers.
Connected Papers is a visual tool designed to help researchers and applied scientists discover academic papers relevant to their field. It allows users to get a visual overview of a research field, identify the most popular papers, explore the dynamics between different areas of study, and ensure they haven't missed key papers. The tool supports bi-directional exploration, enabling users to discover both prior and derivative works related to their area of interest. It leverages the Semantic Scholar database, containing hundreds of millions of papers from all fields of science.
