# Academic Search

Scira is an AI-powered search engine designed to provide users with a more efficient and accurate information retrieval experience through a powerful language model and search capabilities. It supports multiple language models, such as Grok 2.0 and Claude 3.5 Sonnet, and integrates search tools like Tavily, providing features such as web search, programming code execution, and weather queries. Scira's main advantages are its simple interface and powerful feature integration, making it suitable for users who are dissatisfied with traditional search engines and want to use AI to improve search efficiency. This project is open-source and free; users can deploy it locally or use the online service provided according to their needs.

PaSa is an advanced academic paper search agent developed by ByteDance, based on large language model (LLM) technology. It can autonomously invoke search tools, read papers, and filter relevant references to obtain comprehensive and accurate results for complex academic queries. This technology is optimized through reinforcement learning, trained using the synthetic dataset AutoScholarQuery, and has shown outstanding performance on the real-world query dataset RealScholarQuery, significantly outperforming traditional search engines and GPT-based methods. The main advantages of PaSa lie in its high recall and precision rates, providing researchers with a more efficient academic search experience.

Sourcely is an AI-driven academic search assistant that provides access to over 200 million research papers and advanced search filters. It simplifies the research process by finding reliable sources, summarizing them, and exporting citations on the spot, helping users save time and improve the quality of their work. Sourcely aims to aid students and researchers in efficiently locating, summarizing, and citing academic resources, particularly for papers and research projects. With affordable pricing, Sourcely offers monthly plans starting at $17 and annual plans at $167, making it budget-friendly for students and researchers.

Undermind is an AI-powered research assistant designed to help researchers quickly and accurately locate the academic papers they need through advanced language models. Founded by two PhD graduates in quantum physics from MIT, it possesses a robust research background. Undermind's search algorithms mimic the systematic discovery processes of humans by iteratively checking results and making key decisions using language models, such as identifying important information and adjusting search strategies, achieving unprecedented accuracy and comprehensiveness.