Abstract
In the rapidly evolving landscape of academia, the scientific research community barely copes with the challenges posed by a surging volume of scientific literature. Nevertheless, discovering research remains an important step in the research workflow which is also proven to be a challenging one to automate. We present Scispace Literature Review, a sophisticated, multi-faceted tool that serves as a comprehensive solution to streamline the literature review process. By leveraging the state-of-the-art methods in vector-based search, reranking, and large language models, the tool delivers features like customizable search results, data exintegration with an AI assistant, multi-language support, top papers insights, and customizable results columns to cater a researcher’s requirements, and accelerate literature exploration. Resources for simplified sharing and documentation further enhance the scope and depth and breadth of research. We demonstrate the extensive use and popularity of the tool among researchers with various metrics, highlighting its value as a resource to elevate scientific literature review. This tool can be tried using this link: https://typeset.io/search.
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Jain, S., Kumar, A., Roy, T., Shinde, K., Vignesh, G., Tondulkar, R. (2024). SciSpace Literature Review: Harnessing AI for Effortless Scientific Discovery. In: Goharian, N., et al. Advances in Information Retrieval. ECIR 2024. Lecture Notes in Computer Science, vol 14612. Springer, Cham. https://doi.org/10.1007/978-3-031-56069-9_28
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DOI: https://doi.org/10.1007/978-3-031-56069-9_28
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