+++ title = “VitaLITy: Promoting Serendipitous Discovery of Academic Literature with Transformers & Visual Analytics” date = 2021-08-15T00:00:00 draft = false

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authors = [“Arpit Narechania”,“Alireza Karduni”,“Ryan Wesslen”,“Emily Wall”]

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publication_types = [“1”]

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publication = “In Proceedings of the 2021 IEEE Visualization Conference, IEEE.” publication_short = “In Vis”

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abstract = “There are a few prominent practices for conducting reviews of academic literature, including searching for specific keywords on Google Scholar or checking citations from some initial seed paper(s). These approaches serve a critical purpose for academic literature reviews, yet there remain challenges in identifying relevant literature when similar work may utilize different terminology (e.g., mixed-initiative visual analytics papers may not use the same terminology as papers on model-steering, yet the two topics are relevant to one another). In this paper, we introduce a system, VitaLITy, intended to complement existing practices. In particular, VitaLITy promotes serendipitous discovery of relevant literature using transformer language models, allowing users to find semantically similar papers in a word embedding space given (1) a list of input paper(s) or (2) a working abstract. VitaLITy visualizes this document-level embedding space in an interactive 2-D scatterplot using dimension reduction. VitaLITy also summarizes meta information about the document corpus or search query, including keywords and co-authors, and allows users to save and export papers for use in a literature review. We present qualitative findings from an evaluation of VitaLITy, suggesting it can be a promising complementary technique for conducting academic literature reviews. Furthermore, we contribute data from 38 popular data visualization publication venues in VitaLITy, and we provide scrapers for the open-source community to continue to grow the list of supported venues.” abstract_short = “”

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tags = [“transformers”, “word embeddings”, “literature review”, “web scraper”, “dataset”, “visual analytics”]

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url_pdf = “https://arxiv.org/pdf/2108.03366.pdf” url_preprint = “https://arxiv.org/abs/2108.03366” url_code = “https://github.com/vitality-vis” url_dataset = “” url_project = “http://vitality-vis.github.io” url_slides = “” url_video = “” url_poster = “” url_source = “http://vitality.mathcs.emory.edu/app”

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Authors. Comma separated list, e.g. ["Bob Smith", "David Jones"].