{"release_id": "2026-05-21", "README": "Semantic Scholar Academic Graph Datasets\n\nThese datasets provide a variety of information about research papers taken from a snapshot in time of the Semantic Scholar corpus.\n\nThis site is provided by The Allen Institute for Artificial Intelligence (\u201cAI2\u201d) as a service to the\nresearch community. The site is covered by AI2 Terms of Use and Privacy Policy. AI2 does not claim\nownership of any materials on this site unless specifically identified. AI2 does not exercise editorial\ncontrol over the contents of this site. AI2 respects the intellectual property rights of others. If\nyou believe your copyright or trademark is being infringed by something on this site, please follow\nthe \"DMCA Notice\" process set out in the Terms of Use (https://allenai.org/terms).\n\nSAMPLE DATA ACCESS\nSample data files can be downloaded with the following UNIX command:\n\nfor f in $(curl https://s3-us-west-2.amazonaws.com/ai2-s2ag/samples/MANIFEST.txt)\n  do curl --create-dirs \"https://s3-us-west-2.amazonaws.com/ai2-s2ag/$f\" -o $f\ndone\n\nSee the \"s2ag.py\" file for Python code that downloads and parses the data.\n\nFULL DATA ACCESS\nDownloading the full data requires an API key, which can be obtained at https://www.semanticscholar.org/product/api#Partner-Form\nFor access to the full datasets, see https://api.semanticscholar.org/api-docs/datasets.\n\nLICENSE and ATTRIBUTION\n\nSee the README files for each dataset for information about licensing and attribution.", "datasets": [{"name": "abstracts", "description": "Paper abstract text, where available.\n100M records in 30 1.8GB files.", "README": "Semantic Scholar Academic Graph Datasets\n\nThe \"abstracts\" dataset provides abstract text for selected papers.\n\nSCHEMA\n - openAccessInfo\n   - externalIds: IDs of this paper in different catalogs\n   - license/url/status: open-access information provided by Unpaywall, linked by DOI or PubMed Central ID\n\nLICENSE\nThis collection is licensed under ODC-BY. (https://opendatacommons.org/licenses/by/1.0/)\n\nBy downloading this data you acknowledge that you have read and agreed to all the terms in this license.\n\nATTRIBUTION\nWhen using this data in a product or service, or including data in a redistribution, please cite the following paper:\n\nBibTex format:\n@misc{https://doi.org/10.48550/arxiv.2301.10140,\n  title = {The Semantic Scholar Open Data Platform},\n  author = {Kinney, Rodney and Anastasiades, Chloe and Authur, Russell and Beltagy, Iz and Bragg, Jonathan and Buraczynski, Alexandra and Cachola, Isabel and Candra, Stefan and Chandrasekhar, Yoganand and Cohan, Arman and Crawford, Miles and Downey, Doug and Dunkelberger, Jason and Etzioni, Oren and Evans, Rob and Feldman, Sergey and Gorney, Joseph and Graham, David and Hu, Fangzhou and Huff, Regan and King, Daniel and Kohlmeier, Sebastian and Kuehl, Bailey and Langan, Michael and Lin, Daniel and Liu, Haokun and Lo, Kyle and Lochner, Jaron and MacMillan, Kelsey and Murray, Tyler and Newell, Chris and Rao, Smita and Rohatgi, Shaurya and Sayre, Paul and Shen, Zejiang and Singh, Amanpreet and Soldaini, Luca and Subramanian, Shivashankar and Tanaka, Amber and Wade, Alex D. and Wagner, Linda and Wang, Lucy Lu and Wilhelm, Chris and Wu, Caroline and Yang, Jiangjiang and Zamarron, Angele and Van Zuylen, Madeleine and Weld, Daniel S.},\n  publisher = {arXiv},\n  year = {2023},\n  doi = {10.48550/ARXIV.2301.10140},\n  url = {https://arxiv.org/abs/2301.10140},\n}"}, {"name": "authors", "description": "The core attributes of an author (name, affiliation, paper count, etc.). Authors have an \"authorId\" field, which can be joined to the \"authorId\" field of the members of a paper's \"authors\" field.\n75M records in 30 100MB files.", "README": "Semantic Scholar Academic Graph Datasets\n\nThe \"authors\" dataset provides summary information about authors.\n\nSCHEMA\nSee https://api.semanticscholar.org/api-docs/graph#tag/Author-Data\n\nThis dataset does not contain information about an author's papers.\nInstead, join with authors.authorId from the \"papers\" dataset.\n\nLICENSE\nThis collection is licensed under ODC-BY. (https://opendatacommons.org/licenses/by/1.0/)\n\nBy downloading this data you acknowledge that you have read and agreed to all the terms in this license.\n\nATTRIBUTION\nWhen using this data in a product or service, or including data in a redistribution, please cite the following paper:\n\nBibTex format:\n@misc{https://doi.org/10.48550/arxiv.2301.10140,\n  title = {The Semantic Scholar Open Data Platform},\n  author = {Kinney, Rodney and Anastasiades, Chloe and Authur, Russell and Beltagy, Iz and Bragg, Jonathan and Buraczynski, Alexandra and Cachola, Isabel and Candra, Stefan and Chandrasekhar, Yoganand and Cohan, Arman and Crawford, Miles and Downey, Doug and Dunkelberger, Jason and Etzioni, Oren and Evans, Rob and Feldman, Sergey and Gorney, Joseph and Graham, David and Hu, Fangzhou and Huff, Regan and King, Daniel and Kohlmeier, Sebastian and Kuehl, Bailey and Langan, Michael and Lin, Daniel and Liu, Haokun and Lo, Kyle and Lochner, Jaron and MacMillan, Kelsey and Murray, Tyler and Newell, Chris and Rao, Smita and Rohatgi, Shaurya and Sayre, Paul and Shen, Zejiang and Singh, Amanpreet and Soldaini, Luca and Subramanian, Shivashankar and Tanaka, Amber and Wade, Alex D. and Wagner, Linda and Wang, Lucy Lu and Wilhelm, Chris and Wu, Caroline and Yang, Jiangjiang and Zamarron, Angele and Van Zuylen, Madeleine and Weld, Daniel S.},\n  publisher = {arXiv},\n  year = {2023},\n  doi = {10.48550/ARXIV.2301.10140},\n  url = {https://arxiv.org/abs/2301.10140},\n}"}, {"name": "citations", "description": "Instances where the bibliography of one paper (the \"citingPaper\") mentions another paper (the \"citedPaper\"), where both papers are identified by the \"paperId\" field. Citations have attributes of their own, (influential classification, intent classification, and citation context).\n2.4B records in 30 8.5GB files.", "README": "Semantic Scholar Academic Graph Datasets\n\nThe \"citations\" dataset provides details about one paper's citation of another paper.\n\nSCHEMA\n - isinfluential: true/false if the citation is considered influential. https://www.semanticscholar.org/faq#influential-citations\n - contexts: Text surrounding the citation in the source paper's body.\n - intents: Classification of the intent behind the citations. https://www.semanticscholar.org/faq#citation-intent\n\nLICENSE\nThis collection is licensed under ODC-BY. (https://opendatacommons.org/licenses/by/1.0/)\n\nBy downloading this data you acknowledge that you have read and agreed to all the terms in this license.\n\nATTRIBUTION\nWhen using this data in a product or service, or including data in a redistribution, please cite the following paper:\n\nBibTex format:\n@misc{https://doi.org/10.48550/arxiv.2301.10140,\n  title = {The Semantic Scholar Open Data Platform},\n  author = {Kinney, Rodney and Anastasiades, Chloe and Authur, Russell and Beltagy, Iz and Bragg, Jonathan and Buraczynski, Alexandra and Cachola, Isabel and Candra, Stefan and Chandrasekhar, Yoganand and Cohan, Arman and Crawford, Miles and Downey, Doug and Dunkelberger, Jason and Etzioni, Oren and Evans, Rob and Feldman, Sergey and Gorney, Joseph and Graham, David and Hu, Fangzhou and Huff, Regan and King, Daniel and Kohlmeier, Sebastian and Kuehl, Bailey and Langan, Michael and Lin, Daniel and Liu, Haokun and Lo, Kyle and Lochner, Jaron and MacMillan, Kelsey and Murray, Tyler and Newell, Chris and Rao, Smita and Rohatgi, Shaurya and Sayre, Paul and Shen, Zejiang and Singh, Amanpreet and Soldaini, Luca and Subramanian, Shivashankar and Tanaka, Amber and Wade, Alex D. and Wagner, Linda and Wang, Lucy Lu and Wilhelm, Chris and Wu, Caroline and Yang, Jiangjiang and Zamarron, Angele and Van Zuylen, Madeleine and Weld, Daniel S.},\n  publisher = {arXiv},\n  year = {2023},\n  doi = {10.48550/ARXIV.2301.10140},\n  url = {https://arxiv.org/abs/2301.10140},\n}\n\n@inproceedings{cohan-etal-2019-structural,\n    title = \"Structural Scaffolds for Citation Intent Classification in Scientific Publications\",\n    author = \"Cohan, Arman  and\n      Ammar, Waleed  and\n      van Zuylen, Madeleine  and\n      Cady, Field\",\n    booktitle = \"NAACL\",\n    year = \"2019\",\n    url = \"https://aclanthology.org/N19-1361\",\n    doi = \"10.18653/v1/N19-1361\"\n}"}, {"name": "embeddings-specter_v1", "description": "A dense vector embedding representing the contents of the paper.\n120M records in 30 28GB files.", "README": "Semantic Scholar Academic Graph Datasets\n\nThe \"embeddings-specter_v1\" dataset provides embeddings representing a paper's contents in vector form.\n\nThe model is based on the SPECTER model available at https://github.com/allenai/specter. However, the embeddings\nincluded in this dataset are not compatible with the embeddings produced by the pretrained model from that repo.\n\nLICENSE\nThis software is released under the Apache 2.0 license. (https://www.apache.org/licenses/LICENSE-2.0)\n\nBy downloading this data you acknowledge that you have read and agreed to all the terms in this license.\n\nATTRIBUTION\nWhen using this data in a product or service, or including data in a redistribution, please cite the following paper:\n\nBibTex format:\n@inproceedings{specter2020cohan,\n  title={{SPECTER: Document-level Representation Learning using Citation-informed Transformers}},\n  author={Arman Cohan and Sergey Feldman and Iz Beltagy and Doug Downey and Daniel S. Weld},\n  booktitle={ACL},\n  year={2020}\n}\n\n"}, {"name": "embeddings-specter_v2", "description": "A dense vector embedding representing the contents of the paper, generated with SPECTER2\n120M records in 30 28GB files.\n", "README": "Semantic Scholar Academic Graph Datasets\n\nThe \"embeddings-specter_v2\" dataset provides embeddings representing a paper's contents in vector form.\n\nThe model is based on the SPECTER 2.0 model available at:\nhttps://github.com/allenai/SPECTER2_0\n\nThese embeddings are compatible with embeddings produced by the pretrained\nmodel, available from https://huggingface.co/allenai/specter2\n\nLICENSE\nThis software is released under the Apache 2.0 license. (https://www.apache.org/licenses/LICENSE-2.0)\n\nBy downloading this data you acknowledge that you have read and agreed to all the terms in this license.\n\nATTRIBUTION\nWhen using this data in a product or service, or including data in a redistribution, please cite the following paper:\n\nBibTex format:\n@article{Singh2022SciRepEvalAM,\n  title={SciRepEval: A Multi-Format Benchmark for Scientific Document Representations},\n  author={Amanpreet Singh and Mike D'Arcy and Arman Cohan and Doug Downey and Sergey Feldman},\n  journal={ArXiv},\n  year={2022},\n  volume={abs/2211.13308},\n  url={https://api.semanticscholar.org/CorpusID:254018137}\n}\n"}, {"name": "paper-ids", "description": "Mapping from sha-based ID to paper corpus ID.\n450M records in 30 500MB files", "README": "Semantic Scholar Academic Graph Datasets\n\nThe \"paper-ids\" dataset provides mapping between different IDs representing a paper\n\nThe primary key of a paper in the S2AG datasets is the corpusId field. However, the public API and web site also accept a sha-based ID, which is also used in some research datasets. This dataset provides a mapping between the different IDs.\n\nSCHEMA\ncorpusId - The paper's primary key\nsha - A sha-based ID that can be used to access the paper via our API or web site\nprimary - There should be only one primary sha for each corpusId. Accessing papers using a non-primary sha will redirect to the primary sha.\n\nLICENSE\nThis collection is licensed under ODC-BY. (https://opendatacommons.org/licenses/by/1.0/)\n\nBy downloading this data you acknowledge that you have read and agreed to all the terms in this license.\n\nATTRIBUTION\nWhen using this data in a product or service, or including data in a redistribution, please cite the following paper:\n\nBibTex format:\n@misc{https://doi.org/10.48550/arxiv.2301.10140,\n  title = {The Semantic Scholar Open Data Platform},\n  author = {Kinney, Rodney and Anastasiades, Chloe and Authur, Russell and Beltagy, Iz and Bragg, Jonathan and Buraczynski, Alexandra and Cachola, Isabel and Candra, Stefan and Chandrasekhar, Yoganand and Cohan, Arman and Crawford, Miles and Downey, Doug and Dunkelberger, Jason and Etzioni, Oren and Evans, Rob and Feldman, Sergey and Gorney, Joseph and Graham, David and Hu, Fangzhou and Huff, Regan and King, Daniel and Kohlmeier, Sebastian and Kuehl, Bailey and Langan, Michael and Lin, Daniel and Liu, Haokun and Lo, Kyle and Lochner, Jaron and MacMillan, Kelsey and Murray, Tyler and Newell, Chris and Rao, Smita and Rohatgi, Shaurya and Sayre, Paul and Shen, Zejiang and Singh, Amanpreet and Soldaini, Luca and Subramanian, Shivashankar and Tanaka, Amber and Wade, Alex D. and Wagner, Linda and Wang, Lucy Lu and Wilhelm, Chris and Wu, Caroline and Yang, Jiangjiang and Zamarron, Angele and Van Zuylen, Madeleine and Weld, Daniel S.},\n  publisher = {arXiv},\n  year = {2023},\n  doi = {10.48550/ARXIV.2301.10140},\n  url = {https://arxiv.org/abs/2301.10140},\n}\n\n\n"}, {"name": "papers", "description": "The core attributes of a paper (title, authors, date, etc.).\n200M records in 30 1.5GB files.", "README": "Semantic Scholar Academic Graph Datasets\n\nThe \"papers\" dataset provides core metadata about papers.\n\nSCHEMA\nSee https://api.semanticscholar.org/api-docs/graph#tag/Paper-Data\n\nThis dataset does not contain information about a paper's references or citations.\nInstead, join with citingPaperId/citedPaperId from the \"citations\" dataset.\n\nLICENSE\nThis collection is licensed under ODC-BY. (https://opendatacommons.org/licenses/by/1.0/)\n\nBy downloading this data you acknowledge that you have read and agreed to all the terms in this license.\n\nATTRIBUTION\nWhen using this data in a product or service, or including data in a redistribution, please cite the following paper:\n\nBibTex format:\n@misc{https://doi.org/10.48550/arxiv.2301.10140,\n  title = {The Semantic Scholar Open Data Platform},\n  author = {Kinney, Rodney and Anastasiades, Chloe and Authur, Russell and Beltagy, Iz and Bragg, Jonathan and Buraczynski, Alexandra and Cachola, Isabel and Candra, Stefan and Chandrasekhar, Yoganand and Cohan, Arman and Crawford, Miles and Downey, Doug and Dunkelberger, Jason and Etzioni, Oren and Evans, Rob and Feldman, Sergey and Gorney, Joseph and Graham, David and Hu, Fangzhou and Huff, Regan and King, Daniel and Kohlmeier, Sebastian and Kuehl, Bailey and Langan, Michael and Lin, Daniel and Liu, Haokun and Lo, Kyle and Lochner, Jaron and MacMillan, Kelsey and Murray, Tyler and Newell, Chris and Rao, Smita and Rohatgi, Shaurya and Sayre, Paul and Shen, Zejiang and Singh, Amanpreet and Soldaini, Luca and Subramanian, Shivashankar and Tanaka, Amber and Wade, Alex D. and Wagner, Linda and Wang, Lucy Lu and Wilhelm, Chris and Wu, Caroline and Yang, Jiangjiang and Zamarron, Angele and Van Zuylen, Madeleine and Weld, Daniel S.},\n  publisher = {arXiv},\n  year = {2023},\n  doi = {10.48550/ARXIV.2301.10140},\n  url = {https://arxiv.org/abs/2301.10140},\n}\n\n\n"}, {"name": "publication-venues", "description": "Details about the venues in which papers are published.", "README": "Semantic Scholar Academic Graph Datasets\n\nThe \"publication-venues\" dataset contains meta-data for a research paper's publication\njournal or venue. The data sources of the venue data comes from The Fatcat Archive, documented\nhere: https://archive.org/details/fatcat_snapshots_and_exports?sort=-publicdate, and the now deprecated Microsoft\nAcademic Graph (MAG).\n\nSCHEMA\n - id: The id of the venue data. The value also corresponds to the \"venueId\" field in the papers dataset.\n - issn: The issn of the publication venue\n - alternate_issns: The alternative issns for the publication venue\n - name: The name of the venue\n - alternate_names: The alternative names for the publication venue\n - url:  The publication venue's url\n - alternate_urls: The alternative urls of the publication venue\n - type: The type (journal / conference) of the publication venue\n\nLICENSE\nThis collection is licensed under ODC-BY. (https://opendatacommons.org/licenses/by/1.0/)\n\nBy downloading this data you acknowledge that you have read and agreed to all the terms in this license.\n\nATTRIBUTION\nWhen using this data in a product or service, or including data in a redistribution, please cite the following paper:\n\nBibTex format:\n@misc{https://doi.org/10.48550/arxiv.2301.10140,\n  title = {The Semantic Scholar Open Data Platform},\n  author = {Kinney, Rodney and Anastasiades, Chloe and Authur, Russell and Beltagy, Iz and Bragg, Jonathan and Buraczynski, Alexandra and Cachola, Isabel and Candra, Stefan and Chandrasekhar, Yoganand and Cohan, Arman and Crawford, Miles and Downey, Doug and Dunkelberger, Jason and Etzioni, Oren and Evans, Rob and Feldman, Sergey and Gorney, Joseph and Graham, David and Hu, Fangzhou and Huff, Regan and King, Daniel and Kohlmeier, Sebastian and Kuehl, Bailey and Langan, Michael and Lin, Daniel and Liu, Haokun and Lo, Kyle and Lochner, Jaron and MacMillan, Kelsey and Murray, Tyler and Newell, Chris and Rao, Smita and Rohatgi, Shaurya and Sayre, Paul and Shen, Zejiang and Singh, Amanpreet and Soldaini, Luca and Subramanian, Shivashankar and Tanaka, Amber and Wade, Alex D. and Wagner, Linda and Wang, Lucy Lu and Wilhelm, Chris and Wu, Caroline and Yang, Jiangjiang and Zamarron, Angele and Van Zuylen, Madeleine and Weld, Daniel S.},\n  publisher = {arXiv},\n  year = {2023},\n  doi = {10.48550/ARXIV.2301.10140},\n  url = {https://arxiv.org/abs/2301.10140},\n}\n"}, {"name": "s2orc", "description": "Full-body paper text parsed from open-access PDFs. Identifies structural elements such as paragraphs, sections, and bibliography entries.\n10M records in 30 4GB files.", "README": "Semantic Scholar Academic Graph Datasets\n\nThe \"s2orc\" dataset contains parsed full-body text from selected papers.\n\nA subset of this data was previously released (in a different format) as S2ORC https://github.com/allenai/s2orc\n\nThe body text is parsed from PDF documents using Grobid, documented at https://grobid.readthedocs.io.\nIts output is converted from XML into a single string with a set of annotation spans.\n\nSCHEMA\n - externalIds: IDs of this paper in different catalogs\n - content:\n   - source:\n\t   - pdfUrls: URLs to the PDF\n\t   - oaInfo: license/url/status information from Unpaywall\n   - text: Full body text as a single string\n   - annotations: Annotated spans of the full body text\n\n\nLICENSE\nThis collection is licensed under ODC-BY. (https://opendatacommons.org/licenses/by/1.0/)\n\nBy downloading this data you acknowledge that you have read and agreed to all the terms in this license.\n\nATTRIBUTION\nWhen using this data in a product or service, or including data in a redistribution, please cite the following paper:\n\n@inproceedings{lo-wang-2020-s2orc,\n    title = \"{S}2{ORC}: The Semantic Scholar Open Research Corpus\",\n    author = \"Lo, Kyle  and Wang, Lucy Lu  and Neumann, Mark  and Kinney, Rodney  and Weld, Daniel\",\n    booktitle = \"Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics\",\n    month = jul,\n    year = \"2020\",\n    address = \"Online\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://www.aclweb.org/anthology/2020.acl-main.447\",\n    doi = \"10.18653/v1/2020.acl-main.447\",\n    pages = \"4969--4983\"\n}\n"}, {"name": "s2orc_v2", "description": "Full-body paper text parsed from open-access PDFs. Identifies structural elements such as sentences and paragraphs, and bibliographic references.\n16M records in 30 6GB files.", "README": "Semantic Scholar Academic Graph Datasets\n\nThe \"s2orc_v2\" dataset contains parsed full-body text from selected papers.\nIt is a replacement for the \"s2orc\" dataset.\n\nThe body text is parsed from PDF documents using Grobid, documented at https://grobid.readthedocs.io.\nIts output is converted from XML into a \"body\" string and a \"bibliography\" string, with a set of annotation spans for each.\n\nSee https://github.com/allenai/s2orc for more details\n\nSCHEMA\n - openaccessinfo:\n   - externalIds: IDs of this paper in different catalogs\n   - license: License information from Unpaywall, linked by DOI or PubMed Central ID\n   - url: URL to the paper, if available\n   - status: Open-access status of the paper, if available\n   - disclaimer: Human readable description of the copyright status of the paper\n - title\n - authors\n - body:\n   - text: Full body text as a single string\n   - annotations: Annotated spans of the full body text\n - bibliography:\n   - text: Full body text as a single string\n   - annotations: Annotated spans of the full body text\n\n\nLICENSE\nThis collection is licensed under ODC-BY. (https://opendatacommons.org/licenses/by/1.0/)\n\nBy downloading this data you acknowledge that you have read and agreed to all the terms in this license.\n\nATTRIBUTION\nWhen using this data in a product or service, or including data in a redistribution, please cite the following paper:\n\nBibTex format:\n@misc{https://doi.org/10.48550/arxiv.2301.10140,\n  title = {The Semantic Scholar Open Data Platform},\n  author = {Kinney, Rodney and Anastasiades, Chloe and Authur, Russell and Beltagy, Iz and Bragg, Jonathan and Buraczynski, Alexandra and Cachola, Isabel and Candra, Stefan and Chandrasekhar, Yoganand and Cohan, Arman and Crawford, Miles and Downey, Doug and Dunkelberger, Jason and Etzioni, Oren and Evans, Rob and Feldman, Sergey and Gorney, Joseph and Graham, David and Hu, Fangzhou and Huff, Regan and King, Daniel and Kohlmeier, Sebastian and Kuehl, Bailey and Langan, Michael and Lin, Daniel and Liu, Haokun and Lo, Kyle and Lochner, Jaron and MacMillan, Kelsey and Murray, Tyler and Newell, Chris and Rao, Smita and Rohatgi, Shaurya and Sayre, Paul and Shen, Zejiang and Singh, Amanpreet and Soldaini, Luca and Subramanian, Shivashankar and Tanaka, Amber and Wade, Alex D. and Wagner, Linda and Wang, Lucy Lu and Wilhelm, Chris and Wu, Caroline and Yang, Jiangjiang and Zamarron, Angele and Van Zuylen, Madeleine and Weld, Daniel S.},\n  publisher = {arXiv},\n  year = {2023},\n  doi = {10.48550/ARXIV.2301.10140},\n  url = {https://arxiv.org/abs/2301.10140},\n}"}, {"name": "tldrs", "description": "A short natural-language summary of the contents of a paper.\n58M records in 30 200MB files.", "README": "Semantic Scholar Academic Graph Datasets\n\nThe \"tldrs\" dataset provides short natural-language summaries of a paper's content.\n\nThe model is based on the SciTLDR model available at https://github.com/allenai/scitldr.\n\nLICENSE\nThis collection is licensed under ODC-BY. (https://opendatacommons.org/licenses/by/1.0/)\n\nBy downloading this data you acknowledge that you have read and agreed to all the terms in this license.\n\nATTRIBUTION\nWhen using this data in a product or service, or including data in a redistribution, please cite the following paper:\n\nBibTex format:\n@article{cachola2020tldr,\n  title={{TLDR}: Extreme Summarization of Scientific Documents},\n  author={Isabel Cachola and Kyle Lo and Arman Cohan and Daniel S. Weld},\n  journal={arXiv:2004.15011},\n  year={2020},\n}\n\n\n"}]}