@inproceedings{milbauer-etal-2023-newssense,
    title = "{N}ews{S}ense: Reference-free Verification via Cross-document Comparison",
    author = "Milbauer, Jeremiah  and
      Ding, Ziqi  and
      Wu, Zhijin  and
      Wu, Tongshuang",
    editor = "Feng, Yansong  and
      Lefever, Els",
    booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: System Demonstrations",
    month = dec,
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2023.emnlp-demo.39/",
    doi = "10.18653/v1/2023.emnlp-demo.39",
    pages = "422--430",
    abstract = "We present NewsSense, a novel sensemaking tool and reading interface designed to collect and integrate information from multiple news articles on a central topic. NewsSense provides {\textquotedblleft}reference-free verification,{\textquotedblright} augmenting a central grounding article of the user`s choice by: (1) linking to related articles from different sources; and (2) providing inline highlights on how specific claims are either supported or contradicted by information from other articles. Using NewsSense, users can seamlessly digest and cross-check multiple information sources without disturbing their natural reading flow. Our pilot study shows that NewsSense has the potential to help users identify key information, verify the credibility of news articles, explore different perspectives, and understand what content is supported, contradicted, or missing."
}