@inproceedings{spangher-etal-2025-novel,
    title = "A Novel Multi-Document Retrieval Benchmark: Journalist Source-Selection in Newswriting",
    author = "Spangher, Alexander  and
      Huang, Tenghao  and
      Huang, Yiqin  and
      Spangher, Lucas  and
      Min, Sewon  and
      Dredze, Mark",
    editor = "Shi, Weijia  and
      Yu, Wenhao  and
      Asai, Akari  and
      Jiang, Meng  and
      Durrett, Greg  and
      Hajishirzi, Hannaneh  and
      Zettlemoyer, Luke",
    booktitle = "Proceedings of the 4th International Workshop on Knowledge-Augmented Methods for Natural Language Processing",
    month = may,
    year = "2025",
    address = "Albuquerque, New Mexico, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/2025.knowledgenlp-1.18/",
    pages = "180--204",
    ISBN = "979-8-89176-229-9",
    abstract = "Multi-document retrieval approaches often overlook the ways different retrievals complement each other when addressing complex queries. In this work, we study journalist source selection in news article writing and examine the discourse roles that different sources serve when paired together, finding that discourse function (not simply informational content) is an important component of source usage. Then, we introduce a novel IR task to benchmark how well language models can reason about this narrative process. We extract a journalist{'}s initial query and the sources they used from news articles and aim to recover the sources that support this query. We demonstrate that large language models (LLMs) can be employed in multi-step query planning, identifying informational gaps and enhancing retrieval performance, but current approaches to interleave queries fall short. By training auxiliary discourse planners and incorporating this information into LLMs, we enhance query planning, achieving a significant 5{\%} improvement in precision and a 2{\%} increase in F1 score over the previous SOTA, all while maintaining recall."
}